WPC 480_ASU_ASSIGNMENT 2024_PRODUCTION RISK MANAGEMENT OF INDONESIAN BREEDERS

PRODUCTION RISK MANAGEMENT OF INDONESIAN BREEDERS

ARIZONA STATE UNIVERSITY

WPC 480 - STRATEGIC MANAGEMENT

SPRING 2024

INTRODUCTION:

Indonesia's economic growth is expected to continue to increase in line with the

national economic recovery after the Covid-19 pandemic. Amidst the uncertainty of the

global situation, the world is currently faced with a food crisis. However, Indonesia is able to

survive and experience positive economic growth. This growth was triggered by an increase

in domestic consumption, especially animal feed products from the livestock subsector

(Prilliadi 2022). On the other hand, the domestic supply of livestock products tends to be very

low and dependent on imports, while domestic consumption continues to increase, causing a

high consumption demand gap (Yusdja and Winarso 2016). In particular, the livestock

subsector has received less attention because the government has focused more on increasing

food crop production, especially rice. Therefore, support for increased production through

credit is one of the efforts that can be made by the government to increase production inputs

in the livestock subsector so that it can build production competitiveness by utilizing its

comparative advantages.

The livestock subsector plays an important role in supporting the success of Indonesia's

economic growth. This is reflected in the increase in exports of livestock products, both

poultry and cattle, which fill the ASEAN market (Trobos Livestock 2019). The realization of

exports of livestock subsector products including dairy products, processed chicken meat,

animal feed, non-food animal products, hatching chicken eggs, Day of Chicken (DOC), and

frozen semen also contributed to the country's foreign exchange (DKPP Jabar 2020).

Currently, livestock sub-sector products have been able to fill demand from various countries

such as Singapore, Myanmar, Vietnam, Malaysia, Hong Kong, China, Papua New Guinea,

East Timor, and even Japan, which is known for its high food safety (Disnakkeswan NTB

2020).

Market opportunities for livestock commodities in the global market are still wide open,

so cooperation efforts with livestock business actors are needed (Alamsyah 2022). The

superiority of halal products in the livestock subsector in Indonesia is also an attraction for

export to Muslim-majority countries (Ditjen PKH 2019). The demand for meat, both poultry

and cattle, in Indonesia is expected to continue to increase along with the increase in

population and the demand for animal protein (Romadhoni 2014). Several policies of the

Ministry of Agriculture support the improvement of the quality of livestock products to be

exported, including the improvement of the Good Breeding Practices system, animal welfare

principles and veterinary certification regarding animal health status and food safety

assurance. Therefore, support from relevant stakeholders is needed, especially in

implementing international standards from upstream to downstream as an effort to increase

competitiveness. Development of MSMEs and Product Processing Units (UPH) can also

increase added value and product competitiveness.

Basically, the livestock subsector is always faced with uncertainty and high production

risks caused by various factors such as livestock mortality, foot and mouth disease (FMD),

constrained input factors, rising feed prices and other factors that cause low domestic

productivity (Salman 2014; BPS 2015a). The development of the livestock subsector is

inseparable from various challenges, especially dependence on imports that are not supported

by the independence of productive businesses, causing the livestock subsector in Indonesia to

continue to lag behind and be difficult to develop. Livestock business is one of the

prospective businesses but also requires high maintenance. However, the availability of

forage and grass is still available in the rural environment, so the livestock subsector is better

pursued in the countryside. However, another obstacle that poses a threat is the presence of

disease outbreaks such as foot and mouth disease which is a major threat because it can cause

losses, this of course can cause a decrease in the interest of farmers to develop their business

due to the high risks faced related to diseases suffered by livestock (Doudna and Sternberg

2019).

Therefore, it is important for farmers to implement risk management to prevent losses

due to livestock mortality or reduce the impact that will arise due to production risks. Some

of the risk management that farmers can do is by vaccinating livestock as a preventive effort

or maintaining the immune system of livestock by giving vitamins and maintaining cage

cleanliness. In addition, an increase in public awareness about the risk of zoonotic disease

spread related to livestock products can increase interest in replacing animal protein with

non-animal alternatives, thus reducing consumer demand for livestock products. Especially

the demand for halal food which has a fairly high standard free from disease. Therefore, the

number of consumers also has an impact on food production that meets halal requirements to

meet the large domestic market demand. Support for farmers in terms of financing can

encourage livestock businesses to meet high local demand and depend on imports. The

amount of capital certainly affects spending decisions in business activities to increase

income. Efforts to achieve profits through business activities are more easily achieved if

supported by business credit. The higher the business capital, the easier the procurement of

production factors, so that it can indirectly increase production yields. According to the

Directorate General of PKH (2021), based on the Ministry of Finance's program credit

information system (SIKP), the realization of people's business credit (KUR) in the 2015-

June 2019 period of 13.8 trillion focused on developing productive businesses for breeding

and cultivating cattle, dairy livestock, goats/sheep, poultry, and a combination of

agriculture/plantations with the livestock sector. This indicates the increasing confidence of

the banking sector in the livestock sector business. In addition, after the issuance of Law No.

19 of 2013 on the protection and empowerment of farmers, the AUTP scheme was

implemented in 2015, which was then followed by the AUTP scheme Cattle Business

Insurance (AUTS) in 2016 that covers buffalo. This scheme is implemented as a form of

avoidance as well as reduction of risks related to the environment (natural, social, economic,

and cultural) specifically to the agricultural sector (Pasaribu 2021).

However, the misconception that KUR funds should be used as capital to increase

production inputs has shifted to grant funds, which has triggered a lot of moral hazard among

the creditor community, leading to a continued contraction in credit growth. To optimize the

role of credit, it is necessary to review the utilization of credit in order to provide greater

benefits, especially for agricultural development. This is because credit does not fully provide

a positive impact (Chandio et al. 2018; Darfor et al. 2021). This is also reflected by data

showing that a small proportion of households chose to increase debt due to the impact of

Covid- 19 (Bank Indonesia 2021).

1.1 Problem Formulation

Farmers often found in developing countries such as Indonesia are small-scale, poor, or

non-commercial farmers who do not have strong capital. Therefore, the government came up

with a policy of providing financing and capital facilities as one of the strategies to empower

farmers and micro business actors (Law of the Republic of Indonesia 2013; Presidential

Decree of the Republic of Indonesia 2015). With the Covid-19 outbreak in mid-March 2020,

the livestock subsector became one of the subsectors that felt the impact of the pandemic. As

a result of the work from home (WFH) policy, livestock farmers suffered considerable losses

due to the absence of absorption of livestock products due to the non-operation of restaurants,

markets, hotels, catering businesses and businesses related to the livestock product processing

industry. This problem then causes "over supply" because market demand has decreased

dramatically while farmers must continue to produce livestock even though they cannot be

sold and continue to be in the jug causing farmers to still have to provide animal feed,

vitamins, and vaccines to prevent livestock deaths due to viruses so that livestock can stay

alive and reduce losses due to disease and disease livestock mortality. This then causes

farmers to experience "high-cost" or bloated production costs. In addition, the price of feed

continues to rise due to the increase in the price of raw materials for making animal feed. The

increase in the price of chicken feed has caused problems for farmers, due to the initial

problem, namely the very low selling price of livestock products and the difficulty in selling

livestock products, so that farmers cannot afford to buy animal feed and cause death for

livestock (Lokataru 2020). As a result, farmers have no other choice but to sell their livestock

at prices below the reference purchase price in order to avoid greater losses.

The main obstacle faced by farmers during the pandemic is the difficulty in selling their

livestock because large companies or so-called integrators have also lost the market, as a

result, livestock products are not optimally absorbed due to decreased demand. In addition,

the components of production costs, such as in chicken, spend the most on the purchase of

DOC or chicken seeds and animal feed (Ramli 2021). Meanwhile, farmers are forced to sell

livestock in order to repay loans to breeding companies that will be repaid when they succeed

in selling their livestock, but the non-absorption of livestock products due to decreased

demand also triggers losses for farmers which causes farmers to have difficulty repaying their

loans. As a result, many farmers end up giving up their wealth assets to cover the losses.

Thus, the implications of these complex problems cause high production risks in the livestock

subsector so that farmers need to carry out risk management to avoid these losses.

Some steps taken by the government to reduce the risk of losses experienced by farmers

include: First, the government can allocate capital in the form of credit or interest subsidies to

help farmers continue to produce. Second, the government can absorb the "over supply" by

allocating the livestock products to the non-cash food assistance program (BPNT) or other

social assistance in the form of purchasing chicken meat or eggs. This can certainly absorb

the excess supply of livestock subsector products so that not only farmers are helped by the

absorption of livestock products but beneficiary families (KPM) can also fulfill their protein

needs so that they can indirectly improve community nutrition (Khudori 2020).

Credit is one source of capital that is useful for increasing production inputs and farm

income (Soekartawi 2002). Credit is expected to increase the productivity and income of

farmers, which are still considered low (BPS 2015a). The distribution of credit to the

agricultural sector can be an incentive for farmers to increase their production. In addition to

being one of the policy instruments, credit is considered capable of breaking the "vicious

circle" of poverty among rural farmers (Hashim et al. 2016). In addition, the utilization of

agricultural insurance for farmers can also be an alternative that can be done to reduce the

risk of production failure. Accessibility and socialization of agricultural insurance needs to be

developed and expanded so that the economy can continue to be pushed forward, so that a

healthier business system can be created. This can be done by cooperation between the

government (central and regional coordination) in terms of building regional integration that

can encourage livestock business activities in rural areas to continue to produce increased

production and profits of farmers that can create employment opportunities and the provision

of supporting facilities such as financing, infrastructure, and other services. The private sector

will be encouraged to invest in supporting economic or business activities at the farm level by

providing capital support in the form of credit and agricultural insurance. This will create

self-reliance at the rural level.

However, it is undeniable that access to bank credit is still quite difficult for farmers.

Agricultural credit is generally always in demand by smallholders. Access to credit by

smallholder farmers from formal institutions such as banks is still a challenge due to the

collateral requirements. The microfinance sector fills the gap to some extent in some

countries, but informal lenders still control a large part of the agricultural credit market. More

often, these moneylenders are part of the agricultural value chain on the demand or supply

side of the farmer (Chatterjee and Oza 2021). Several previous studies have analyzed

production risk factors in livestock businesses in general. However, there is no analysis of

coping strategies carried out by farmers in facing production risks and how risk management

is carried out by farmers. In particular, the data used in this study is sourced from the 2014

Livestock Business

1.1 Production Factors and Production Risks of Livestock Business in Indonesia

Research on production factors and production risks in livestock businesses has been

conducted by many previous researchers. There are several factors that can reduce production

risk as well as increase production risk, but there is no research that formulates risk

management carried out by farmers, both preventive efforts, risk mitigation and coping

strategies carried out, especially in the use of credit by farmers. Analysis of factors affecting

production and production risk in this study uses the Just and Pope (1976) Model which

estimates the production function and risk function. The production used in this study is the

Cobb-Douglass production function in the form of a natural algorithm. In addition, this study

uses secondary data from the 2014 Livestock Business Household Survey in Indonesia which

can provide an overview of the livestock subsector (poultry and dairy cattle) on a national

scale. Thus, the risk management carried out can also be used as a basis for implementing a

policy. This research can also be used as a further study considering that the 2023

Agricultural Census is being conducted. Thus, it is hoped that this research can be a study

that represents livestock businesses in the 2014 period that can be used as a comparison with

the results of the next agricultural census data.

Here are some previous studies that discuss production factors and production risks in

the livestock subsector. Research on production risk in dairy farming using sanitation risk

variables, namely the risk factor if milk is contaminated with bacteria so that it requires cage

construction that meets the requirements and the importance of sanitation, the availability of

clean water, the health of dairy cows, the risk of unclean cow udders. Then the risk of

distribution or delay in milk delivery to the milk processing industry. Production input risk is

the continuous availability of feed. External risks such as the involvement of business

partners as input providers, the risk of high feed and concentrate prices, the risk of forage

feed quality and quantity, and the risk factor of unqualified cow seeds are described in

research (Septiani 2016; Firlia 2017; Noviana 2020). Research on production risks and risk

preferences of layer and broiler farms uses disease risk variables and drinking water sources

as the two main sources of risk in layer farms (Vinanda et al. 2016; Suyudi et al. 2019; Sayid

Akbar et al. 2022).

Research on production risk and risk preferences of shrimp farmers (Hartoyo 2018).

Research by Kurniati (2015) showed that most farmers in Sambas Regency behaved neutrally

in the face of risk (risk neutral) which amounted to 48.39 percent, while those who behaved

fearfully in the face of risk (risk averter) amounted to 38.71 percent and the remaining 12.9

percent were willing to take risks (risk lover). Farmers who are neutral to risk (risk neutral)

are farmers who have a rational attitude in the face of risk,

To achieve food self-sufficiency, the government and non-governmental organizations need

to continue to encourage agricultural business activities actively and more intensively. There

are three suggestions that can be done, namely by improving the ability of human resources

(farmers and breeders), developing supporting infrastructure, and finally improving the

smoothness and access to credit, information systems, and distribution of inputs and outputs

to farmers and breeders (Asnah et al. 2015).

Thamrin's research shows that the factors that influence the production of coffee plants

are land area, urea fertilizer, ZA fertilizer, and the amount of labor. With the proper allocation

of agricultural inputs, especially the use of appropriate fertilizers, it can increase production

yields and increase greater income for farmers (Thamrin et al. 2015). Research by Maertens

et al. (2014) provides considerable knowledge by analyzing the relationship between attitudes

towards risk and investment decisions. Risk-taking behavior seems to be driven by credit

constraints combined with non-convexities in production. In particular, the investment

potential of higher education and irrigation is strongly associated with risk-taking behavior. In

addition, this study also explains that creating real potential for investment in high-cost

projects will lead to risk-averse decisions (Maertens et al. 2014).

Research by Gomez-Limon et al. (2002) shows a variety of attitudes to risk among

farmers, which mainly shows a relatively high absolute risk aversion coefficient (DARA) of

41 percent indicating that farmers have a high aversion to risk or tend to be "paranoid" and

relatively constant risk aversion (CRRA) represents farmers' behavior towards risk. The

results show that most food crop farmers are risk-averse. Regression results of other studies

show that access to microcredit, income status, age, education and household size are

significant determinants of farmers' risk attitudes (Dadzie and Acquah 2012).

Virginia farming households on the island of Lombok are risk takers in production and

labor allocation decisions but risk averse in consumption decisions. Increased production and

price risk of virginia tobacco, giving positive direction or simultaneously, have a positive

influence on the behavior of farmers in production, consumption, labor allocation, which will

have a positive effect on the income and economic welfare of farmer households (Siddik et

al. 2015). In addition to the factors that contribute to production, there are also factors that

influence other influential factors such as farmers' knowledge, attitudes, and skills in

conducting production activities. Farmers' knowledge in cultivating wetland rice is included

in the medium criteria, farmers' attitudes in cultivating rice are included in the high criteria,

which means that farmers are open to any information, innovations, programs, and

government recommendations in rice farming activities. While farmers' skills in farming in the

medium criteria, namely with an average score of 30.62. Overall, the behavior of farmers in

cultivating lebak swamp rice is in the high criteria, this can be one of the factors that can

reduce production risk (Rambe and Honorita 2011).

Research by Lawalata et al. (2017) shows that the amount of organic fertilizer, the

amount of phonska fertilizer, the amount of fungicides, the amount of l a b o r , th e age of

farmers and farming experience has an influence and is significant to production risk, while

the price of organic fertilizer, the price of phonska fertilizer, the price of fungicides, l a b o r

wages, the age of farmers and farming experience has an influence and is significant to

income risk. The majority of shallot farmers in Bantul Regency have risk averse behavior as

many as 44 farmers (73.33%) although shallot farming is risky. Farmers' age, education,

shallot farm income and shallot farm income are significant and affect farmers' behavior

towards risk. The results of this study are in line with the theory of Moscardi and de Janvry

(1977) where farmers tend to reject risk (Hamal and Anderson 1982).

Research by Olarinde et al. (2019) shows that farmers face different types of risks in

maize production: natural, social, economic and those related to crop production (technical).

Specifically, the following are suggested: natural risk issues, for example, can be addressed

through technological changes, such as breeding for drought tolerance, pest and disease

resistance, and dwarf varieties. For social risks, institutional and policy interventions that

regulate animal movement and authorized periods for forest fires can contribute to addressing

the problems posed by this type of social risk. However, a sustainable solution is the

"sedentarization" of livestock through intensification of crop-livestock integration. For

economic risks, farmers need to be more organized to have an impact on the market.

However, maize farmers do not have a strong association to protect their interests. Thus,

institutional innovation is needed to make a major contribution to addressing the above

economic risks. Finally, for risks related to the production process, addressing production

issues from technical risks will require a combination of technological changes and policy

interventions. It can be concluded that farmers' risk attitudes are directly responsible for their

level of maize cultivation. The level of risk aversion results from the interaction of perceived

socioeconomic, institutional and agricultural characteristics that characterize farm

households. The level of risk aversion also supports the fact that maize sustainability can be

achieved by tailoring program design to smallholder needs based on the implications of these

factors on farmer behavior.

In addition, research by Nabilla et al. (2014) showed that the variables of land area,

number of seeds, number of pesticides, number of fertilizers, and labor had an effect on land

area. However, partially, the variables of the number of seeds, the amount of pesticides, and

labor have a significant effect on corn production, while the variables of land area and the

amount of fertilizer have no significant effect on corn production. Based on the results of

other analyses, the variables of soybean harvested land area, subsidized fertilizer allocation

and average altitude from sea level are variables that have a significant effect on soybean

production. The coefficient of determination resulting from the semiparametric spline

regression model is 98.2% (Amelia and Budiantara 2013).

Some previous studies used different analysis methods. Most studies use the Moscardi

and de Janvry (1977) approach method, including research (Hamal and Anderson 1982;

Gomez-Limon et al. 2002; Dadzie and Acquah 2012; Maertens et al. 2014; Asnah et al.

2015; Kurniati 2015; Thamrin et al. 2015; Lawalata et al. 2017; Olarinde et al. 2019).

Meanwhile, several other studies used regression methods (Siddik et al. 2015), descriptive

statistics (Rambe and Honorita 2011), combined DEA (Data Envelopment Analysis) analysis

with output oriented assumptions, Ordinary Least Squares (OLS) regression analysis, and

Cobb Douglas production function analysis and the Just-Pope heteroscedasticity model in

research (Lawalata et al. 2017). The analysis method using the cobb-douglas model

production function and the income function of multiple linear regression equations in

research (Nabilla et al. 2014; Lawalata et al. 2017). There are also studies that use the Spline

analysis method with the Optimum Knot Point obtained from the Generalized Cross

Validation (GVC) Method (Amelia and Budiantara 2013). The results of the research are also

diverse where there are factors that can increase or decrease production risk. Some risks from

natural, social, economic, and production are able to significantly influence. Thus, it is also

necessary to analyze risk management that can be done as a step to prevent or reduce

production risk.

1.2 Risk Management of Indonesian Farmers Facing Production Risks

People's Business Credit or also called (KUR) in the period 2015 to June 2019 has

disbursed funds amounting to 13.8 trillion. This credit can be utilized for business scale

development, increasing production inputs, and a form of risk mitigation that can be useful as

a form of capital assistance facility from the government. The credit distribution policy has

been regulated as in Ashari's research (2019) explaining to strengthen the position of the

agricultural sector, strengthening the capital of agricultural business actors and potentially

becoming a strong foundation to support Indonesia's economic development (Kementan

2021). This is related to the function of capital as a facilitating factor for agricultural

development. This is explained by Tampubolon et al. (2017) that credit can help businesses

to develop product innovation by providing productive investment loans.

Farmers or breeders who are often found in developing countries such as Indonesia are

small, poor, or non-commercial farmers who do not have strong capital. Therefore, the

government created a policy of providing financing and capital facilities as one of the

strategies to empower farmers and micro-entrepreneurs (Law of the Republic of Indonesia

2013; Presidential Decree of the Republic of Indonesia 2015). Credit is one source of capital

financing that is useful for increasing production inputs and farm income (Soekartawi 2002).

Credit is expected to increase the productivity and income of farmers, which are still

considered low (BPS 2015a). The distribution of credit to the agricultural sector can be an

incentive for farmers to increase their production. Apart from being a policy instrument,

credit is considered capable of breaking the "vicious cycle" of poverty among rural farmers

(Hashim et al. 2016). However, it is undeniable that access to bank credit is still quite

difficult for farmers. Agricultural credit is generally always in demand by smallholders.

Access to credit by smallholder farmers from formal institutions such as banks is still a

challenge due to collateral being the main requirement. The microfinance sector fills the gap

to some extent in some countries, but informal lenders still control a large part of the

agricultural credit market. More often, these moneylenders are part of the agricultural value

chain on the demand or supply side of the farmer (Chatterjee and Oza 2021).

In general, the agricultural sector is constantly faced with problems such as high price

volatility and bad debts. The weaknesses of smallholder farmers are simple management and

operational systems and limited capital. These weaknesses indicate that the business is still

inefficient because existing production factors have not been optimally utilized. Variations in

mastery in allocating production factors show the efficiency of farmers in running a business

(Wakhidati et al., 2017). Capital and labor as production factors are factors that have a

significant effect on production value (Aris, 2020). This means that any additional capital and

labor will increase the value of production. Business development can be done because of the

capital owned by farmers. Another problem is that the majority of farmers in Indonesia are

classified as small and marginal farmers with decreasing and fragmented land ownership. The

low scale of business at the farm level can certainly lead to minimal production levels which

have an impact on the low income of farmers. This problem leads to uncertainty that can

make farmers very vulnerable to risk. In general, agricultural production has always been

dependent on the use of limited agricultural inputs, such as fertilizer and credit, due to several

constraints in accessing these inputs. As a result, farmers experience low yields and

agricultural production, making them heavily dependent on casual labor, charcoal and

firewood sales, and petty trading to earn cash income to buy food. Farmers also face

marketing problems, including fluctuating crop prices, lack of farmer associations to negotiate

selling prices, poor road infrastructure and long distances to markets (Coulibaly et al. 2015).

Therefore, credit assistance from the government allocated in the form of the People's

Business Credit (KUR) program needs to be reviewed for credit utilization. The amount of

resources allocated to livestock business interests can be one indicator that can be used to

assess the success of credit utilization.

With the research on risk management analysis that is usually used by farmers, it

certainly helps farmers and microfinance institutions, formal and non-formal credit

institutions to re-evaluate related to solving debt problems that cause bad credit. Although the

government in India has issued orders related to agricultural loan waivers to ease the financial

difficulties of farmers. However, in the long run, it can lead to the destruction of the trust of

banking financial institutions towards farmers due to the lack of repayment of credit loans

provided (Narayanan and Mehrotra 2019). This study therefore suggests three possible loan

insurance product instruments that can address the consequences of farmers' repayment

failure,

Some of the strategies that can also be used to mitigate farmer business failure in India

are increasing income through technological improvements by strengthening the seed sector

or superior seeds and knowledge dissemination systems, supporting high-value commodities,

developing value chains by connecting marketing production centers and setting minimum

prices in the event of a commodity price drop during the harvest. In addition, the success of

farmers depends on the level of production produced and marketing carried out, so it is

necessary to have cluster agriculture and farmer producer organizations and farmer groups

that can support this success (Joshi 2018). The second is to generate employment

opportunities, especially for millennial farmers (young farmers) by utilizing their aspirations.

With the regeneration of farmers, especially in Indonesia, which has a demographic bonus,

this can create a fairly high chance of success if supported by the provision of entrepreneurial

knowledge that can help novice farmers in managing their business (Bank BJB 2022).

The third strategy is to develop agricultural infrastructure that can be useful for

processing agricultural products (Ogwuike et al. 2022). With adequate infrastructure, an

organized, unfragmented and efficient agricultural supply chain can certainly increase

productivity, which has an impact on increasing the turnover of agricultural businesses.

Fourth, by improving the quality of rural life. Farmers generally carry out most of their

production activities in the village. Therefore, support for basic facilities such as sanitation,

drainage of health centers, clean drinking water and schools can improve the quality and

welfare of farmers (Isoto et al. 2017). This study shows that the loss of health of farmers who

take credit can affect the increase of fungibility credit where credit can be utilized to increase

resources that should be used for input purchases are diverted to overcome health problems

for treatment and other medical needs (Chandio et al. 2017; Chandio et al. 2018).

The results of this study are in line with DeLoach and Smith-Lin's (2018) research

which explains that households respond to changes in farmer health in different ways. First,

households that have accessibility to credit will tend to increase loans compared to

withdrawing savings or selling assets. However, also There are farmer households that do not

have access to financial institutions tend to liquidate their assets for treatment needs. There is

also research that shows that farming households in Bangladesh with access to microcredit do

not need to sell their livestock because they tend to get a higher rate of return compared to

farmers who do not use credit in dealing with health problems (Islam and Maitra 2012).

It is therefore important to ensure that low-income rural households can access medical

care as needed. In addition, implementing these four strategies can support national economic

recovery by identifying and assessing agricultural loans that can contribute to increased

national income through increased income earned by farmers, as agricultural credit systems

are generally long-term in most developing countries (Okorie and Iheanacho 2014).

Thus we will realize that production depends not only on labour and "capital", but on

the whole set of factors of production, it is quite possible that it is simultaneously true that a

particular American capital equipment (tractor) can release (save) a greater amount of labour

in India than in the United States, but will produce less wheat in India than in the United

States. This relates to the lack of incentive to invest in developing countries like India

(Makower and Nurkse 1953). In addition to experience in the agricultural business, the

importance of farm management can improve the ability of farmers in Ilocos to develop

better coping strategies. Where farmers in Ilocos understand well the conditions of their

business environment so that in implementing coping strategies they tend to integrate first

with the production practices they have by diversifying land that can reduce the risk of crop

failure or irrigation management (Catudan and Martin 2013).

In addition, farmers in Ilocos also seek solutions to problems in the field by conducting

research to determine their efficiency and effectiveness. In addition, it is also necessary to

socialize the importance of agricultural insurance so that it can develop more broadly and is

not only limited to commodities such as rice and cattle and can also provide technical

guidance and risk management in order to reduce risks in farming (Asnah et al. 2015). The

existence of agricultural insurance can certainly reduce the burden on farmers from losses due

to farming risks. It is necessary to develop an insurance model that combines the interaction

between the government, the private sector and farmers (public-private-partnership) in

integrated farming financing. In addition, the development of an insurance model based on

the use of technology based on farmer productivity can be an option so that farmers can

choose insurance that is more suitable, simpler, and more profitable (Pasaribu 2021). Thus, a

better agricultural insurance scheme can be implemented in the future.

Some studies also explain the existence of partnerships between local chicken farms

and restaurants or restaurants as suppliers of local chicken meat to meet the demand for local

chicken menus (Nurlaelah et al. 2022). Demand fulfillment is also related to with the

fulfillment of consumer tastes that prefer native chicken menus compared to broiler chickens.

Several partnerships of native chicken farms with restaurants, SMEs, communities,

organizations, or other partners have also been found as an alternative strategy used to

increase the certainty of sales of production products (Hadi et al. 2021; Prabewi and

Listiyowati 2021; Ulfa et al. 2021; Rosmalah et al. 2023; Silaban et al. 2023)

Another risk management that can also be applied by farmers is by implementing an

integrated farming system or also known as a crop-livestock integration system. According to

some studies, this strategy can reduce production risk due to the balance of ecosystems that

can suppress pest and disease disorders (Imron 2020). Based on previous research, it also

explains that the crop-livestock integration model or crop diversification can provide higher

income (Khandari 2015; Rahmi 2015; Idris 2022). In addition, the study of partnerships has a

broader explanation when examined in collaboration with livestock businesses. In the dairy

farming business, there are many research results that show that the success of dairy farming

is also inseparable from its partnership with village unit cooperatives (KUD).

In some studies, it is explained that KUD has an important role as a provider of

production facilities, ease of obtaining animal feed, technical guidance and knowledge,

management, dairy cattle credit programs such as KKP-E, counseling, capital assistance,

health checks and treatment of dairy cattle, implementation of artificial insemination,

collecting cow's milk, processing into processed products, and marketing production results

in the form of products both fresh milk and processed products made from cow's milk (Dewi

et al. 2013; Sawantah 2015; Anzory 2018; Soedarto and Hendrarini 2021). Cooperation in the

form of this partnership also uses a lot of core-plasma partnership models where farmers as

(plasma) and cooperatives as (core) partners (Soedarto and Hendrarini 2021). There is also

research that explains the cooperation of KUD with dairy farms is only limited to cooperation

to distribute the results of dairy products because KUD is only as a milk processing industry

(IPS) (Anzory 2018). Sawantah's research (2015) explains that the partnership pattern used

by dairy farmers with the agribusiness cooperative Dana Mulya applies agribusiness

operational cooperation (KOA).

FRAMEWORK

3.1 Theoretical Framework

Production and Production Risks:

Production activities are a series of processes that transform two or more inputs

(resources) into one or more outputs (Pindyck and Rubinfeld 2009). Production can also be

defined as the activity of producing goods and services from inputs in the form of production

inputs, capital, and labor. Production activities aim to produce added value that can be used to

meet the needs of human life. The production process requires at least two inputs to produce

one or more outputs. Thus, the amount of output produced is influenced by the number of

inputs used in one production process.

In conducting a production process, especially in an agricultural commodity, it tends to

require a lot of production inputs. The simplification of the production input-output model is

formulated into a production function. The production function can be defined as the

relationship between production inputs to be used in the production process and the quantity

of output that can be produced (Ragan and Lipsey 2011). In addition, a production function

can also be defined as the maximum amount of output that can be produced from a certain

amount of input (Baye 2010). Thus, a production function can describe the functional

relationship between inputs that are transformed into certain outputs (Doll and Orazem 1984).

In a production function modeling, there are three models of inputs based on the time

horizon, which can be divided into fixed inputs (unchangeable), which are inputs that are

needed in a very short period of time and are fixed, short-term inputs, where some inputs are

fixed and others are variable (or changeable), and finally long-term inputs, where all

production inputs are variable.

Based on economic theory, the production function has three derived concepts, namely

the concept of total production (TP), the concept of marginal production (MP), and the

concept of average production (AP). Total production is the entire amount of output produced

by a production process in a certain period of time. Marginal production (MP) is the value or

amount of change in total output produced when there is a change in the form of either

adding or reducing the amount of a production input used in a production process.

Meanwhile, average production (AP) is the value of output per unit of input, where in the

production function the cateris paribus assumption is often used or changes in input use only

occur in one production input while other production inputs are considered constant. The

relationship between inputs and outputs is explained in the law of diminishing returns, which

means that the use of factors of production (inputs) is increase will cause the amount of

output to decrease over time (Pappas and Hirschey 1995).

The production curve also shows the elasticity of production where there is a rational

area to produce. The concept of production elasticity is the sensitivity of changes in output

due to changes in the use of one unit of input, cateris paribus. Elasticity of production has

three regions in the production curve. Region I and Region III are irrational regions while

Region II is a rational region of production. Region I is an irrational region because every

additional unit of production always gives a larger additional output, cateris paribus. In

addition, in region I, the company's profit has not yet reached the maximum level so that the

addition of inputs can continue to be increased. Region I has an elasticity Ep ≥ 1 and is

limited to the point of the MP = AP curve. Region III is also an irrational region because

every additional input decreases the output produced. Thus, region II is a rational region

because it provides maximum profit by following the law of diminishing return, where each

additional input used will produce a smaller additional output until the maximum is equal to

the additional input, cateris paribus. Region II has an elasticity value between 0 and 1

(0<Ep<1), where the curve starts at maximum AP and ends at MP=0. The production curve

showing the relationship between total production (TP), marginal production (MP) and

average production is described in Figure 2 below.

In running a business, there is one important factor to consider, namely the scale of the

business. Business scale relates to the concept of Long-term costs required to run the

business. Making production decisions in the long run can lead to differences in output

produced at various levels of production so that decision making must be based on

knowledge of minimum production costs. An overview of the long-run average cost (LRAC)

curve that includes all possible short-run average cost (SRAC) curves is depicted in the

following business scale envelope curve.

Business scale shows the relationship between average production costs and changes in

business size. According to Debertin (2012), there are two conditions that will occur if there

is a change in the scale of business in farming, namely economies of scale and diseconomies

of scale. Economies of scale are conditions that occur when the use of inputs increases, the

cost per unit of input will decrease. While diseconomies of scale is a condition that occurs

when an increase in output actually increases the cost per unit of input. Economies of scale

occur when output moves between q0 and q1, while diseconomies of scale occur when output

moves between q1 and q2.

A production function consists of production inputs represented through independent

variables (x) and production outputs represented through dependent variables (y). One of the

most common production functions The Cobb-Douglas function is used to explain the

relationship between the dependent and independent variables. In using the production

function approach, there are several conditions that need to be met, among others, no

observation value is zero, there are no technological differences, and each independent

variable is perfect competition for other independent variables. Some advantages of the

Cobb-Douglas function approach according to Dillon and Hardker (1989) include: (1) the

Cobb-Douglas function approach is relatively easier than other functions and can be made

linear, (2) The results of estimating the line through the Cobb-Douglas function will produce

regression coefficients that can directly show the amount of elasticity, and (3) The amount of

elasticity also shows the level of return to scale.

Risk is a result or a consequence that can occur as a result of making a decision or an

ongoing process or future event. Basically, business decision-making always carries the risk

that the results arising from the decision will not necessarily match expectations. For business

actors in the agribusiness sector, especially at the on-farm level, risks and uncertainties are a

constant phenomenon. Climate change and pest and disease attacks are among the common

sources of risk faced by farmers.

Risks not only arise at the farm level, but can also arise outside of farming activities.

When farmers sell their products, the price is far below expectations, or when farmers buy

superior seeds for their paddy crops, it turns out that the seeds they buy do not have the

productivity that was originally expected, even though the farmers have managed the plants

as well as possible. Thus, there are several risks that are usually faced by a farming activity,

including production risk, price risk, and market risk. Production risk is a risk that can occur

in a farming activity caused by internal and external factors. Production risks that occur in

farming activities can cause the optimal production point on the total production curve (TP)

to not be reached. This condition is caused by the difference or gap between the actual

production amount and the average production amount. Therefore, the nature of production

inputs to risk can be divided into two, namely risk inducing factors and risk reducing factors.

Risk is an event with a probability and outcome of the event that can be calculated by

the decision maker (Debertin 2012). Risk can also be defined as an event with a known

chance of occurrence so that it can be used as a basis for decision making (Ellis 1988). In

addition, risk can also be defined as an event that can cause loss. Thus, in general, risk can be

defined as an event with a chance that can be calculated to minimize losses that can be used

as a basis for making a decision.

Risks faced by farmers consist of risks that can be controlled and risks that cannot be

controlled. Risk factors that can be controlled usually come from internal factors consisting

of the use of production inputs which include the use of feed, fertilizer, labor, medicines and

other production factors. Meanwhile, uncontrollable risk factors come from external factors

such as weather and climate, rainfall, pests and diseases and other external factors. One of the

neoclassical production models regarding the impact of seasonal changes on production risk

on the decision to produce and risk preferences is described as follows.

The curve illustrates the impact of seasonal conditions as one of the risk factors on the

response to fertilizer needs. The following is an explanation of production decisions using the

income variance approach (Ellis 1988), namely:

1. T h e efficient use of input X1 with allocative efficiency is TVP1 which gives the largest

profit at point ab that is possible under good weather conditions. The value of losses incurred

if weather conditions are bad is bj. Farmers operating at this point can classified as farmers

who dare to take risks or commonly called risk takers.

2. The use of input X2 is consistent with the allocative efficiency of TVP2. In good weather

conditions, farmers will earn a profit of ce, while in bad weather conditions farmers will earn

a profit of de. Farmers operating at this point can be classified as risk averse.

3. Input use X3 is consistent with balanced allocative efficiency under both probabilities of

climate events. At TVP1 farmers earn a profit of fh (smaller than ab) and at TVP2 the losses

incurred are hi (smaller than bj). Farmers operating at this point can be classified as risk

neutral.

Risk is closely related to opportunity. Therefore, the measurement of a risk can be

measured using the probability or possibility of a risk occurring from the impact of the risk.

The size of the probability measure needs to be known so that a model is needed in the

measurement. Risk can be measured using three measuring tools, namely, variance, standard

deviation, and coefficient variance. Each of these measuring instruments is interconnected

with each other with the variance value as the basis of measurement for other measuring

instruments. The variance value is a measure used to describe how scattered the data points

are in a sample or data set. Meanwhile, standard deviation is the average value of the squared

difference, where standard deviation aims to see the distribution of data in a sample to see

how far or how close to the average value. Thus, the standard deviation value is obtained

through the squaring of the variance value. Coefficients variance is the resulting ratio of

standard deviation to the expected return value of an event. The return in this case is the

income earned, the production produced, and the selling price.

Decision makers will be better off using coefficient variation when compared to

variance and standard deviation as a measuring tool to determine one of the business

alternatives by considering the risks faced by a business. The smaller the coefficient variation

value can illustrate the smaller the business risk that will be faced. Some models commonly

used in risk measurement are the standard value model (Z-score), determining the value of

standard deviation, variance, and coefficient variation, Just and Pope model, GARCH model,

frontier function merging model with risk function, and various other models. One model that

is often used in determining production risk is the Just and Pope model. The model can

describe the use of production factors that affect production risk through variations in

production and output productivity. The types of production factors can be divided into two,

namely, risk reducing factors and risk reducing factors production factors that are causative

or risk inducing factors (Robinson and Barry 1987).

The total output (Q) in Just and Pope's production function risk model explains that the

total output produced is influenced by the input variables of the production function and the

variance function (risk function). This production function risk model considers the element

of risk that comes from variations in the use of production inputs. The average production

function or f(x) is the functional relationship between the inputs used in production and total

output, while the variance function (risk function) h(x) is the relationship between the

production inputs used and the gap between actual production and average production.

According to Robison and Barry (1987), there are seven assumptions in the model that must

be met by an input as a risk-reducing input.

The Cobb-Douglas function is a production function model that is usually used in a Just

and Pope production risk model. Production risk can be measured using the Just and Pope

Model through estimates of the variables of the average production function and the gap

between actual production and average production for the risk function.

Risk Management Strategy

According to Darmawi (2010), risk management is an effort to find out, analyze and

control risks in every company loss with the aim of obtaining higher company effectiveness

and efficiency. Risk management carried out can reduce risky events that occur within the

company. Risk management can be done if there is awareness about the risks that occur. Risk

management can be carried out through several stages, namely, identifying the risks that

occur, measuring risks, considering the consequences of the risks that occur, and

communicating the risks that occur to all parts to find handling. Risk handling strategies that

can be carried out by business actors can be divided into two (Kountur 2008), namely:

a. Preventive strategy

Preventive strategy is a risk management strategy that is carried out to minimize the

occurrence of risks before the risk occurs. This preventive strategy is usually carried out if the

probability value of a risk is quite high. The strategy that is usually carried out is to avoid the

possibility of risk occurring by creating or improving the procedure system, developing

human resources, and installing or improving physical facilities. In this study, it can be

identified through efforts made by farmers to minimize the risk of disease or death of

livestock. Preventive efforts that are often carried out by farmers are maintaining the

cleanliness of cages using disinfectants, sanitizing clean water for eating and drinking

livestock, agricultural insurance, vaccination, and active efforts of farmers to obtain

information through farmer institutions such as farmer groups, cooperative membership,

association membership, and getting counseling.

b. Mitigation strategy

Mitigation strategies are risk management strategies that are carried out before the

occurrence of risks with the aim of reducing the impact of risks that can be caused.

Mitigation strategies are usually carried out to minimize the impact that has been caused by a

particular source of risk and are usually recommended to handle high risk impacts. In this

study, mitigation strategies carried out by farmers are efforts made to reduce the impact of

greater losses in the event of risks such as livestock affected by disease or livestock death.

Mitigation efforts can be in the form of the use of medicines for livestock affected by disease,

treatment to a veterinarian, or treatment of livestock by farmers independently. There are

three ways that can be done when conducting mitigation strategies, namely:

1) Diversification

It is a way of placing prices or assets in several locations so that if one is disrupted it

will not eliminate all other assets owned. One of the most effective ways to transfer the risk

that occurs is to diversify to minimize the impact of risk.

2) Merger

It is an activity of merging with other business units or companies. Examples of

strategies that are usually carried out are acquisitions or mergers.

3) Risk transfer

It is a way of handling risk by transferring the impact of risk to other parties. Some

strategies that can be done include insurance, leasing, outsourcing, and hedging. The risk

management process according to Kountur (2008) can be seen in Figure 4.

The risk management process can be done by identifying what risks the company

faces, then measuring the risks that have been identified to find out how likely the risk is and

how much impact the risk has. Furthermore, handling risks to provide suggestions on what to

do to handle these risks so that all possible losses can be minimized (Kountur 2008).

c. Coping strategies

Coping strategies are risk management strategies that are carried out after the risk occurs

to reduce the impact that has occurred. Coping strategy is defined as a certain process that is

accompanied by an effort in order to change the cognitive domain and or behavior constantly

to regulate and control external and internal demands and pressures that are predicted to be

able to burden and exceed the ability and ability to cope resilience of the individuals

concerned (Bowman and Stern 1995). In this case, individuals in this study refer to livestock

business households, so there are several coping strategies carried out to reduce the impact of

production risks. Some forms of coping strategies carried out by farmers include productive

loans or credit, installments after production, selling assets, selling production to credit

providers, diversification and other forms of coping strategies.

3.2 Operational Framework

This study aims to answer what are the production risk factors in livestock farming in

Indonesia that will be estimated using two characteristics, namely production input factors

and production risk factors. The production function model of poultry farming uses six

production factors consisting of feed, disinfectant, sanitation, animal health, farming

experience, and number of animals. Meanwhile, the risk function model of poultry farming

uses the same production factors as the production function model with the additional

variables of farmer age, education level, number of dependents, credit, livestock mortality

rate, farmer activeness, and partnership.

In the production function model, dairy farming in Indonesia is analyzed using the

variables of feed, sanitation, animal health, farming experience, and number of livestock.

Meanwhile, the risk function model of dairy farming is analyzed using the production factors

used in the production function model with the addition of farmer age, education level,

number of dependents, farmer activeness, credit, and partnership.

Thus it can be analyzed how the production of livestock businesses and how the

production risks that occur are analyzed using the Just and Pope (1976) model using the

production function and variance function (risk function). Thus, it can also analyze and

formulate risk management carried out by livestock business households in facing production

risks in Indonesia. The risk management carried out is divided into three namely preventive

efforts, risk mitigation, and coping strategies. This framework is outlined in the following

flowchart in Figure 6.

4.1 Evaluation of the Presumptive Model

Basically, in empirical analysis, choosing the right model is very important to ensure that

the model matches the characteristics of the data used. A good or suitable model is one that

can describe the relationship between the relevant variables in the model analysis well

(Gujarati and Porter 2009). The existence of fit between the model and the data can be tested

using various methods such as fit test, assumption test, and evaluation of the quality of model

improvement. Therefore, it is important to note that the selection of a good model is not only

based on statistical accuracy, but also theoretical considerations, experience, and a deep

understanding of the data and the context of the analysis being conducted (Gujarati 2012).

2The model used must meet several criteria, among others, (1) cost-effective, meaning that

the model is as simple as possible, (2) identifiable, meaning that the estimated parameters

must have unique values or for the same purpose and there is only one estimate for each

parameter, (3) goodness of fit, meaning that it can explain the diversity of variation in the

independent variation described in the model and has a high enough R value, (4) theoretical

consistency, (5) predictive power, meaning that it can describe the comparison between

prediction and experience. According to Gujarati (2006), it is said that a good model is a

model that meets the goodness of fit criteria with several more detailed criteria as follows:

1. The suitability of the direction and size of the coefficient of the model obtained based on

the theory used in the study. The coefficient of determination (R2 ) which describes the

fit between the actual data and the estimated data. The coefficient of determination (R2 )

is in the range 0 ≤ R2 ≤ 1 and is positive. Model suitability can be said to be perfect if the

resulting coefficient of determination (R2 ) is equal to 1, whereas if the resulting

coefficient of determination (R2 ) is equal to 0, it can be said that there is no relationship

at all between the dependent variable and the independent variable.

2. The conjecture model is significant in predicting the dependent variable. The hypothesis

test used to check the accuracy of the conjecture model is Test

F. If the value of Fhitung > Ftabel or the probability value is less than the real level (P < α), it

can be said that the model is significant in predicting the dependent variable.

3. Each independent variable is thought to have a significant effect on the dependent

variable. The T test can be used to see the significance of the independent variable. Test

results with the value of tcount> ttabel or the value of the probability value is less than the

real level (P < α), it can be said that the independent variable is significant to the

dependent variable.

4. The OLS (Ordinary Least Square) assumption is fulfilled in accordance with the

requirements so that the OLS assumption is BLUE (Best, Linear, Unbiased, Estimator),

namely a linear model in parameters (coefficients) and there is no multicollinearity.

Multicollinearity in the independent variables is a condition where there is a linear

relationship between the independent variables. The cause of multicollinearity usually

comes from the tendency of economic variables to move simultaneously. This causes the

magnitude and direction of the coefficients to be invalid for interpretation and the results

of the significance test of the estimated model coefficients are invalid. One way to detect

multicollinearity symptoms can be seen from the Variance Infaltion Factor (VIF) value.

If the VIF value> 10, then it can be ascertained that there is multicollinearity. Some ways

to overcome multicollinearity are:

1) Adding observations so that the variance bj becomes smaller

2) Removing independent variables that are strongly correlated with other independent

variables

3) Using Principal Component Analysist (PCA) technique

c. There is no autocorrelation

The resulting error component is not patterned and spreads normally with a mean value

equal to zero, is homoskedasitas (has the same variance), and there is no autocorrelation. The

standard error used in this study is a robust standard error that can overcome potential

heteroscedasticity problems that can occur, thus the estimation results using robust standard

errors can fulfill the prerequisites of the classical assumption test, namely autocorrelation and

heteroscedasticity (Wooldrige 2013).

5.1. Characteristics of Poultry Farmers in Indonesia

The characteristics of poultry farmers used in this study are the results of a description

of farmers running poultry farming businesses in Indonesia. The characteristics of poultry

farms used as variables and samples in this study are described statistically in Table 2. The

total number of poultry farm households used in the production function model and variance

function (risk function) is 20,601 farm households. In the production function model of

poultry farming, six variables were used that were expected to affect the value of production.

The variables used in the production function model are poultry feed, disinfectant, sanitation,

animal health, farming experience, and number of animals. Meanwhile, to estimate the

production risk function model, thirteen variables were used that were thought to affect the

risk of sales turnover. The variables used in the production risk function model consist of

variables used in the production function model with additional risk variables, namely farmer

age, education level, number of dependents, livestock mortality rate, farmer activeness,

credit, and partnership. The following is the descriptive statistics of the sample of poultry

farming households in Indonesia in Table 2.

5.1.1 Poultry Farm Business Location

Based on the 2014 livestock business household survey data, there are various farmers

from various provinces in Indonesia. In this study, the farmers studied came from 34

provinces in Indonesia with the following proportions listed in Table 3.

Based on Table 3, poultry farming is most prevalent in Java, namely in Central Java

Province, and least prevalent in DKI Jakarta Province. This is because DKI Jakarta is the

center of the capital city, making it less suitable as a place to conduct livestock farming.

Livestock business is generally carried out in rural areas. This is related to the development

potential and resources available in determining the development of livestock businesses,

namely the ecological basis of land, infrastructure, and capital.

In developing a livestock business, of course, it is necessary to pay attention to the

distance to residential areas, the availability of affordable traditional animal feed, the

availability of water that can be sourced from rivers, wells, and the availability of access to

capital by taking into account the benefits of spending on maintenance costs in the village, of

course cheaper than in the city (Siagian 2011; Umiarti 2017; Mahfut and Rusdiyana 2019;

Ploransia et al. 2022). Thus, there is a great opportunity for livestock business development

to be carried out in rural areas with the aim of realizing rural economic growth.

The five provinces with the most poultry farms include Central Java, East Java, West

Java, Lampung, and South Kalimantan. Meanwhile, the five provinces with the least poultry

farming include DKI Jakarta, West Sulawesi, Gorontalo, Bali, and Papua.

5.1.2 Productive females

Productive females are the number of female poultry parents that can lay eggs and

produce young. The types of poultry cultivated in this study include layer chickens, native

chickens, ducks and manila ducks. Generally, female chickens or ducks have different

characteristics. These are described in Table 4.

5.1.3 Poultry feed

Feed is a single or mixed, processed or unprocessed food material given to farm

animals for the process of survival, production, and breeding (UU RI 2014). Feed is an

estimate of poultry feed expenditure that depends on each farm management. There are

differences between each farmer in providing feed, in this study there were eight main types

of feed used by farmers, namely starter layer feed, feed, and feed grower layer feed, layer

feed, broiler starter, broiler finisher, concentrate (pellets etc.), bran or rice bran, and grains

(grain). Differences in feeding or animal feed management (phase feeding) are due to

differences in nutritional needs both from energy and protein requirements for each type of

livestock as the age of poultry increases. Thus, differences in feeding certainly have an

impact on the cost of each livestock, especially the frequency of feeding. The average poultry

feed for RTUP poultry is IDR 9,216,877.

Feed itself is the largest cost component of the production cost of poultry farming.

There are several studies that explain that feed is the largest component of production costs,

one of which is North and Bell (1990) approximately 65% of production costs, Tumion et al.

(2017) explained that layer chicken feed has a percentage of 77% of total production costs,

and several other studies explained that animal feed is the cost with the largest cost

component (Pambudy 2013; Huda 2019; Nisak and Nurhman 2021). Based on survey data,

broiler feed is the largest cost component at 83.58 percent of total production costs, while

broiler feed accounts for 64.69 percent of total production costs (BPS 2015c). In addition, the

uncertainty of feed prices, which continue to rise, can also increase feed, which results in

high production costs. In addition, the lack of easily accessible feed companies means that

farmers need to find out other feeds that can be used as feed for other livestock. Some poultry

farmers claim to use food scraps to feed their birds. Thus the feed used is mostly obtained not

through direct purchase. The following are the ten types of other feed most commonly used

by farmers based on the results of the farm household survey in Table 6.

5.1.4 Disinfectant

Disinfectants are expenses for the purchase or non-purchase of disinfectants.

Disinfectants are chemicals used to inhibit or kill microorganisms such as bacteria, viruses,

and fungi. In this case, disinfectants are used to clean both poultry houses and equipment

related to livestock production activities. However, the selection of disinfectants also needs to

be considered, this is related to the function of disinfectants as chemicals such as halogens,

alcohols, oxidizing agents, phenols, and aldehydes, so it is necessary to pay attention to the

following points including: 1) the history of disease spread, 2) the amount of organic manure,

and 3) the material of the cage (Kusuma 2023). In applying disinfectants, it is necessary to

adjust the material of the cage, if the cage material is made of wood or bamboo, a disinfectant

is needed that can reach the pores of the wood. Another case with cages made of iron or

metal, non-corrosive disinfectants are needed to avoid rust on iron or metal, as well as

vehicles that are always used to market livestock products also need to be sterilized to avoid

germs and diseases. Based on the survey results, the expenditure of livestock business

households for disinfectants is Rp 9,150.

5.1.5 Sanitation

Sanitation or operational costs are the ongoing expenses of conducting the operations of

a business or the ongoing costs of conducting a production activity related to the

implementation of business operations. In this study, operational costs refer to the total costs

for electricity and water expenses. Based on the survey results, the average cost of spending

on electricity and water is IDR 236,382. Sanitation aims to facilitate production activities

such as water for livestock drinking, cage hygiene, and electricity for cage lighting (Riptanti

2008).

5.1.6 Farm animal health

Livestock health is an accumulation of expenses for vaccines, salt, medicines, vitamins,

artificial insemination, and livestock maintenance costs, among others. Based on the results

of the survey of livestock business households, livestock health expenditure amounted to Rp

235,510. Each farmer certainly has different types of vaccines, medicines, and vitamins used

for their livestock. The provision of vaccines, medicines, and vitamins aims to increase the

endurance of livestock which can also affect the risk of livestock mortality, thereby reducing

the risk of production failure (Ramadhan and Burhanuddin 2017). The types of vaccines,

medicines, and vitamins most widely used by poultry farmers in Indonesia are listed in Table

7. Based on the table, it is known that there are ten types of vaccines most widely used by

farmers including ND, ND Lasota, Gumboro, Drops, ND Kill, ND-IB, Bird Flu, Marek,

NCD, and vita chicks. Meanwhile, there are five types of medicines used for diseased

ungasses, namely bodrex, tetra-chlor, dewormer, vita chicks, and trimezyn. Meanwhile,

vitamins that are always used by farmers are dominated by Vita Chicks and turbo. This is in

line with the vaccination program that was conducted simultaneously in 2014 (Livestock

2014). The following is a list of vaccines, medicines and vitamins used by poultry farmers in

Indonesia in table 7.

5.1.7 Age of breeder

Farmer age is a variable that describes the demographic age distribution of poultry

farmers in Indonesia. This variable is used to show whether poultry farmers in Indonesia are

of productive age. This has to do with productive age which can increase labor productivity,

thus affecting business performance. If the labor used is in the productive category. This

allows for higher work productivity compared to labor with a non-productive age (Utomo

2019). In addition, in conducting livestock business activities, both physical (stamina) and

non-physical (knowledge) abilities are needed. Livestock business activities involve a lot of

physical activities, younger farmers generally have better physical abilities when compared to

older farmers so that it affects higher work productivity. In addition, younger farmers

certainly have a high level of curiosity, especially in the adaptation of higher technology that

allows farmers to adopt more efficient and up-to-date farming techniques (Mandaka and

Hutagaol 2015). Farmers' age is also related to decision-making and behavior so that it can

also affect decisions in determining the direction and objectives of their business (Asih 2007;

Muhammamah 2008; Haloho 2010; Auditiya 2011; Samti 2011; Abadi 2014; Wati et al.

2014; Kusumaningtyas 2017; Marantika and Sampurno 2018). The age diversity of poultry

farmers in Indonesia is shown in Table 9, which is dominated by farmers with productive age

of 15-65 years with a proportion of 85.81 percent. The average age of poultry farmers in

Indonesia is 49 years. The age diversity of poultry farmers in Indonesia is shown in Table 9.

5.1.8 Education level

Education level is a demographic variable that describes the diversity of education

levels achieved by poultry farmers in Indonesia. The diversity of education levels is related to

the ability of farmers to adopt farming techniques, technology adoption, business decisions,

business management, technical efficiency of the business, as well as the activeness of

farmers to participate in institutions such as cooperative membership, associations, farmer

groups, extension services, and decisions on additional business capital through credit

(Latruffe et al. 2012; Oladeebo 2013; Suprapti et al. 2014; Mandaka and Hutagaol 2015;

Bethel et al. 2016; Firmansyah et al. 2017; Maemunah and Isyanto 2017). The higher the

level of education achieved by farmers can certainly affect the ability of farmers to manage

their business more efficiently with the aim of increasing the benefits obtained by farmers by

producing at an efficient level. Based on the survey results, the diversity of education levels

pursued by poultry farmers in Indonesia is dominated by farmers with elementary school

graduates with a proportion of 40.38 percent. Meanwhile, the average level of education

attained by farmers in Indonesia is 7.85 years or equivalent to elementary school graduates.

The diversity of education levels of poultry farmers in Indonesia is available in Table 10.

5.1.9 Number of dependents in the family

The number of dependents in the family is a demographic variable used with the aim

of describing the diversity of the number of dependents of farmers in the family. This

variable has a relationship with the number of dependents in the family which is a proxy for

the involvement of labor in the family (TKDK) (Firmansyah et al. 2017). Based on the survey

results, the average number of dependents in the farmer's family is 4 people. The smallest

number of farmer dependents is 1 person and the largest is 13 people. This indicator also has

a relationship with spending on labor costs, with the involvement of labor in the family, of

course, it can reduce spending on labor and support the success of the business being carried

out, especially if the business income obtained by the farmer (Arinta 2014; Firmansyah et al.

2017). However, there are studies that assume the higher number of dependents in the family

can increase family expenses that must be met so that it affects the decrease in cost allocation

for business capital or has a negative effect on business success (Arinda 2015; Elrangga

2016; Budi and Wirajaya 2018; Marantika and Sampurno 2018). This also results in low

credit repayment rates (Asih 2007; Samti 2011; Wati et al. 2014; Rosiana et al. 2015;

Kusumaningtyas 2017). However, this can also be influenced by outside variables such as

business experience or lifestyle factors. That way, the success of the business is also closely

related to the ability of farmers to manage their business and the ability to allocate capital for

business. Some other studies mention that the number of dependents in the family has a

positive influence on technical inefficiency. This is related to the greater the family size, the

smaller the technical efficiency that can be achieved (Maemunah and Isyanto 2017).

5.1.10 Farmer activeness

Farmer activeness is a variable that describes the institutional aspect of farmers. This

is because farmer activeness in this study is estimated using the accumulation of farmer

participation in cooperative membership, farmer group membership, farmer associations, and

extension. The four aspects are used with the aim of describing the livestock farmers'

activeness with an economic approach to livestock institutions. Strengthening farmer

institutions plays an important role in increasing the productivity and competitiveness of

livestock businesses (BPS 2015a). Strengthening the institutional aspects of farmers such as

farmer groups, cooperatives, associations and extension services can certainly support

livestock businesses in developing their businesses with collective activities that can support

business success such as strengthening business capital, partnership cooperation, procurement

of production facilities, knowledge about livestock cultivation, increasing business

production, handling livestock diseases, and facilitating marketing of livestock products

(Baga 2009; Mochtar 2016). The diversity of institutions followed by poultry farmers in

Indonesia is listed in Table 11.

Institutional aspects themselves have a variety of different benefits and roles. This

institutional aspect is an internal factor of the farmer as an effort he makes in an effort to

achieve his business goals. In managing their livestock business, farmers do not only rely on

their knowledge and skills, but also their skills in managing their business. This can be

learned through farmer groups, farmer associations, farmer cooperatives, or counseling. With

this participation, farmers can learn from other farmers who have higher experience, through

the exchange of information, experience in handling livestock diseases, the use of animal feed

technology, vaccines, medicines, and vitamins that can prevent livestock from getting

diseases, and market networks that can be built among farmers (BPS 2015a; Mochtar 2016).

However, there are several reasons why farmers do not become members of cooperatives,

farmer groups, and do not attend extension services. Therefore, improvements and efforts are

needed to increase farmers' participation in institutions to support their business success.

Based on the survey results, some of the main reasons for farmers are listed in Table 12.

Based on the survey results, it can be concluded that the lack of cooperatives and

farmer groups in the village, as well as the uneven distribution of extension services are still

the main causes of the lack of participation of farmers in institutions. Thus the need for

support for livestock businesses from both the government and the local livestock office

(Yulia 2022). In addition, the government and the Livestock Service Office can be a liaison

medium between livestock businesses and banking and non-banking microfinance institutions

to increase business capital. Based on the survey results, it is known that the level of

participation of breeders' associations is the least followed institution by breeders (Table 11).

However, based on the survey results, farmers who participated in the association claimed to

get several benefits after joining the breeders' association. Some of the main benefits of

joining the association are listed in Table 13.

Meanwhile, there were several other reasons why farmers did not attend extension

services such as: 1) ignorance of available extension information (65.52%), 2) There is no

time (6.38%), 3) Busy (4,40%), 4) Uninvited (3.12%), 5) Not selected (2.84%), 6) Not

member (1.84%), 7) No time (1.84%), and 8) other reasons (13.05%). In addition, based on

the survey results, farmers admitted that some of the counseling conducted was not in

accordance with the needs of farmers (Table 12). Therefore, it is necessary to collect

information about the counseling needed by farmers so that the counseling conducted is in

accordance with what is needed by the farmers themselves. Some of the counseling needed

by farmers are listed in Table 14.

Some types of counseling needed by farmers are livestock cultivation techniques,

livestock treatment, preparation of livestock rations, marketing of production products, and

processing of production products. Some Agricultural extension itself is a technical extension

program that requires field instructors who have competence in the field of animal husbandry

so that farmers can learn directly from the experts. Agricultural extension officers themselves

need to be competent and not only focus on the implementation of routine tasks such as

increasing production, but also on qualitative aspects such as how well farmers understand

the techniques that have just been delivered or direct application. Extension workers also

need to be an intermediary between the government and farmers by conveying constraints in

the field such as analyzing opportunities or factors that are strategic or threats that will be

faced. The role of extension workers is certainly very important for farmers, breeders and

fishermen in an effort to improve the performance of the agricultural sector including

improving the welfare of farmers (Descartes et al. 2021). In addition, extension workers can

also act as facilitators who connect farmers, breeders, or fishermen with external parties such

as the local government, the private sector, banking and non-banking financial institutions

related to the need for business capital in the form of credit, agricultural insurance, certified

seeds, animal feed, medicines, vitamins, livestock vaccines, and other needs that can support

agricultural activities. Finally, accessibility to extension services also needs to be a concern,

this is because one of the reasons farmers are reluctant to attend extension services is because

the location of extension services is far away (Table 12). This is in line with the research of

Achmad et al. (2012) that many farmers can only access counseling 0-3 times from the

minimum 6 times required, so that improvements to the extension system itself need to be

further improved and complete facilities and infrastructure in providing counseling can

certainly support extension activities carried out. Improving materials, providing information

on the latest input and output prices, as well as knowledge on product processing and post-

harvesting are also important. The processing of products can certainly increase the price of

output so that farmers can also increase the benefits they receive. This also supports the

concept of agribusiness by not only selling primary products, but also secondary products.

5.1.11 Livestock mortality rate

Livestock mortality rate is an indicator used to estimate the production risk of

livestock businesses. The mortality rate is calculated using the ratio of animals that die from

certain diseases or natural deaths compared to the total number of livestock owned. Poultry

farming has always been haunted by livestock diseases, which is often a limiting factor in

obtaining business capital from investors. The high mortality rate of livestock certainly

indicates the high risk of losses that will be experienced due to the high mortality rate of

poultry, causing a decrease in income obtained from production (Balitbangtan Kemendag

2014). Based on the survey results, several types of poultry diseases that often trouble

farmers in Indonesia are listed in Table 15. Based on Table 15, the most common diseases

experienced by poultry are avian influenza, tetelo (chicken plague), and cold or snot. Several

other types of poultry diseases are paralysis, sudden death, and pestilence (tetelo).

Avian influenza is still a major disease in poultry, this is because avian influenza itself

has a very high transmission rate (Wahyuni et al. 2022). Some coping strategies that can be

done to avoid higher losses in livestock business can be done by: 1) building a network of

livestock disease control, 2) strengthening veterinarians and paraveterinarians in all lines of

work, 3) strengthening laboratory facilities and supporting facilities as well as providing

technical training for handling livestock diseases, 4) finally making biosecurity SOPs to

prevent outbreaks of infectious livestock diseases, both with fellow livestock and humans, 5)

building a national animal or poultry quarantine network to avoid the entry of livestock

diseases from abroad, 6) building a socialization system to prevent infectious livestock

diseases in the community at large (Abidin 2011; Balitbangtan Kemendag 2014; Hewajuli et

al. 2014).

In addition, some strategies that can be used as risk mitigation efforts include

vaccinating livestock, Several vaccines have been proven to increase protective immunity in

livestock, namely ND vaccine, ND-AI combination vaccine, and spirulina administration

(Lokapirnasari and Yulianto 2014; Ayu et al. 2015; Made et al. 2016). In addition, farms also

need to conduct preventive activities such as making poultry houses with clean sanitation and

vaccinating poultry (Frisa et al. 2017). The risk of livestock disease spread also needs to be

mapped through three risk categories such as negligible risk, low risk, and medium risk

(Wahyuni et al. 2022). This is needed as an effort to prevent more dangerous impacts on

areas with low and medium risk categories, as well as to increase higher security in risky areas

compared to safe areas. Other control efforts such as routine vaccination, routine socialization

or counseling and monitoring can certainly prevent the transmission of livestock diseases

optimally. Based on the survey, it is known that there are still few farmers who treat livestock

directly to veterinarians or orderlies, most of them are still treated independently. Some of the

main livestock treatments and other treatments conducted by farmers in Indonesia are listed

in Table 16.

5.1.12 Credit

Credit is additional capital obtained by farmers from external parties either through

formal or informal institutions. Credit is a variable that estimates additional capital for

livestock businesses to increase the use of production inputs so that it can also increase the

production of livestock products when compared to before the use of credit (Putri et al. 2021).

However, there are also studies that prove that the impact of credit on the income received by

farmers is not significant, this is because some farmers experience problems such as disease

in livestock and livestock death (Dahri et al. 2015).

Based on the survey results, it is known that most of the additional sources of capital

for farmers are obtained through their own capital, followed by additional capital from

companies and village credit institutions (LPD). The next interesting thing is that other

sources of additional capital come from relatives (relatives or family). This is in line with the

research of Chandio et al. (2017) and Pratiwi et al. (2019) which explains that farmers tend to

prefer additional sources of capital through informal financial institutions as a source of

credit financing. This is because most farmers do not have sufficient collateral to be used as a

requirement that must be met as in formal financial institutions, where collateral is still the

biggest influence on access to credit compared to other factors. This causes farmers to choose

to access credit through informal financial institutions because they are more flexible in terms

of collateral rules, although formal financial institutions have clearer transparency in the

lending process including interest rates that have been set from the start, but the collateral

requirements are still quite difficult, causing farmers to be reluctant to access formal credit.

Based on the survey results, there are several sources of additional capital that farmers

obtained through the list listed in Table 17.

In an effort to increase the use of production inputs through additional business capital

through credit, of course, it has its own challenges for efforts to repay the credit obtained.

However, there are two main ways that are often done by farmers in returning the credit used,

namely by repaying the credit after production or selling the production results to the lender

or capital. These two main ways are often done by farmers to return the credit they receive.

Of course, the point of selling production to the capital provider can be a positive influence,

namely the certainty of purchase, but this can also have a negative effect if the farmer is

actually forced to give up his livestock assets to cover the credit he uses. This means that

farmers will lose some of their livestock due to credit payments followed by interest that also

needs to be paid. The main ways of repaying credit are listed in Table 18.

There are several reasons why farmers are reluctant to get credit or additional capital.

The three main reasons are lack of interest, no credit provider, and inability to pay interest.

Reasons one and two are closely related to the provision of credit information and the

successful socialization of credit utilization, in contrast to the third reason, the inability to pay

the interest charged is influenced by a variety of factors both internal to the farmer and

market uncertainty that causes the price of production and interest set high enough so that

farmers experience problems of inability to repay credit (bad credit). Some other reasons

include ignorance of information about credit, using their own capital, and farmers feel they

do not need to use credit. Some of these are listed in Table 19 below.

5.1.13 Partnership

Partnership is a form of cooperation that mutually supports and benefits both parties

as outlined in the form of an agreement with the aim of achieving mutually agreed matters.

Partnership is a strategy that can be used to increase economic growth both regionally and

nationally, employment, income distribution and encourage community welfare. Several

studies have shown that partnerships are also closely related to the addition of business

capital such as credit, which is proven to be able to increase the sales turnover of a business,

increase labor and increase joint profits (Ardiyanto and Setiawan 2013). One of the

advantages of partnering is of course accessibility to capital sources, this has been proven to

significantly help business partners (Ardiyanto and Setiawan 2013; Wibowo 2013; Widyani

2013; Santoso et al. 2015; Fitria and Jurana 2016; Asiati and Nawawi 2017; Maemunah and

Isyanto 2017; Saputra et al. 2017; Diana 2019). Based on the survey results, it is known that

most farmers who have partners choose to partner with private parties (companies), the rest

choose to partner with BUMD and BUMN listed in table 20.

5.1.14 Number of Livestock

The number of livestock is a variable that aims to describe the scale of the livestock

business. This is related to the higher number of livestock owned, the higher business capital

required with the aim of increasing production and sales turnover (Mayangsari et al. 2014;

Waqid 2014; Dahri et al. 2015; Utomo 2019). The average number of poultry owned by

farmers is 62 birds. Some of the objectives of poultry farming based on the results of this

survey are livestock breeding, egg production and livestock fattening listed in Table 21.

5.2. Characteristics of Dairy Farmers in Indonesia

Dairy farming is a subsector of animal husbandry that needs to be the focus of business

development. This is because the availability of family labor, feed, and the rate of demand for

dairy products continues to increase along with improvements in the nutrition of the

Indonesian people. Therefore, support for improved dairy farm management, technology

adoption, infrastructure and government policies are needed to support business development.

The characteristics of dairy farmers used in this study are the results of a description of

farmers who run dairy farms in Indonesia. The characteristics of dairy farms used as variables

and samples in this study are statistically described in Table 1.

22. The total number of dairy farm households used in the production function model and

variance function (risk function) in this study is 597 farm households. In the production

function model of dairy cattle farming, five variables are used that are thought to affect the

value of production. The variables used are dairy cattle feed, sanitation, animal health,

farming experience, and number of livestock. Meanwhile, to estimate the production risk

function model, eleven variables are used that are thought to affect the risk of sales turnover.

The variables used in the production risk function model consist of variables used in the

production function model with additional risk variables, namely farmer age, education level,

number of dependents, farmer activeness, credit, and partnership. The following is the

descriptive statistics of the sample of dairy farming households in Indonesia in Table 22.

5.2.1 Dairy farm business location

The location of dairy farms in Indonesia consists of several provinces. Most dairy

farmers are located in Java with a proportion of 97.83 percent of the total dairy farms. This is

related to one of the government programs regarding the sustainable milk production program

in line with the Indonesian Dairy Blue Print 2013-2025, namely with the target of meeting

national milk needs from within the country by 60 percent (DG PKH 2021b). The program

aims to increase dairy cow productivity by 20 liters per day by increasing the dairy cow

population through the Sikomandan and Upsus Siwab programs. This program is supported

by the introduction of dairy cows (heifers) or rearing rearing paddocks and providing

investment incentives in the form of tax allowances. The government also carries out genetic

improvement with the aim of increasing milk productivity, the government realizes this

through assistance in the application of Good Farming Practices (GFP), Good Handling

Practices (GHP), Good Manufacturing Practices (GMP) and improving the quality and

quantity of animal feed carried out through a partnership between Indonesia-Denmark as the

largest organic milk producer in Indonesia. The improvement of milk production that

emphasizes local livestock businesses aims to develop dairy farming based on a fully

integrated agribusiness subsystem from upstream to downstream, so that it not only produces

fresh milk products but also processed milk products, organic fertilizer from livestock waste,

and increases added value and product competitiveness through diversification of dairy

products that can reduce stunting in Indonesia.

One of the efforts to develop the dairy farming business is realized through

empowering dairy farmers in areas that have high potential in dairy cattle business

development. Java is an area with high potential for dairy farming development (Siregar and

Kusnadi 2004; Riptanti 2008; Rahayu 2013; Pamungkasih and Febrianto 2021). This is

because the dairy cattle population is still concentrated in provinces in Java, around 97

percent, in line with the observations of this study (Pamungkasih and Febrianto 2021).

The development of dairy cattle farming generally requires consideration of business

locations in highland areas because they have optimal temperature and humidity suitability

for dairy cattle farming. Consideration of altitude and temperature has been shown to affect

the feeding patterns of dairy cows so that it has the potential to affect the productivity of

dairy cows. Some of the locations that have the most dairy cattle farming are East Java

(Malang), West Java (Lembang and Cirebon), and Central Java (Boyolali and Klaten).

Several studies have shown that dairy cows can also be cultivated in lowland areas (Siregar

and Kusnadi 2004; Riptanti 2008; Rahayu 2013; Pamungkasih and Febrianto 2021). Several

studies have also shown the link between dairy farming and the role of village unit

cooperatives (KUD) as well as the involvement of additional business capital in the form of

credit from formal financial institutions such as banks and government business development

programs. The locations of dairy farms based on the survey results are listed in Table 23.

5.2.2 Dairy cow feed

Feed is a single or mixed, processed or unprocessed food material given to livestock for

the process of survival, production, and breeding (UU RI 2014). Dairy cattle feed has several

main feed components including the use of forage feed (grass), factory-made feed (pellets),

household waste, agricultural waste (straw), and factory waste (tofu pulp, palm kernel cake,

bran or rice bran) and other types of feed. Feed is one of the factors that play an important

role in the management of dairy farming (Santosa et al. 2013; BPS 2015°; Putri et al. 2019;

Matialo et al. 2020). Dairy cattle feed does not only come from purchased feed, but also feed

that is cultivated by farmers from leftovers, searching, or planting themselves, so that even

though the feed provided does not come from purchases, farmers can still support their cattle

(Riptanti 2008). Based on the survey results, the average feed for dairy cattle is Rp

34,508,560. Meanwhile, other types of feed that are often used by farmers are cassava, banana

stems, and coconut as a substitute for the main feed. Some other types of dairy cattle feed are

listed in Table 24.

5.2.3 Sanitation

Sanitation or operational costs are the ongoing expenses of conducting the operations of

a business or the ongoing costs of conducting a production activity related to the

implementation of business operations. In this study, operational costs refer to the total costs

for electricity and water expenses. Based on the survey results, the average expenditure for

electricity and water for dairy farms is Rp 1,780,787. The sanitation aims to facilitate

production activities such as water for cattle drinking, cage hygiene, and electricity for cage

lighting. This is because the need for water for dairy cows is relatively stable, so to prevent

constraints on water needs during the dry season, farmers usually provide a large enough

volume of water reservoirs as a form of mitigation of the risk of prolonged drought, besides

cage cleanliness or cage hygiene can also affect the levels of germs or bacteria contained in

milk milked (Riptanti 2008).

5.2.4 Farm animal health

Livestock health is an accumulation of expenses for vaccines, salt, medicines, vitamins,

artificial insemination, and livestock maintenance costs, among others. Based on the results

of the survey of dairy farm households, the average expenditure on livestock health is Rp

1,142,822. Each farmer has different types of vaccines, medicines, and vitamins used for their

animals. The provision of vaccines, medicines, and vitamins aims to increase the endurance

of livestock which can also affect the risk of livestock mortality, thereby reducing the risk of

production failure (Ramadhan and Burhanuddin 2017). In addition, disease control through

cleaning the udders of dairy cows, cutting hooves, vaccinating, and cleaning cages using

disinfectants are carried out as a form of risk mitigation to avoid hoof and mouth disease

(FMD), anthrax, tuberculose and miscarriage of the womb which are contagious, as well as

diseases such as unwillingness to eat, diarrhea, and bloating (Riptanti 2008; Balitbangtan

Kemendag 2014; Nuhung 2015).

Foot and mouth disease (FMD) is a serious problem in cattle farming, hence the need

for serious treatment. This disease can affect ruminant animals such as cattle, buffalo, goats,

sheep, deer, pigs, camels, and some wild animals where the disease can be transmitted to

even or split hoofed animals. The government has chosen to export live cattle from Australia

that are free from foot and mouth disease (FMD) to increase the added value of cattle farming

in Indonesia. This cattle trade activity is only carried out in FMD-free countries based on the

recommendations of the OIE (Office International des Epizootics) in Paris. Indonesia is one

of the countries free from FMD based on the OIE decision, but the disease began to reappear

in Gresik, East Java on April 28, 2022. This disease has caused the Ministry of Agriculture to

issue several policies including the establishment of FMD handling officers and structuring

animal traffic in disease outbreak areas. This was done to minimize the impact of FMD

outbreaks such as public panic in consuming meat or milk which can cause a decrease in

demand for meat and milk which can cause losses to livestock businesses in Indonesia

(Susanto 2022). Therefore, the allocation of livestock health costs for vaccines, medicines,

and vitamins can be useful as an effort to prevent (risk mitigation) infectious diseases. The

types of vaccines, medicines and vitamins most widely used by dairy farmers in Indonesia are

listed in Table 25.

Livestock health costs are an important variable because they are related to livestock

mortality rates. Livestock mortality rate is an indicator used to estimate the production risk of

livestock businesses. The mortality rate is calculated using the ratio of livestock that die from

certain diseases or natural deaths compared to the total number of livestock owned. Dairy

farming has always been haunted by livestock diseases, especially hoof and mouth disease

(FMD), which is often a limiting factor in obtaining business capital from investors (Riptanti

2008; Balitbangtan Kemendag 2014; Nuhung 2015). The high mortality rate of livestock

certainly indicates the high risk of losses that will be experienced, causing a decrease in

income obtained from production (Balitbangtan Kemendag 2014; Susanto 2022). Based on

the survey results, the three main diseases of dairy cattle in Indonesia are abdominal

distension, worms, and anthrax as shown in Table 26.

In optimizing the increase in farmers' income, dairy farming businesses can implement

Good Dairy Farming Practices (GDFP) which aims to produce quality and standardized

milk, so as to increase consumer confidence in healthy dairy products and management

carried out based on sustainable business provisions by considering aspects of animal

welfare, social, econony, and the environment. The main aspects that become the main focus

of GDFP are livestock reproduction, livestock health, environment and socio-economic

management (Lestari et al. 2015). In addition to livestock reproduction, GDFP also

prioritizes animal health through vaccination efforts as an effort to prevent livestock diseases.

However, the results of the 2013 agricultural census (ST2013) show that most dairy farming

households have never vaccinated their animals. Only 12 percent of all dairy farming

households routinely vaccinated their dairy cattle (BPS 2015a). This indicates a lack of

implementation of GDFP aspects in dairy farming in Indonesia. Vaccination of dairy cattle is

a form of prevention (risk mitigation). Although only 22.3 percent of dairy cattle have ever

been sick, the provision of vaccines can certainly reduce the disease rate of dairy cattle to a

minimum.

Based on Table 26, the most common diseases experienced by dairy cattle are bloat,

worms, and anthrax (Riptanti 2008; Balitbangtan Kemendag 2014; Nuhung 2015). In

addition, Foot and Mouth Disease (FMD) is a serious problem in cattle farming. This disease

can affect ruminants such as cattle, buffalo, goats, sheep, deer, pigs, camels, and some wild

animals where the disease can be transmitted to even or split hoofed animals. The

government has chosen to export live cattle from Australia that are free from foot and mouth

disease (FMD) to increase the added value of cattle farming in Indonesia. This cattle trade

activity is only carried out in FMD-free countries based on the recommendations of the OIE

(Office International des Epizootics) in Paris. Indonesia is one of the countries free from

FMD based on the OIE decision, but the disease began to reappear in Gresik, East Java on

April 28, 2022. This disease then caused the Ministry of Agriculture to issue several policies

including the formation of FMD handling officers and structuring animal traffic in disease

outbreak areas. This was done to minimize the impact of FMD outbreaks such as public panic

in consuming meat or milk which can cause a decrease in demand for meat and milk which

can cause losses to livestock businesses in Indonesia (Susanto 2022). Therefore, the

allocation of livestock health costs for vaccines, medicines, and vitamins can be useful as an

effort to prevent (risk mitigation) infectious diseases.

Some coping strategies that can be done to avoid higher livestock business losses can

be done by:

1) build a network of livestock disease control, 2) strengthen veterinarians and

paraveterinarians in all lines of work, 3) strengthen laboratory facilities and supporting

facilities and provide technical training for handling livestock diseases, 4) finally make

biosecurity SOPs to prevent infectious livestock disease outbreaks, both with fellow livestock

and humans, 5) build a national animal or poultry quarantine network to avoid the entry of

livestock diseases from abroad, 6) build a socialization system for preventing infectious

livestock diseases to the public at large (Abidin 2011; Balitbangtan Kemendag 2014;

Hewajuli et al. 2014).

In addition, some strategies that can be used as risk mitigation efforts include

vaccination of livestock, several vaccines that have been proven to increase the protective

immunity of dairy cows, namely the anthrax vaccine, Septicaemia Epizootica, and septivet

(BPS 2015b; BPS 2017). In addition, the cleanliness of cages and udders of dairy cows can

also affect the level of germs or bacteria contained in milk (Riptanti 2008). Other control

efforts, such as routine vaccination, socialization orRoutine counseling and monitoring can

certainly prevent the transmission of livestock diseases optimally. Based on the survey, it is

known that there are still minimal farmers who treat livestock directly to veterinarians or

orderlies, most of them are still treated independently. Some of the main livestock treatments

and other treatments conducted by farmers in Indonesia are listed in Table 27.

6.1 Conclusion:

Based on the results of research on the risk management of Indonesian farmers facing

production risks, it is concluded that:

1. Factors that reduce the value of production in poultry farming are the number of

livestock. Meanwhile, factors that increase production value in poultry farming include

variables of poultry feed, sanitation, animal health, farming experience. The disinfectant

variable is not statistically significant.

2. Production factors of poultry farming that are included in risk inducing factors include

poultry feed, education level, number of dependents, number of livestock, credit, and

mortality rate. Some production factors that are included in risk reducing factors include

sanitation, animal health, and farming experience. The variables, disinfectant, farmer

age, farmer activeness, and partnership were not statistically significant.

3. Factors that reduce the value of production in dairy farming are dairy cattle feed.

Meanwhile, factors that increase the value of production include sanitation, animal

health, farming experience, and the number of livestock.

4. Dairy farm production factors included in risk inducing factors include sanitation,

farming experience, education level, number of livestock. Meanwhile, production factors

that are included in risk reducing factors include dairy cattle feed. The variables of

livestock health costs, farmer age, number of dependents, credit, farmer activeness, and

partnership are not statistically significant.

5. Preventive strategies carried out by livestock farming households are by improving feed,

sanitation, disinfecting, vaccinating livestock, providing vitamins, partnerships and

increasing the livestock farmers' activeness. Risk mitigation strategies are carried out by

improving the health of livestock (medicines, and treatment of sick livestock to

veterinarians or by the farmers themselves). While coping strategies can be done by

using credit. In this study, credit still cannot be categorized into coping strategies,

because farmers who use credit are done before the risk occurs to reduce the impact of

risk.

WPC 480_ASU_ASSIGNMENT 2024_PRODUCTION RISK MANAGEMENT OF INDONESIAN BREEDERS

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