AGB 100_ASU_ASSIGNMENT 2024_MILK AVAILABILITY MODEL TO SUPPORT THE DEVELOPMENT OF DAIRY CATTLE AGRIBUSINESS SYSTEM

MILK AVAILABILITY MODEL TO SUPPORT THE DEVELOPMENT

OF DAIRY CATTLE AGRIBUSINESS SYSTEM

INTRODUCTION

The development of the livestock subsector contributes strategically to the

fulfillment of food needs along with the increase in demand due to the increase in

population and increase in income. In line with that, the livestock subsector is expected to

become a new source of growth for the Indonesian economy. Dairy agribusiness is one

component of the livestock subsector that has the potential to be developed because there

is still a gap between domestic milk production and national milk demand. Currently,

around 80% of national milk demand still depends on imports, mainly from New Zealand,

Australia, the United States and Europe. Data from BPS (2019) and Pusdatin (2019) show

that the total demand for milk (fresh milk equivalent) in 2018 was 4,716,680 tons, which

could only be met from domestic fresh milk production of 990,370 tons. In addition, the

rate of fresh milk production, which grew by 3% per year, has also not been able to keep

up with the rate of milk consumption, which grew by around 5% per year (Pusdatin 2019).

In two decades in the period 1996 - 2018, the realization of dairy imports was far above the

amount of export realization, resulting in a trade balance deficit (Pusdatin 2019). BPS data

(2019) shows that the volume of dairy imports in 2018 was recorded at 256,657 tons

(578,073 thousand USD) much higher than the volume of dairy exports of 23,153 tons

(39,336 thousand USD). The milk imports were mostly in the form of skim milk powder,

anhydrous milk fat, and butter milk. For the needs of the food industry, milk powder,

cheese and butter are imported.

The Indonesian government during the New Order era issued an import quota

policy through the implementation of an import ratio or Proof of Absorption (BUSEP) of

domestic fresh milk through INPRES Number 2 of 1985 concerning Coordination of

National Dairy Development. This policy intervention was pursued with the aim that the

Milk Processing Industry (IPS) must absorb domestic fresh milk production as a

requirement in determining the amount of imports. The import ratio applied is one part for

domestic fresh milk and two parts for the amount of imports. According to Taufik (2019),

d o m e s t i c fresh milk production during the implementation of the proof of absorption

policy of the new order period, had reached 40% of the national milk demand.

However, after Indonesia faced a monetary crisis, in 1998 the Indonesian

government and the IMF signed an agreement related to milk trading, so that the BUSEP

policy was finally abolished. After that, the import regulation intervention policy was

implemented by the 5% import tariff policy imposed by the Government of Indonesia. This

is in line with what Priyanti et al. (2004), that based on the Decree of the Minister of

Finance No. 16/KMK/01/1998 on the Reduction of Import Duty Tariffs on Certain

Agricultural Products, the import tariff on dairy raw materials and finished products, which

initially varied from 5-30%, was now changed to 5%, and did not distinguish between raw

materials and finished products.

Following up on the condition of dairy development in Indonesia, the

Government through the Coordinating Ministry for Economic Affairs has issued the

Indonesian Dairy Blueprint 2013 - 2025. The blueprint, which was launched in 2014

and reviewed in 2016, targets that by 2025 60% of national milk demand can be met

from domestic mi l k production. The implementation of the action plan of the dairy

blueprint is the issuance of regulations to encourage domestic fresh milk market

absorption and regulation of the Milk Drinking Movement (GERIMIS) program and

the Milk Drinking Movement for School-Age Children (GERIMIS BAGUS)

program. This was implemented by the Ministry of Agriculture with the issuance of

MOA No. 26/2017 on the Supply and Distribution of Milk after a long period of

absence of regulations after the revocation of Presidential Instruction No. 2/1985.

One year later, due to pressure to respond to World Trade Organization

(WTO) policy regulations, this MOA was revised into MOA No. 33 of 2018

concerning the Second Amendment to MOA No. 26 of 2017, one of the points of

which eliminated the obligation of IPS and Importer business partnerships with milk

cooperatives or dairy farmer groups. In line with the dairy blueprint issued by the

Coordinating Ministry for Economic Affairs and regulations issued by the Ministry

of Agriculture, the Ministry of Industry has previously developed a roadmap for the

d a i r y industry for the period 2010 - 2025. The long-term goals in 2010-2025

targeted several achievements to accelerate national milk supply, namely the target

of increasing the supply of domestically produced milk to 50% to 60% of national

demand, increasing milk productivity to 20 liters/head/day, and increasing the dairy

cow population to 1.587 million heads by 2025. These government targets have high

urgency in supporting Indonesia's vision as the world's food barn in 2045.

In connection with efforts to achieve the target of 60% share of domestic

milk production from the total national milk demand, Indonesia faces opportunities

and challenges in accelerating the availability of milk from upstream to downstream.

Improvement and development of the agribusiness system from upstream to

downstream is an integral part of efforts to achieve these targets. One of the

agribusiness subsystems that needs to be elaborated is the upstream and on-farm

subsystem, represented by the dominance of dairy farmers who are cultivated mostly

by smallholder farms involving 141,989 dairy cattle farming households (BPS 2014).

The growth of national milk production will depend on the growth of the national

dairy cattle population and productivity. The national dairy cattle population for the

period 1980 - 2019 experienced growth of 3.01% per year, fresh milk production

growth of 4.34% per year (Figure 1.1) and productivity grew by 1.71% per year. On

the one hand, the average national milk consumption is 16.27 liters per capita per

year (including processed products containing milk) (BPS 2021). Although, this

value is still lower than ASEAN countries such as Malaysia at 36.2 liters per capita

per year and Thailand at 22.2 liters per capita per year, but along with the increase in

population, increase in income, and public awareness to consume milk needs to be

balanced with an increase in

domestic

milk production. This national

demand is predicted to continue increasing and is an opportunity that the dairy

market in Indonesia is still very promising.

More than 90% of the milk production is produced by smallholder dairy farmers

with an average ownership scale of 3-4 lactating mothers per household (Priyono 2010;

Martindah and Saptati 2008). The main actors of the dairy cattle agribusiness system that

strongly influence dairy farmers in the on-farm subsystem are cooperatives and the Milk

Processing Industry (IPS). Most farmers are members of cooperatives. The cooperative is

an intermediary between farmers as milk producers and the IPS where the cooperative

plays a role in the milk distribution process from farmers to the IPS. Most dairy farmers

sell milk to dairy cooperatives, then the cooperatives resell the milk to IPS. This is in

accordance with Priyono and Priyanti (2015) that the dairy industry system in Indonesia is

mostly a collaboration involving farmers, cooperatives and IPS where in this system, fresh

milk is sold to the IPS Vertically distributed from farmers to cooperatives, then directly

distributed to IPS.

Milk cooperatives in Indonesia are members of the Indonesian Milk

Cooperative Association (GKSI). According to Tiesnamurti et al. (2017), the number

of cooperatives under the national GKSI coordination amounts to 98 units. This

number consists of 22 dairy cooperative units in West Java (GKSI Jabar), 24 dairy

cooperative units in Central Java (GKSI Central Java and Yogyakarta), and 52 dairy

cooperative units in East Java (GKSI East Java). The national GKSI milk production

capacity is: (1) GKSI West Java has 16,018 members with a dairy cow population of

57,661 heads capable of producing fresh milk production as much as 410,556 kg per

day; (2) GKSI Central Java and Yogyakarta has 20,784 members and 53,841 dairy

cows capable of producing 131,118 kg per day; and (3) GKSI East Java with 49,420

members and a dairy cow population of 142,775 cows capable of producing milk

production 810,284 kg per day (Setiadi 2017). Business actors in Indonesia (IPS)

currently amount to 60 units. IPS in carrying out its business operations, only about

23% is met from domestic fresh milk production (Riwu 2017).

Thus, the gap between milk production and milk demand in the country is both an

opportunity and a challenge, so it is necessary to improve and develop the dairy

cattle agribusiness system in Indonesia. Dairy cattle agribusiness is a system

consisting of several subsystems in which there are interrelated business processes

from upstream to downstream. The development of dairy cattle agribusiness needs to

be aligned with the government's targets and objectives in an effort to accelerate milk

supply in Indonesia.

1.1 Problem Formulation

The development of the dairy cattle agribusiness system is faced with the

target of achieving national milk production of 60% of national needs (Coordinating

Ministry for Economic Affairs 2013; Ministry of Industry 2009) which is directed to

be able to support Indonesia's vision as the world's food barn in 2045. Current

conditions show that the rate of cow's milk production of 3% per year cannot keep

up with the rate of cow's milk consumption which grows at around 5% per year

(Pusdatin 2019). Indonesia's per capita milk consumption shows an increase along

with the increase in population, increase in income and public awareness of the

importance of consuming animal protein from milk, as well as an increase in the

dairy-based food processing sector. Various food industries, cafes, restaurants and

processed foods are now using fresh milk ingredients. This is both a market

opportunity and a challenge for milk supply in Indonesia.

Various problems are still faced in the upstream and on-farm subsystems,

namely the low percentage of lactating cows to the total population of dairy cows in

Indonesia. In addition, the relatively low milk productivity is also a factor in the low

percentage of national milk production. This is consistent with Tiesnamurti et al.

(2017) that the productivity of national dairy cows has stagnated, only ranging from

8-12 liters per head per day with a maintenance scale of 2-3 mothers per household.

Business actors in Indonesia in developing dairy cattle breeding in the upstream

subsystem also still need to develop their dairy cattle breeding skills optimized again,

most of the seedling development is aimed at replacement stock (Firman et al. 2010).

Quality improvement and genetic improvement of dairy cattle seedlings that are

more adaptive still need to be optimized and aligned with the introduction of

applicable technology at the farm level so as to obtain optimal seedling productivity

(Anggraeni and Iskandar 2008; Anggraeni 2012). In addition, feed costs as the

highest contributor to production costs are faced with fluctuating feed prices that

tend to rise, and milk prices that tend to stagnate. According to Hertanto (2014), low

farmer margins and high feed costs in dairy cattle production operations have an

impact on the quantity and quality of milk produced. The increasingly limited forage

land for dairy cows, especially in Java, is also an obstacle that needs to be addressed

in the upstream subsystem (Farid and Sukesi 2011).

Smallholder farms that have not been able to implement good dairy farming practices on a

massive scale are also an obstacle in the development of the dairy cattle agribusiness

system. According to FAO and IDF (2011) the implementation of good dairy farming

practices includes several components consisting of animal health management, milking

process hygiene, adequate feed nutrition and water availability, animal welfare,

environmental management, and socio-economic management. Until now, farmers in the

on-farm subsystem have experienced difficulties in adopting technological developments,

business concepts, and the creation of added value in providing dairy products in a

sustainable manner. The scale of dairy cattle businesses, which are mostly small-scale with

<5 lactating mothers (Tiesnamurti et al. 2017) and also with a smaller average level of

technical efficiency compared to those with a business scale of >5 lactating cows (Asmara

et al. 2016), are also factors that need to be considered in the on-farm subsystem.

In addition, in the milk supply chain network, dairy farmers in the on-farm

subsystem have a lower bargaining position in the face of IPS and cooperatives. The lack

of movement of dairy farmers in creating added value in the provision of dairy products,

the production process, and the distribution of dairy products causes dairy farmers to still

occupy a lower bargaining position. In the creation of added value by farmers, Arjakusuma

et al. (2013) reported that inhibiting factors include limited adoption of technology, feed

quality, not fully occupied cages, difficulty in accessing sanitation, congested

transportation routes, and low quality of supporting materials from within the country.

Ramadanti et al. (2017) found several critical issues in the milk value chain at KPBS

Pangalengan, West Java, namely declining milk production at the farmer level, lack of a

strong tracing system on the downstream side, the dominance of IPS along the chain and

the modern market revolution.

Another problem that is still faced is the price of female dairy cattle seeds

(lactation) which is not balanced with the ability of smallholder farmers to increase the

scale of business. Although currently access to capital for dairy farming can be relatively

done by farmer groups or cooperatives (Asih et al. 2013), farmers have the risk of

difficulties in repaying credit if the cultivation business is not able to produce the expected

productivity and profit. This is confirmed by Septanti et al. (2020) that smallholder dairy

farms still face problems of small business scale and limited capital and knowledge.

Cooperatives as the only link with IPS, related to the quality of cooperative services has

also not been able to fully encourage the acceleration of the increase in the scale of the

breeder's business. Business partnerships between farmers and cooperatives and IPS

should be encouraged in productive and integrated partnership activities, including through

Public Private Partnership programs (Pasaribu 2015). Thus, in the upstream and on-farm

subsystems, smallholder dairy farmers as the main contributors to the supply of fresh milk

in the country are faced with the ability of milk quantity and quality that have not been

able to compete with imported products.

Most of the fresh milk in the country (90%) is produced by smallholder

farmers in partnership with dairy cooperatives that are members of the Indonesian

Milk Cooperative Association (GKSI) organization. The price of dairy products

produced by farmers is strongly influenced by the existence of IPS in the

downstream subsystem. On the other hand, the dairy industry faces the condition of

the quality of milk products produced by smallholder farmers. Some of the quality of

domestic fresh milk has not met the SNI standards for fresh milk (TPC>1 million cfu

per ml and TS below 11.3%) so that the price of milk at the farm level will be

adjusted to the quality of milk produced. This is in line with Anugrah et al. (2021)

who reported that in Pangalengan-South Bandung, the price of milk between Milk

Collection Points (MCP) differs depending on the quality of milk with a standard

deviation ranging from IDR 200 - IDR 300 per liter, and bonuses are applied

according to grade based on the number of TPC.

The gap between the price of fresh milk received by farmers as milk producers and

the price of milk at the consumer level is still a problem. Competitive fresh milk

prices are needed to encourage the development of the national dairy cattle

agribusiness system. The price of fresh milk at the consumer level from 2008 to 2018

grew significantly by 7.12% per year (Pusdatin 2019).

A prolonged gap in the price margin of fresh milk at the farmer and consumer

level can result in a decline in the number of f a rm e r s and the dairy cattle population.

This condition will have a direct impact on farmer business profitability and national milk

production. Profitability of dairy cattle business is influenced by the price of milk along

with other factors such as the number of livestock ownership, investment, milk production,

concentrate feed costs and farming experience (Nisa et al. 2012). If allowed to drag on, the

hope of achieving food self-sufficiency from milk will be increasingly difficult to achieve.

The problems faced in the downstream subsystem are mainly in the milk supply chain

network, where IPS locations are mostly in DKI Jakarta and West Java Province. In

addition, out of 60 milk processing companies, domestic fresh milk is only absorbed by 14

companies. In the downstream subsystem, the main problem faced is the international price

of milk (powder) which is cheaper than domestic milk powder. The cheaper price in

exporting countries can be attributed to income over feed cost, that in exporting countries

with higher business scale supported by the availability of ranch system grazing land can

be more efficient in feed costs. This is evidenced by the results of research by Ozawa et al.

(2005) that the percentage of feed costs per kg of fresh milk in New Zealand is only 16%

of feed costs in Hokkaido Japan, even the total cost per kg of fresh milk incurred by

farmers in New Zealand is only 29% compared to Japan. The production cost to produce

milk is lower because the total dairy cow population in New Zealand reaches 4.921 million

heads with milk production reaching 21.1 billion liters per year (LIC and Dairy NZ 2020).

Thus, although the selling price of farmers' milk in exporting countries is lower than the

price of milk in importing countries, the net income earned by farmers in exporting

countries remains competitive.

Meanwhile, based on Minister of Finance Regulation No. 26 of 2022 on the

Determination of Goods Classification System and Imposition of Import Duty Tariffs on

Imported Goods, it is stipulated that the import tariff for milk is set at 5% (Table 1.2). The

purpose of the import tariff policy intervention in Table 1.2 is to protect farmers and as a

safety net for domestic fresh milk prices and imported raw material prices. This is

consistent with Priyanti et al. (2004) that import tariff policy intervention aims to protect

dairy farmers and the sustainability of the dairy industry in Indonesia. Efforts to protect

farmers through import tariff policy intervention (Table 1.2) are in line with the regulations

of Law No. 19 of 2013 on the protection and empowerment of farmers and Law No. 41 of

2014 on the amendment of Law No. 18 of 2009 on animal husbandry and animal health. In

article 13 of Law Number 19 of 2013 states that the government in accordance with its

authority is responsible for the protection of farmers and Article 15 states that to meet food

needs, the government must prioritize domestic production and the shortage is met from

imports It is also stated in Article 36B of Law No. 41/2014 that the import of livestock

products into the country can be done if domestic production and supply have not met

national demand.

In order to encourage the availability of milk in Indonesia, several relevant

regulations have been issued, one of which regulates the circulation of milk and farm

business partnerships. Business partnerships are crucial in the dairy agribusiness

system, given that milk is a perishable food product. Milk sales from farmers to

cooperatives, then from cooperatives to IPS cannot be separated from business

partnerships, both formal and informal. Business partnerships have been regulated in

MOA 13/2017 on Livestock Business Partnerships (Figure 1.3). In the

implementation of this regulation, the number of companies in Indonesia with

partnerships is 30 IPS companies and 99 importer companies with a total investment

of 751.75 billion (Murfiani 2020).

Through business partnerships that are also regulated in MOA No. 33/2018,

farmers provide a guarantee of industrial raw material availability to IPS and IPS provides

a guarantee of fresh milk markets to cooperatives, where cooperatives will provide milk

quality assurance from farmers. Based on what has been described previously, in an effort

to overcome problems that can hinder the achievement of the milk production target of

60% of national needs can no longer be resolved partially, but needs a solution with a

holistic system approach that is dynamic in nature.

The dynamic model can reflect efforts to revamp and develop the dairy cattle

agribusiness system that can adopt changes over time to build a sustainable and profitable

dairy industry for all actors in the interrelated system. The gap between domestic milk

production and national milk demand (supply and demand balance), the gap in milk prices

at the farmer and consumer levels, low productivity, relatively expensive seeds and feed,

fluctuations in the ratio of feed prices to milk prices, price dependence on IPS,

strengthening good dairy farming practices, and farmer capital accessibility as well as

cheaper international milk prices and demands for reduced import tariffs in international

trade are problems that need attention in the upstream-downstream subsystem. Based on

the existing problems, to achieve the target percentage share of milk production of 60% of

the total national demand, it is necessary to design a model of milk availability in

Indonesia.

The dynamic system approach is a solution to build an integrated interactive model.

System dynamics can be offered from the model built through efforts to achieve national

milk production targets, increase the population of dairy cows, increase milk productivity,

increase farmer profits, and increase milk prices at the farmer level in the national milk

availability model through a simulation. Through a dynamic system, forecasting and the

impact of policy intervention simulations on the model can be done to capture complexity,

non-linearity and causality, so that strategies and recommendations can be formulated for

efforts to develop the dairy cattle agribusiness system in Indonesia. Research on milk

availability models to support the development of dairy cattle agribusiness systems in

Indonesia through a system dynamics approach has a high urgency to be carried out in

solving the problem of the gap between domestic milk production and national milk

demand.

1.2 Supply and Demand Milk

Several previous studies related to milk supply and demand have been

conducted in Indonesia. Research related to trade policies that regulate milk imports

and exports also complement research results related to milk supply in Indonesia.

The gap between milk production and national milk demand led the government to

adopt a milk import policy to meet demand. The intervention of import quota policy

(import ratio) conducted before 1998 and subsequently through Minister of Finance

Decree No. 16/KMK/01/1998, the import tariff policy was established in the face of

international demands in the form of non-tariff barriers on agricultural products.

Until now, based on Minister of Finance Regulation No. 26 of 2022, the import tariff

for dairy products is set at 5%. The research results of Riethmuller et al. (1999)

showed that the elimination of the milk import ratio policy eliminated the obligation

of IPS to absorb domestic milk production as a precondition for imports. Through

this policy, IPS can obtain raw materials from imported milk at a lower price.

However, on the other hand, this is a dilemma for domestic milk producers to

improve business efficiency in order to compete with imported milk, because IPS

will not absorb milk at a higher price.

National milk production and milk imports are the sources of milk supply in

Indonesia. The contribution of national milk production currently only reaches 20-

23% of national demand (Riwu 2017; Pusdatin 2019), and it is expected that the

contribution will continue to increase. Sudaryanto and Hermawan (2014) stated that

the population of dairy cows as a determinant of the amount of national milk

production is not evenly distributed in Indonesia and most of them are smallholder

dairy farms with small business scale, simple technology, part-time and carried out

by family members. Efforts to increase national milk production in Indonesia cannot

be separated from the amount of milk prices that affect the viability of dairy farming.

This is in line with the research of Daryanto et al. (2020) that the price of fresh milk

in Indonesia is not only influenced by milk price volatility, but also by feed prices

and climate change. Furthermore, the results of the analysis using the ARCH-

GARCH method show that in the short term of the three dairy centers in Indonesia,

fresh milk price volatility often occurs in West Java.

Meanwhile, research conducted by Raharjo et al. (2020) found that 94.26 percent of

the variation in Indonesia's milk imports could be explained by the exchange rate,

GDP per capita, processed milk exports, and fresh milk production. In this study, the

explanatory variables used had a positive influence on milk imports, except for the

exchange rate variable which had a negative influence on milk imports. The results

of other related research conducted by Nurunisa et al. (2014) reported that there is a

cointegration relationship between the Indonesian milk market and the market of one

of the milk exporting countries (New Zealand). This indicates that Indonesian milk

importing companies will be affected if there is a shock to the milk market in New

Zealand.

Indonesia's milk demand is represented by the total national milk consumption.

According to Suryani et al. (2016) national milk demand is obtained from the su m of

milk demand of all regions in Indonesia which is influenced by population and milk

consumption per capita. According to Priyanti and Soedjana (2015), national milk

consumption is dominated by milk powder consumption at 43.3% and followed by

consumption of sweetened condensed milk made from milk at 20.4%. The use of milk for

the food industry such as ice cream, biscuits, candy, chocolate and other ingredients

reached 27.5%. Meanwhile, liquid milk consumption is only 8.5%, consisting of UHT

milk (4.6%), sterile milk (2.7%) and pasteurized milk (1.2%).

In addition to research related to milk supply and demand in the country, several related

studies were also conducted a b r o a d . The gap between national milk production and milk

consumption also occurs in Bangladesh. Research by Uddin et al. (2011) showed that

appropriate policy interventions are needed to increase milk production and reduce

dependence on imported milk powder in Bangladesh. The results of the study informed that

milk production in Bangladesh is dominated by smallholder dairy farms with traditional

systems so that milk production has not been able to meet national needs. In Ukraine, based

on the study of Kvasha et al. (2019) stated that the demand for milk can only be met from

the country's milk production as much as 55% of which more than 75% is produced from

the farmer's household business.

Research related to milk supply and demand was also conducted in Jordan by

Altarawneh (2015) with the result that milk price, number of lactating cows, variable costs,

and income per capita have a significant effect on cow's milk production. Meanwhile, on

the demand side, information was obtained that there was an increase in milk price

elasticity, so that consumption became slightly more responsive to milk prices and became

a matter of concern in milk sales. Furthermore, research by Shahid et al. (2012) in Pakistan

found that accessibility constraints of quality cattle breeds, inadequate availability of feed,

and the application of traditional farm management are the main problems resulting in

relatively low supply of cow's milk.

In the Asian region, research by Fuller et al. (2005) found that the main factors

causing the increase in demand for milk in China in t he last decade are the increase in

purchasing power and consumer preferences driven by awareness of the health benefits of

milk. Research by Song and Sumner (1999) showed that the demand for dairy products in

Korea is elastic and sensitive to income growth and modernization of the Korean economy.

It is projected that there is still great potential for growth in imports of dairy products for

manufacturing. Milk supply and demand conditions in developed countries are shown by

research on dairy trade between Australia and the United States. The results of research by

Alston et al. (2006) found that the impact of the Australia-United States Free Trade

Agreement (AUSFTA) negotiations had little impact on milk prices and production in the

United States.

World cow's milk production in 2015-2019 averaged 323,468 thousand tons

(64.49%) produced by dairy producers including the United States, India, China, Russia,

Brazil, New Zealand, Mexico, Argentina, Ukraine, and Australia, while the remaining

178,118 thousand tons (35.51%) were produced by dairy producers accumulated

production from other countries in the world (Pusdatin 2019). Along with the increasing

population and rising incomes, it is estimated that the demand for milk will continue to

increase, so Indonesia needs to accelerate the improvement of domestic milk production

capabilities.

1.3 Cattle Agribusiness System Dairy

The concept of agribusiness views a farm including dairy cattle holistically

starting from the provision of production facilities, production processes, processing,

to marketing (Siregar and Ilham 2003). Furthermore, the use of the agribusiness

concept must pay attention to two things, namely strengthening vertically integrated

subsystems and each subsystem is able to create efficient agribusiness companies, so

that livestock products including milk can increase their competitiveness. Pambudy

(2010) states that the birth of the agribusiness paradigm was motivated by the

emergence of the problem of price gaps at the farm gate price and consumers and the

price of products that fall during harvest. This is partly because the products

produced by farmers to get to consumers must go through interrelated stages in a

system. In the system, there are various business actors from upstream to

downstream that are holistically interdependent.

Competitive advantage in the dairy cattle agribusiness system can be done by

increasing market share and profit of actors in the system by considering

productivity, technology, products, inputs and costs, industrial structure, and the

amount of market demand (Martin et al. 1991). The availability of quality supporting

human resources (HR) is also a determinant of competitive advantage in the

agribusiness system (Mugera 2012). Efforts to achieve business efficiency through

competitive and comparative approaches in the agribusiness system require the role

of government in the supporting subsystem through investment in research,

extension, breeding and marketing facilities; spatial arrangements for the provision of

grazing land; and regulation of business patterns in the agribusiness system (Siregar

and Ilham 2003). Agribusiness systems are closely related to supply chains, where in

a modern global market environment if the level of domestic government support and

trade barriers continue to decline, agricultural producers will be severely affected by

oversupply, so efficient supply chains are important for maintaining sustainable

agricultural production (Bolotova 2014).

Milk production is the core process carried out by dairy farmers as business

actors in the on-farm subsystem. The results of research by Asmara et al. (2016)

showed that forage inputs, concentrate feed, labor, and the number of lactating cows

are the main determinants that affect milk production and dairy cattle businesses

with a larger scale of cow ownership will show higher business technical efficiency.

Arsenault et al. (2009) found that the life cycle of the on-farm subsystem of dairy

cattle agribusiness in Canada is linked to the upstream feed supply subsystem,

namely the production of feed ingredients for concentrate feed processing and

pasture cultivation as a source of forage The dairy cattle population will produce

manure that can be used as a source of compost in the pasture.

Research by Sirajuddin et al. (2017) found that the problems faced by farmers in

increasing milk production are low dairy cow ownership, low milk productivity, and

uncompetitive milk selling prices. Dairy farmers in the on-farm subsystem need to be

supported by cooperative empowerment through the provision of dairy cows, provision of

quality forage and concentrate feed at affordable prices, and development of milk

marketing networks. Research conducted by Mukson et al. (2010), that in Semarang

Regency, Central Java Province has the potential to be used as a location for dairy cattle

agribusiness development with a Location Quotient (LQ) value of 4.67 (LQ>1) and social,

economic and demographic resources are important factors that must be considered in the

development of dairy cattle agribusiness. Research in Boyolali District, Central Java

Province by Santoso et al. (2013), also showed the same thing where the LQ value was >1

and the determinants of dairy farmer income in the on-farm subsystem were the age of the

farmer, the amount of milk production and feed costs.

In the dairy cattle agribusiness system, farmers cannot be separated from the role of

dairy cooperatives. Dairy cooperatives have a strategic role in helping to increase farmers'

income, but monopsony IPS have a negative impact on the independence of farmers and

dairy cooperatives (Yusdja 2005). The dairy agribusiness system in Indonesia places IPS

quite favorably in the market due to their relatively limited number, so IPS tend to form an

oligopsony market in the purchase of fresh milk through cooperatives, where milk prices at

farmers and cooperatives are highly dependent on IPS (Yusdja and Rusastra 2001). In the

agribusiness system model, optimization efforts are required using a combination of

various limited inputs to achieve the ultimate goal by maximizing profits or minimizing

costs (Tuguz et al. 2015).

The problems faced by cooperatives in relation to dairy farmers are the limitations of

cooperatives to develop markets independently, the business of farmers as members has

not been fully fostered efficiently, and the existence of barriers between cooperatives as

profit-maximizing companies and fostering farmers to maximize their profits (Yusdja and

Rusastra 2001). Efforts to encourage the development of dairy cattle agribusiness can be

made through cooperative empowerment by providing a source of dairy cattle breeding

stock and providing quality concentrate feed at affordable prices (Rusdiana and Sejati

2009). Even the white revolution in India was carried out through the establishment of

dairy cooperatives with the target of increasing domestic milk production as an economic

driver and creation of added value, as well as to cut distribution channels to make milk

prices at the farm level more competitive (Duncan 2013). The white revolution has placed

India as the world's top milk producer with milk production reaching 155.4 million tons in

2015-2016 (Kale et al. 2018). Based on data from the Indian Ministry of Statistics and

Program Implementation, it is known that per capita milk consumption in India reaches

406 grams/day or 148.19 kg/day.

Strengthening dairy cooperatives can be done through an inventory of cooperative

institutions, identification of access to capital, markets, and business networks,

strengthening of dairy cooperatives, and strengthening of cooperative networks training and

education, cooperative accreditation, cooperative institutional viability, and utilization of

the internet, technology, and information systems (Priyono and Priyanti 2015). The

development of cooperative entrepreneurs with competencies according to cooperative

commodities can be one of the ways that can be taken for cooperative development in the

agribusiness system (Baga 2003). In order to have good bargaining power, dairy

cooperatives can enter into institutional contracts with farmers and IPS in the form of

business partnerships that are fair and can improve the welfare of dairy farmers (Sebayang

2013).

In the downstream subsystem, the role of large milk processing companies

determines the price received at the farm level. Efforts to increase profit margins and

problems with milk quality standards are thought to be the reasons why large

processing companies in the downstream subsystem must set significant limits on

farmers' milk purchase prices (Godfrey et al. 2018). The supply of dairy products in

the downstream subsystem is influenced by international competition. The dairy

industry sector in Germany has internationally competitive dairy products in the

form of fresh milk products such as yogurt, milk powder and evaporated milk, while

in Italy, the Netherlands and Denmark the competitive dairy product is cheese

(Drescher and Maurer 1999).

The government's role in the agribusiness support subsystem, in setting milk

prices, needs to consider the balance of milk prices at the consumer level and at the

farm level. The government needs to decide on policies t o support price balance,

for example by considering subsidy scheme programs (Sulastri and Maharjan 2002).

On the other hand, the government in supporting the development of the national

dairy industry in the downstream subsystem, also needs to consider efforts to reduce

the carbon footprint, where the main source of carbon footprint of dairy cows comes

from feed, enteric gas, and manure (Mayuni et al. 2019). Such carbon footprint

reduction programs to prevent global warming have additional cost consequences

that need to be taken into account (Foote et al. 2015). However, the dairy industry is

not the dominant contributor to Indonesia's carbon footprint. According to Carbon

Brief (2019), Indonesia's carbon footprint is dominated by peatland fires, coal use

(energy), forestry and land use, waste, industrial and agricultural activities.

1.4 Model Design and Development of Policy Recommendations through a

System Dynamics Approach

The design of models to solve problems in t h e agricultural sector using a

system dynamics approach has been widely carried out both domestically and

abroad. Through the dynamic system model, policy recommendations can be

formulated using several scenarios in the model. Rosiana's research (2019) built a

model of Indonesian coffee exports with a dynamic system approach that divides

into a supply submodel, demand submodel, and trade submodel. The results showed

that the scenario of policy integration of intensification, extensification, elimination

of Value Added Tax (VAT) and a decrease in population growth rate was the best

scenario in the simulation of the Indonesian coffee export model. Bastan et al. (2018)

also conducted research on sustainable agricultural development through a system

dynamics approach. This research utilizes scenarios to achieve increased farmer

profits and guaranteed water availability for sustainable agricultural development.

Panikkai (2017) developed a model of maize production development to meet industrial

needs and improve Indonesia's economy by building a supply submodel, a demand

submodel and a regional economic submodel. The model was built with the aim of

providing recommendations for achieving corn self-sufficiency. Policy recommendations

from the simulation results showed that a combination of scenarios of increasing land

extensification, increasing productivity, decreasing imports, and decreasing population as

scenarios that provide the best performance in the model. Furthermore, Panikkai et al.

(2017) stated that the simulation results of sustainable maize self-sufficiency is achieved

when applying the scenario of increasing extensification and increasing maize productivity

with simulation results able to exceed the government target of 24 million tons, namely

25.83 million tons for increasing extensification and 26.69 million tons for increasing

productivity. Ariadi et al. (2016) also conducted research on integrated farming models of

cassava commodities through a dynamic system approach. The scenario of using organic

fertilizer in the integration of cassava crops - goats is simulated to be able to reduce

farming costs ranging from 27.75% to 34.36%.

Research on policy models to increase sugar production and income of sugarcane

farmers in East Java was also conducted by Yunitasari et al. (2015) with the aim of

analyzing the Revitalization of the National Sugar Industry (RIGN) policy towards

increasing White Crystal Sugar (GKP) production in an effort to meet government targets.

The results showed that the policies of area, productivity and yield increase were

simultaneously able to increase sugar production in East Java in accordance with the

target. Similarly, the scenario is simultaneously able to increase the income of sugarcane

farmers per hectare beyond the existing conditions. Nugrahapsari et al. (2013) also

conducted research related to the effectiveness of the national sugar industry revitalization

policy on the achievement of self-sufficiency in white crystal sugar with a dynamic system

approach. The simulation results concluded that increasing yields has better performance

than increasing productivity and sugarcane area. However, it will be more effective if the

increase in yield, increase in productivity and area expansion are carried out

simultaneously.

Hasibuan et al. (2012) built a dynamic model of the cocoa agro-industry system

built from 4 submodels, namely cocoa processing submodel, raw material supply

submodel, trade submodel, and consumption submodel. The policy scenarios applied in the

study are the impact of achieving the national movement policy (gernas) and cocoa export

duties made in pessimistic, moderate, and optimistic scenarios. Simulation results show

that the gernas policy and cocoa export duty are simultaneously able to absorb domestic

cocoa bean production and increase the share of processed cocoa export volume and value.

Farmers involved in the gernas cocoa program are able to raise their income levels.

Research using a system approach was also carried out by Basith (2012) with the aim of

studying the behavior of rice supply in Indonesia using ithink software. The design of the

national rice stock model system consists of farmer subsystem, collector subsystem,

cooperative subsystem, milling subsystem, wholesale subsystem, Bulog subsystem,

importer subsystem, retailer subsystem, consumer subsystem, and national stock

subsystem. The results showed that the model described the dynamics of the ten

subsystems and the results were not significantly different from the actual data in the field.

The post-harvest shrinkage parameter has the most significant influence on the amount of

milled dry grain production, so it is recommended to follow up with a problem-solving

strategy.

A dynamic model of the national meat availability system has been

conducted by Harmini et al. (2011) which was built in the national beef demand

submodel and the national meat supply (production) subsystem. The results show

that if the government implements the recommended policy scenario of the business

as usual program, the 2014 meat self-sufficiency target will not be achieved. In

contrast, beef self-sufficiency is projected to be achieved in 2015 if policy

interventions are implemented to reduce the slaughter of productive female cattle and

increase crossbreeding through IB. However, this needs to be anticipated if there is

an increase in the demand for meat consumption.

Denny et al. (2011) conducted research on the impact of biofuel development

policies on the dynamics of national food and energy commodity prices using a

dynamic system approach. The model consisted of three submodels, namely CPO

submodel, diesel oil submodel, and biodiesel submodel. The policy

recommendations show that an increase in CPO supply by 50% will result in a

decrease in domestic CPO prices. CPO consumption will decrease with the

development of CPO-based bioenergy, and this will also affect the domestic CPO

price. The dynamic system model approach was also used by Purnomo et al. (2020)

who analyzed the palm oil value chain with the aim of being sustainable using

intensification scenarios, no deforestation, no peat strategy and land swaps. Through

a dynamical system approach, a solution is simulated to address the trade-off

between economic development and environmental conservation.

A sustainable rice self-sufficiency model to support food sovereignty and

security has been developed by Nurmalina and Harmini (2014). The model is built in

two subsystems, namely the rice demand subsystem and the rice supply subsystem,

where rice demand is identified from public consumption, processing industry, and

exports. The simulation results show that improvement policies from the supply side

including improvements in productivity, production, and land management provide

better model performance towards sustainable rice availability. In order to obtain

optimal results, extensification policy strategies need to be integrated with

intensification policies to be sustainable in the future.

Nurmalina (2007) also conducted research using a systems approach in building a

sustainable rice availability balance model in Indonesia with the aim of designing a

rice availability balance model using a dynamic systems approach. The rice

availability balance model is translated into a national rice supply submodel, a

demand submodel, and a rice availability balance model.

A dynamical systems approach was also conducted by Walters et al. (2016) in the

USA to model crop production systems, livestock, and the integration of both to see

environmental, social, economic, livestock production, and crop production changes due to

interventions in the model. Kotir et al. (2016) modeled the sustainable management of

water resources with agricultural development in the Volta River Basin of West Africa

with the result that the business as usual scenario simulated the population and water

demand for agriculture will continue to increase. The water infrastructure development

scenario was simulated to provide maximum benefits for farmers and residents living in

the watershed.

McRobert et al. (2017) utilized a system dynamics approach to analyze the impact

of several scenarios on the financial performance of dairy cooperatives in Mexico. The

results show that dairy cooperatives have the potential to improve their financial

performance by controlling the environment and market conditions in the analyzed system.

Nicholson and Stephenson (2014) also used a dynamical systems approach by modeling

the dairy industry.

A quantitative study was conducted in the USA to determine the impact of

market dynamics on the Margin Protection Program (MPP). The analysis shows that

MPP in the dairy industry will weaken market feedbacks through lower prices, lower

margins, and greater government spending.

Research on model design through a system dynamics approach on livestock

commodities, especially those related to the model to be built in this study, is still

limited. Some research in the livestock agribusiness sector that builds models and

simulates policy scenarios using a dynamical system approach that includes model

design, validation, and simulation of policy scenarios can be seen in Table 2.1.

1.5 Government Policy in Dairy Industry Development National

In supporting the development of the national dairy industry, the government

through the Coordinating Ministry for Economic Affairs has issued the Indonesian

Dairy Blueprint 2013-2025. The blueprint serves as a policy basis for

Ministries/Institutions in the development of the dairy industry in Indonesia. The

Ministry of Agriculture has issued Minister of Agriculture Regulation No.

33/Permentan/PK.450/7/2018 on the Amendment of Minister of Agriculture

Regulation No. 26/Permentan/PK.450/7/2017 on the Supply and Distribution of Milk

to improve milk regulations in Indonesia, namely Presidential Instruction No. 2 of

1985 and Presidential Instruction No. 4 of 1998. In an effort to improve the welfare

of farmers, there has been MOA No. 13/2017 on livestock business partnerships that

will be interrelated with MOA No. 33/2018. In detail, the dynamics of dairy

regulations and policies that have been implemented in Indonesia can be seen in

Table.

1.1.1 Foundations of Economic Theory Balance Sheet Availability Milk

The balance of milk availability can be used to measure the performance of

milk supply (supply) and milk demand (demand). Milk supply is the sum of national

milk production plus milk imports minus exports and plus stocks. Milk demand is

represented by milk consumption and population. Milk consumption in this study is

measured using total cow's milk consumption without being broken down by source

due to data limitations. In the availability balance model, if demand is higher than

supply (excess demand) then there is a negative national availability balance,

otherwise if there is excess supply where availability is higher than demand then

there is a positive national availability balance (Nurmalina 2007). The availability

balance is also shown by Pindyck and Rubinfeld (2013) in the theory of supply and

demand balance which can be seen in detail in Figure 3.1 below.

Furthermore, the economic theory of milk availability balance can be

explained using the proxy of milk supply and demand behavior that occurs in

Indonesia associated with trade between two countries. This is because whether there

is excess demand (negative availability balance) or excess supply (positive

availability balance), in order for needs or demands to be met, it is necessary to

trade. The milk supply and demand mechanism between importing and exporting

countries in the world market (international equilibrium) can be explained in Figure

3.2.

(b). This shows that the excess demand of importing countries can meet the

excess supply of exporting countries so that there is a balance in the world

market.

As one of the sources of national milk supply, national milk production represents

activities to produce output through the transformation of various inputs in dairy cows into

milk products. Acceleration of milk supply is an effort to meet its own milk needs or fulfill

national milk demand (self-sufficiency). Policies that can be implemented to encourage

increased national milk production include regulation of milk imports. Government

intervention in regulating milk imports in Indonesia, until now, has been the milk import

tariff policy and the milk import ratio policy (Bukti Serap - BUSEP). The import ratio

policy is set at a ratio of 1: 2, where every import of two tons of milk raw materials, must

absorb one ton of domestic fresh milk, has been removed based on INPRES Number 4 of

1998 concerning Coordination of National Dairy Development. Based on the INPRES, the

provisions in the Annex to INPRES Number 2 of 1985 Article 1 point 8, Article 1 point 9,

Article 6 paragraph (1) and all provisions relating to the control of milk imports, the

obligation to absorb domestically produced milk, and the control of milk prices in the

country are declared no longer valid.

Milk import tariffs are a policy implemented by the Government aimed at

protecting dairy farmers by maintaining domestic milk prices above world milk prices, so

that the domestic dairy industry will be more competitive. Abidin (2015) stated that the

application of import tariffs (import duties) is one of the policy interventions aimed at

protecting farmers by creating conditions that result in prices that are above world milk

prices agricultural commodities that benefit farmers. Government intervention through

import tariff policies is an effort to protect dairy farmers that has been regulated through

the regulation of Law No. 19 of 2013 concerning the protection and empowerment of

farmers and Law No. 41 of 2014 concerning amendments to Law No. 18 of 2009

concerning animal husbandry and animal health. The protection is one of the protective

measures to help farmers in facing the problems of business certainty, price risk and high

cost economic practices.

3.1.2 System and Business Agribusiness

The agribusiness system is a series of activities consisting of mutually

influencing subsystems including the agricultural input supply subsystem (upstream),

agricultural production subsystem, product processing subsystem, marketing

subsystem and agribusiness service/support subsystem (Saragih 2001; Saragih 2010).

Each of these subsystems contains interrelated business processes ranging from

upstream including agricultural production facilities, agricultural cultivation,

agricultural tools and machinery to downstream including post-harvest processing or

raw materials for other sectors, distribution and marketing.

The direction of agribusiness system development in Indonesia is carried out

to realize a competitiveness, people-driven, sustainable and decentralized

agribusiness system (Saragih 2010). Through the development of the agribusiness

system, the development of the industrial, agricultural and service sectors will each

strengthen each other to produce products needed by the market. The development of

agribusiness systems in Indonesia can be carried out on various strategic

commodities, one of which is the dairy cattle agribusiness system. Dairy cattle

agribusiness system in Indonesia in the future needs to be supported with

competitive advantage and comparative advantage.

David and Goldberg (1957) define agribusiness as all operations related to

the manufacture and distribution of agricultural supplies, on-farm production

activities, storage, processing and distribution of a g r icul t ur a l commodities The

agribusiness system can also be interpreted as all activities ranging from the

procurement and distribution of production facilities to the marketing of products

produced by farms and agro-industries related to each other (Saragih 2010). The

agribusiness system includes five subsystems, namely: (a) Upstream agribusiness

subsystem for industries that produce agricultural capital goods; (b) On-farm

agribusiness subsystem for cultivation activities that produce primary agricultural

commodities; (c) Downstream agribusiness/processing subsystem; (d) Downstream

agribusiness/marketing subsystem for industries that process primary agricultural

commodities into processed industries; and (e) Subsystem of service providers and

agribusiness supporters such as credit, transportation and logistics storage, R&D,

education, and economic policy (Deptan 2002; Saragih 2004; Saragih 2010).

The subsystems in the agribusiness system include interrelated business processes

from upstream to downstream. Upstream business processes include agricultural

production facilities, agricultural cultivation, agricultural tools and machinery, while

downstream business processes include post-harvest processing that produces goods ready

for consumption, or raw materials for other sectors, as well as distribution and marketing.

The complete scope of the agribusiness system can be seen in Figure 3.5.

Through the development of agribusiness systems and businesses, the

development of industry, agriculture and services will strengthen each other to

produce products needed by the market. The development of competitive

agribusiness systems and businesses is how to change from unskilled human

resources (factor-driven) to the development of agribusiness systems and businesses

that rely on capital goods and more skilled human resources (capital-driven).

Furthermore, the development of agribusiness systems and businesses is directed at

the development of science and technology (IPTEK) and skilled human resources

(innovation-driven). If the stage has reached innovation-driven, then Indonesia will

have competitiveness at the global level.

Dept. of Agriculture (2002) and Saragih (2004) stated that in order to achieve

the development of competitive, populist, and sustainable agribusiness systems and

businesses, the supporting policy challenges needed are macroeconomic policies,

industrial development policies, trade policies and international cooperation, land

policies and infrastructure development, security policies and law enforcement,

policies to improve farmer human resources, development of farmer organizations,

and development of agribusiness growth centers in the regions.

3.1.3 Systems and Systems Approach Dynamic

The system is a business unit consisting of subsystem parts that are

interrelated, interacting, and related in achieving goals in a complex environment

(Marimin and Maghfiroh 2010). The systems thinking approach begins with

capturing a system based on real conditions to be modeled and implementing policy

changes through a rigorous modeling process (Forrester 1994). In real life, efforts to

solve complex and diverse problems cannot be successfully resolved if only one or

two specific methods are used (Nurmalina 2007). The stages of the system approach

according to Manetsch and Park (1977) in Nurmalina (2007) and Rosiana (2019)

consist of needs analysis, problem formulation, system identification, system

modeling, model testing and validation, and implementation.

The dynamical system approach is a modeling approach that simplifies the

complexity of the real world in a model concept that captures changes in the time

dimension of the system in the form of feedback loops that show the structure and

behavior of the real world (Muhammadi et al. 2001). In dynamic system modeling, a

system is defined pragmatically as a set of parts organized for a specific purpose

(Coyle 1996). Complex and dynamic problems in real life can be solved through a

systems approach (Sterman 2000). Changes in the time dimension are manifested

dynamically and dynamic systems can reflect the process, behavior and complexity

of a system (Forrester 1994; Sterman 2000). Understanding the structure and

behavior in a dynamical system model is necessary in designing and analyzing a

phenomenon. Understanding the structure includes the variables or elements that

form the phenomenon and the relationship between variables, while understanding

the behavior includes changes in a variable within a certain period of time, for

example milk production per year.

Based on Figure 3.6, model design involves a model structure consisting of various

variables that are interrelated in a dynamic system. The model that represents the real world

is limited to the objectives of the research. In order to obtain a good and effective model,

iteration is required by conducting various experiments and learning from the concept

model (mental model) and information obtained from the real world. Mental models are

built to simplify the complexity of the real world in a constrained system based on

information from the real world. The formulation of strategies, structures and decisions in

the real world can be done through simulation using models that have been tested for

validity, then from the real world can be obtained feedback information (Sterman 2000).

According to Forrester (1994), the stages of the dynamical system process begin with

describing the system and hypotheses/theories that are built and formulated in level and

rate equations in the dynamical system model. Model simulation can be done after the

previous step meets the logical criteria. Simulation tests are carried out to determine the

most rational policy alternatives. Evaluation and discussion are needed to determine the

impact of policy simulation implementation and then the appropriate new policy can be

implemented. The steps of modeling with the dynamic system method according to

Sterman (2000), consist of problem formulation, dynamic hypothesis formulation,

simulation model formulation, testing, and policy design and evaluation where these steps

are iterative steps. The stages in modeling with a dynamic system approach according to

Forrester (1994) can be seen in Figure 3.7.

3.2 Operational Framework

The national demand for milk has yet to be met by domestic milk production. The

high level of gap between milk availability and national milk demand is an inhibiting

factor in efforts to achieve national food independence and sovereignty from livestock.

Various problems are still faced in the dairy cattle agribusiness system in Indonesia,

including the upstream and on-farm subsystems faced with technical constraints, namely

the ratio of the number of lactating mothers to the total population and the low milk

productivity of dairy cows. The monopsony structure of the milk market, where 90% of the

market share is controlled by IPS (Priyono and Priyanti 2015), causes business actors in

the on-farm subsystem to stagnate. Although there are currently dairy cooperatives, the

dependence of farmers on IPS in marketing milk results in farmers being in a low

bargaining position as indicated by low farmer income and milk quality below SNI (TPC >

1 million cfu/ml and total solid < 11.3% (Murfiani 2020; Miskiyah 2011).

The application of good dairy farming practices on smallholder farms has not been

carried out massively and the adoption of technology, business concepts, and the creation

of added value in the upstream and on-farm subsystems has an impact on the quantity and

quality of milk that is not in accordance with the expected target. The existence of

cooperatives as the only link between farmers and IPS has not been fully optimized in

encouraging the acceleration of farmers' business scale increase. In the downstream

subsystem, the efficiency of the milk supply chain network is still faced with the center of

the dairy industry in Java. Domestic milk production, which is mostly produced by

smallholder farmers, is only absorbed by 14 companies out of a total of 60 milk processing

companies in Indonesia. Another constraint is that the price of milk powder produced by

the domestic industry is higher than the international price of milk powder, especially since

the import duty rate is only set at 5%.

Indonesia in increasing national milk production cannot be separated from the dairy

cattle agribusiness system. The agribusiness system is the totality or unity of agribusiness

performance consisting of upstream agribusiness subsystems; farming subsystems;

agribusiness processing subsystems, marketing subsystems; and supporting subsystems

(Deptan 2002; Saragih 2004; Saragih 2010). Improvement and optimization of the

upstream, on-farm, and downstream subsystems are believed to encourage the

development of the dairy cattle agribusiness system in Indonesia. The target of national

milk production to reach 60% of national demand (Coordinating Ministry for Economic

Affairs 2013; Ministry of Industry 2009) is both an opportunity and a challenge in

supporting the development of the dairy cattle agribusiness system in Indonesia. The

accelerated increase in production needs to be followed by an increase in productivity from

8-10 liters per head per day to 20 liters per head per day and an increase in the income and

welfare of farmers to accelerate the availability of national milk. Modeling milk

availability to support the development of dairy cattle agribusiness systems in Indonesia

through a dynamic system approach has a high urgency to be carried out in solving the

problem of the gap between domestic milk production and national milk demand. In more

detail, the operational framework of this research can be seen in Figure 3.10.

1.2 Design Research

The research design uses a system dynamics approach and quantitative methods

with the support of simulation tools in analyzing the national milk availability model to

support the development of the dairy cattle agribusiness system. The system dynamics

approach can be used to design, develop concepts, make updates, and evaluate the impact

of policy changes applied in the model (Forrester 1994; Sterman 2000). Research on

national milk availability models that are analyzed holistically for the development of

dairy cattle agribusiness systems with a system dynamics approach is still limited, so the

design of the national milk availability model is a solution for consideration in the

formulation of strategies and alternative policy recommendations in an effort to accelerate

the availability of fresh milk in Indonesia and increase the cumulative profit of farmers.

In this study, the national milk availability model uses a positivism, empirical and

quantitative approach based on the real conditions of the dairy economy in Indonesia

which cannot be separated from the dairy cattle agribusiness system in Indonesia. This

approach begins with model specification and model evaluation and can be respecified to

obtain a model that is closest to reality (Sterman 2000). Model specification includes

derivation, design, development, construction, prototyping or creating something new

(Shamsuddoha 2014). Thus, this research will develop a model design to achieve the

targets set by the government and relevant stakeholders.

Dynamical systems are concerned with systems that have causal relationships

between related variables over time. This is very suitable for analyzing the national milk

availability model which consists of interdependent subsystems. Models built using

dynamical systems can reflect real-world approaches, non-linearity, feedback and

complexity holistically (Forrester 1994). System dynamics is an approach to modeling

interconnected subsystems that will form feedback loops that will describe the behavior of

the system (Shamsuddoha 2014).

1.3 Types and Sources Data

The national milk availability model supports the development of dairy cattle

agribusiness systems using secondary data. The data source used secondary data of

national scope from the Central Bureau of Statistics (BPS), Ministry of Agriculture,

Coordinating Ministry for Economic Affairs, Ministry of Industry, and Food and

Agriculture Organization of the United Nations (FAO). Supporting quantitative data were

obtained from cooperatives, GKSI, farmers, and samples of milk processing companies

from some of the results of the author's research activities at the Livestock Research and

Development Center, Balitbangtan, Ministry of Agriculture and a number of Focus Group

Discussion (FGD) activities on dairy cows and dairy in the 2016-2019 period.

In building and developing the model, a descriptive statistical analysis of milk

supply and demand in Indonesia was conducted. In order to obtain key variables

affecting national milk supply and demand, Two Stage Least Square (2SLS) analysis

and simultaneous equation system models using Statistical Analysis System (SAS) 9.4

were conducted using secondary data at the national level. The milk availability

model with a dynamic system approach was analyzed through several stages of

research consisting of needs analysis, problem formulation, system identification

(causal loop diagram and black box diagram), model formulation (stock and flow

diagram), model validation (structure and output) and model simulation along with

sensitivity analysis using secondary data and primary data that researchers followed

in 2016-2019 at the Livestock Research and Development Center. Dynamic system

modeling was analyzed using Vensim PLE and Powersim Studio 10 Academic.

1.4 Data Analysis and Processing Methods

1.4.1 Supply and Demand Analysis Milk

The milk supply and demand analysis method uses descriptive statistical analysis

covering the appearance and development of milk in Indonesia and the world

including indicators of population, production, consumption, availability, prices,

exports and imports. In detail, indicators of milk supply and demand analysis in

Indonesia and the world can be seen in Table 4.1.

1.4.2 Analysis of Factors Affecting Milk Supply and Demand in Indonesia

The identification of factors affecting milk supply and demand in Indonesia

was estimated using the Two Stage Least Square (2SLS) method. The selection of

the 2SLS method was determined after based on the order condition criteria, the

structural equation in the model was declared over identified. Simultaneous

equations with the 2SLS estimation method are carried out with the aim of seeing the

relationship between variables grouped into several blocks of equations or economic

aspects, especially those related to milk supply and demand.

a. Specification Equation

A model is a representation of actual conditions. An econometric model is a pattern

of stochastic economic phenomena that includes one or more confounding variables

(Intriligator et al. 1978). Furthermore, according to Koutsoyiannis (1977), econometric

models are an integration of economic theory, economic mathematics, and statistics.

Econometric models can be used for: (a) testing economic theory, (b) providing the

estimated value of economic behavior parameters, and (c) using the estimated value to

predict future economic conditions. Model specification is an effort to study the

relationship between variables and be able to express the relationship in the form of

mathematical equations. In developing the model specification, the process is based on

theory and various empirical experiences relevant to the conditions of dairy agribusiness in

Indonesia.

1.4.3 Dynamic System Model Analysis

The stages of dynamic system model analysis in this study were carried out in

6 stages, namely needs analysis, problem formulation, system identification, model

formulation, model validation (validity and reliability) and policy simulation

(Forrester 1994; Wolstenholme 1999; Nurmalina 2007; Van der Aalst et al. 2010;

Shamsuddoha 2014; Rosiana 2019). Nurmalina (2017) also said that in the system

methodology there are six stages of analysis, namely needs analysis, system

identification, problem formulation, formation of system alternatives, determination

of physical, social and political realization, and determination of economic and

financial feasibility. The dynamic system model analysis in this study uses powersim

studio 10 software.

a. Needs Analysis

The needs analysis in the national milk availability model to support the

development of the dairy cattle agribusiness system in Indonesia based on the results

of the literature review can be seen in Table 4.2. The needs analysis was refined

based on the policy review of the Focus Group Discussion results involving experts

in the dairy sector.

b. Problem Formulation

The different needs and desires of the actors in the dairy cattle agribusiness

system will result in conflicts of interest that can interfere with the achievement of

system goals. Thus, it is necessary to analyze the problem formulation faced by each

actor involved in the system. In problem formulation, it is necessary to consider

several things, namely learning from previous problems, detecting what problems

and how problems arise, the possibility of problem transformation, and analyzing

problems appropriately (Hovmand 2014). The problems faced by system

actors/stakeholders in the system based on the results of the literature review are

presented in Table 4.3.

c. System Identification

System identification is done by linking the results of the needs analysis and

problem formulation of stakeholders in the dairy cattle agribusiness system in

Indonesia. The identification of variables in the system can be done through searches

based on literature studies using secondary data and through empirical studies

through observation, interviews, and FGDs (Aghalaya et al. 2012). The milk

availability model supporting the development of the dairy cattle agribusiness system

is built through three submodels, namely the national milk production submodel, the

milk import-export submodel, and the national milk demand submodel. The main

goal of the model is to increase the percentage share of domestic milk production to

demand, decrease the deficit of milk availability balance and increase the profit of

dairy farmers.

1) Causal Loop Diagram

Cause and effect diagrams provide graphical information about the

interrelationships between elements in the model (Sterman 2000). The arrow

upstream indicates the cause and at the end of the arrow indicates the effect and

within the submodel there are positive and negative signs. The positive sign reflects

that the addition of one variable will cause an increase in the variable connected to

the arrow (Wolstenholme and Coyle 1983; Sterman 1989; Sterman 2000).

The relationship between variables built in the milk availability model is

based on theory, empirical studies, research results, logic, government, and other

factors related reports, and study of relevant literature. The theory is based on the

concept of supply and demand in the dairy cattle agribusiness system. The detailed

diagram of the submodel built in this study is divided into three submodels, namely:

(a) National milk production submodel; (b) Import-export submodel; and (c)

National milk demand submodel.

The milk availability model to support the development of dairy cattle agribusiness

system in Indonesia is built with a balance approach between national milk supply and

demand. The national milk production submodel and the import-export submodel represent

the national milk supply. T h e national milk production submodel will also examine the

causal relationship of profits received by farmers from farmers' milk production. More

than 90 percent of national milk production is produced by smallholder dairy farmers,

however, the bargaining position of farmers is lower in the dairy cattle agribusiness system

in Indonesia.

In this study, the national milk production submodel represents conditions in the

upstream and on-farm subsystems of the dairy cattle agribusiness system. The import-

export submodel describes conditions in the downstream subsystem of the dairy cattle

agribusiness system. In this study, the national milk production submodel and import-

export submodel are part of the national milk supply. Furthermore, the national milk

demand submodel explains the need for milk to fulfill consumption for people in

Indonesia.

The milk availability model supporting the development of agribusiness systems in

Indonesia is the subtraction of the total national milk supply from the national milk

demand. Based on Figure 4.1, referring to the main objectives of increasing the percentage

share of domestic milk production, reducing the milk availability deficit and increasing the

profit of dairy farmers, the milk availability model is built by taking into account

government policies that regulate milk circulation, imports, exports, and policies to

increase national milk production involving all actors in the dairy cattle agribusiness

system in Indonesia. The urgency of farmer profit is built into the national milk production

submodel. It aims to explore the impact of various policy intervention scenarios in the

model on dairy farmers' profit.

In the national milk production submodel, if the population of dairy cows increases

with the support of increased milk productivity, it will encourage an increase in the supply

of domestic fresh milk production. The continuity of milk production in dairy cows must

consider the delay time of raising female calves to become mothers and the delay time of

raising bulls to be ready for sale. The quantity and quality of feed for dairy cows is a top

priority in addition to seeds, as it will affect productivity and milk quality. The availability

of feed in the form of forage and concentrates will encourage increased milk productivity

at the farm level. A detailed causal loop diagram of the milk availability model in

Indonesia can be seen in Figure 4.1.

2) Input Output Diagram (Black Box Diagram)

Based on the causal loop diagram, an input output diagram (black box

diagram) can be prepared. The input output diagram illustrates the relationship between

inputs and outputs based on the results of the needs analysis, problem formulation, and

causal loop diagram (Nurmalina 2007; Rosiana 2019). Uncontrolled inputs are inputs that

affect national milk availability but cannot be controlled such as population, milk price and

climate change. In contrast, controlled inputs are controllable inputs that affect national

milk production, namely seed and feed technology, c ul ti va t i o n technology, processing

and distribution technology, dairy cattle population intensification and extensification

programs, and per capita milk consumption. Inputs environment are inputs that by not

which indirectly affect national milk production, namely national socio-economic

conditions, rupiah exchange rate, interest rate, and externalitiesModel Formulation

The formulation of the milk availability model to support the development of

the dairy cattle agribusiness system in this study was built on three submodels,

namely the national milk production submodel, the import-export submodel, and the

national milk demand submodel. Model formulation is done by describing the model

in level and rate equations (Forrester 1994).

1) National Milk Production Submodel

The national milk production submodel is built by focusing on the main

determinants that determine milk production, namely feed and mother cow

population. Feed availability comes from forage production and concentrate feed

production. Feed support and cattle farming infrastructure will determine the

structure of the dairy cattle population in Indonesia. The total national dairy cattle

population is derived from the components of calves, heifers, mother cows, young

bulls and mature bulls. Female calves born are modeled to be raised to motherhood

with a delay time of about 2 years. Male calves will partly be raised to weaning and

then sold, partly as young bulls (feeder cattle) and a small proportion will be raised

to mature bulls. A small number of mature bulls are used as straw-producing males

for artificial insemination. The model considers mortality rate, male/female birth

ratio, birth rate, fraction of male calf sales, fraction of young bull sales and delay

time.

The primary commodity production activity (dairy cows) in the national milk

production submodel is to produce milk production. In this research model, national milk

availability is one of the main goals of the national milk availability model. The parent

population and its productivity will determine the amount of milk production produced.

The level of milk productivity, in addition to being influenced by the quality of the

seedlings, is modeled to be influenced by the effect of feed adequacy in quantity and

quality. Farmers in this submodel cultivate dairy cows including milking until they are

deposited in milk cooperatives. Almost all milk from the cooperative will be sold to milk

processing companies (IPS). Some milk production is also sold to the informal sector,

including sales in restaurants, hotels, restaurants, and some are sold directly to consumers.

A small portion of milk from the informal sector is sourced from private milk collectors

who partner with farmers.

In the national milk production submodel, the output that will be generated is

national milk production and farmer profits. This model is also built with the aim of

knowing the impact of policy interventions on the milk availability model on the profits

received by farmers. The components that determine profit are the total revenue received

by farmers and the total costs that farmers must incur in milk production. Total production

costs are modeled as coming from forage production costs, concentrate costs, drug and

vitamin costs, labor costs, IB costs, milk collection costs, and other costs. Total revenue

comes from fresh milk sales, cull cow sales, male calf sales, young male sales, male

seedling sales and manure sales. Revenue from milk sales will depend on the farm gate

milk price which is determined by the domestic milk price and milk quality. The flow

diagram of the stock and flow submodel of national milk production built in this study can

be seen in Figure 4.3.

2) Import-Export Submodel

The import-export submodel in this study is modeled in 3 scopes, namely: (a) milk

imports and exports; (b) domestic and world milk prices and import tariffs; and (c)

downstream dairy industry activities related to national milk production and milk imports

to meet demand. Milk imports and national milk production minus exports are the main

components that determine national milk supply. In this submodel, national milk

production is compared to milk demand, which will obtain the percentage share of

domestic milk production. On the other hand, milk import tariffs will have an impact on

the large difference in milk prices that must be paid by importing/IPS companies with

domestic milk prices. The price of imported dairy products and dairy products produced by

domestic companies is also a determining factor for the development of the dairy

agribusiness system in Indonesia. Milk imports and exports in world trade use world

prices, so the exchange rate is a factor that determines the domestic milk price. Based on

domestic prices, an approach can be taken to determine the retail price of milk both at the

farm level and at the consumer level.

In the dairy industry, there are three main activities, namely distribution, processing

and marketing. Dairy cooperatives play a major role in the distribution of milk from milk

producers (farmers) to the IPS. Lack of milk raw materials for processing, IPS and

importers will import milk raw materials. The milk raw materials will undergo processing

in accordance with market demand. Processed milk that has been packaged, will be

marketed to distributors. Milk marketing distribution passes through distributor agents

(wholesalers) and then marketed through to consumers through hypermarket retailers,

minimarkets, traders, and retailers. The detailed import-export submodel stock and flow

diagram can be seen in Figure 4.4.

The mathematical equations in the import-export submodel that causally connect the

variables are:

1. Milk Import (t) = Milk Import Init (t-dt) - (Import Rate)*dt

2. Milk Export (t) = Milk Export Init (t-dt) + (Export Rate)*dt

3. Processor and Importer Stocks (t) = Init Processor and Importer Stocks (t-dt) + (IPS

Processed Milk Production)*dt + (Imported Desired Dairy Products)*dt

4. Distributor Company Ending Stock (t) = Distributor Company Ending Stock (t-dt) +

(IPS Shipments to Distributors)*dt - (Distributor Shipments to Retailers)*dt

5. Retailer Ending Stock (t) = Retailer Ending Stock Init (t-dt) + (Distributor Shipments

to Retailer)*dt - (Dairy Products Sold)*dt

6. Desired Consumer Demand (t) = Desired Consumer Demand Init (t-dt) + (Change in

Consumer Milk Demand)*dt

7. National Milk Availability Balance = Domestic Milk Availability- National Milk

Demand

8. Percentage of National Milk Availability = (National Milk Production/National Milk

Demand)*100

9. Domestic Milk Availability = National Milk Production+Dairy Imports-Dairy Exports

10. Import Rate = (Milk Imports*Import Growth)+(Import Tariff Elasticity*Dairy

Imports)+(World Price Elasticity*Dairy Imports)

Conclusion:

1. Indonesia's dairy cattle population and milk production are concentrated in Java,

including East Java, Central Java and West Java. The national dairy cattle population

and milk production in the existing conditions are growing positively but have not

been able to keep up with the growth rate of milk consumption.

2. The occurrence of excess demand causes Indonesia to still be an importer of dairy

products. Dairy imports to Indonesia m o s t l y come from New Zealand, the United

States and Australia.

3. The variables of parent population, milk production, productivity, import tariff,

domestic milk price, imported milk price, import volume, exchange rate, per capita

milk consumption, population, and income are the key variables in the model. The

estimated key variables are used in the design and development of the milk

availability model with a dynamic system approach.

4. In the base condition, although domestic milk production, share of domestic milk

production and profit increased positively, the deficit of milk availability continued

to increase at a rate of 4.06%/year. Therefore, there needs to be a policy to accelerate

the availability of milk in terms of production and other supporting institutions.

5. Without the intervention of policy scenarios, the baseline share of domestic milk

production of 27.64% in 2045 is still far from the target share of domestic milk

production to demand of 60% in the Indonesian dairy blueprint.

6. The scenario of increasing the supply of mother cows and rearing program and the

scenario of increasing conception rate each have a positive impact on the dairy cattle

population, the share of domestic milk production to demand, and the cumulative

profit of farmers. On the other hand, both scenarios have a positive impact on

reducing the milk availability deficit.

7. The scenario of increasing milk consumption results in a decrease in the share of

domestic milk production and an increase in the milk availability deficit, but the

cumulative profit is relatively the same as the baseline. The import tariff scenario has

an impact on increasing the share of domestic milk production and increasing

cumulative profits. On the other hand, the implementation of the import tariff

scenario results in a decrease in import volume, resulting in an increase in milk

availability deficit.

8. The results of the sensitivity analysis show that the rate of milk consumption is most

responsive to a decrease in the availability balance and a decrease in the share of

domestic milk production, while the supply of mother cows is most responsive to an

increase in profit.

9. The optimistic policies of scenario 7 through increased supply of mother cows and

rearing programs, increased conception rate, increased milk consumption, and

import tariffs are jointly the best in leveraging an increased share of domestic milk

production, decreased milk availability deficit and cumulative increase in farmer

profits.

10. The scenario of increasing import tariffs needs to consider international trade

rules. As a second base policy, the optimistic policy of scenario 6 through

increased supply of mother cows and rearing programs, increased conception

rate and increased milk consumption is an alternative policy that is able to

increase the share of domestic milk production to demand, decrease the deficit

of milk availability, and increase the cumulative profit of farmers.

AGB 100_ASU_ASSIGNMENT 2024_MILK AVAILABILITY MODEL TO SUPPORT THE DEVELOPMENT OF DAIRY CATTLE AGRIBUSINESS SYSTEM

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