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THE INFLUENCE OF FINANCIAL INSTITUTIONS ON THE GROWTH
OF MICRO AND SMALL AGRIBUSINESS INDUSTRIES
Introduction:
Financial institutions provide facilities and products to increase the accessibility of
capital for micro and small industries. Financial institutions are all bodies that engage in
financial activities in terms of channeling and collecting funds to the public (Anshori 2019).
In this case, financial institutions provide capital accessibility so that businesses have the
availability of funds to buy production inputs such as raw materials, machinery, and labor so
that they are able to turn business cash flow. This provides a role for financial institutions as
mediators for parties with excess funds with parties who need financing, including businesses
in micro and small industries (IMK).
Financial institutions are divided into two types, namely, banks and non-banks
(cooperatives, pawnshops, and others). The fundamental difference between the two types is
how to collect and distribute funds. In banks, funds can be deposited directly in the form of
savings, deposits, and current accounts and indirectly in the form of credit/loans from other
institutions and securities. Meanwhile, non-bank financial institutions collect funds indirectly
from the public. In addition, the purpose of channeling funds to banks is broader, namely for
working capital, consumption, and investment in business entities and individuals in the short,
medium and long term. Meanwhile, the distribution of funds at non-bank financial institutions
focuses more on investment activities in business actors in the medium and long term
(Caroline et al. 2021).
Bank and non-bank financial institutions experience fluctuations in the number of units
from year to year. Table 1 shows the number of units of several bank financial institutions,
namely Commercial Banks and Rural Banks (BPR) and non-bank financial institutions
incorporated as cooperatives. Non-bank financial institutions, namely cooperatives, have the
largest number of units among other financial institutions. This is because non-bank financial
institutions are more inclusive, faster, and easier to obtain credit by every category of society,
especially for business actors in IMK. In addition, the role of financial institutions as
providers of capital accessibility through credit for businesses is more widely utilized through
non-bank financial institutions because they do not require collateral and the credit
requirements provided are easier to meet than bank financial institutions, especially by
businesses in IMK.
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The micro and small industry (IMK) consists of various micro and small enterprises
(MSEs). The most common grouping of businesses is micro, small and medium enterprises
(MSMEs) and large enterprises, so MSEs are included in MSMEs. However, micro and small
enterprises have the largest percentage of businesses compared to medium-sized enterprises.
Data from the Ministry of Cooperatives and SMEs of the Republic of Indonesia (2021) shows
that there were 63,955,368 micro business units in Indonesia in 2021. This number is
equivalent to 99.62% of the total MSMEs in Indonesia. Meanwhile, small businesses
amounted to 193,959 business units in 2021 or equivalent to 0.3% of the total MSMEs in
Indonesia in that year. Meanwhile, medium-sized enterprises amounted to 44,728 units or
0.06% of the total MSMEs in Indonesia in 2021. With the dominance of numbers, MSEs have
a major contribution to the role of MSMEs in the economic and social fields.
The significant role of MSMEs can be seen in their contribution to the Indonesian
economy. MSMEs have contributed to the increase in national nominal and real gross
domestic product (GDP), which is one of the indicators to show the condition of a country's
economy. GDP shows the total added value of all economic activities of business units in the
country (Ministry of Cooperatives and MSMEs, 2021). Nominal GDP measures the value of
goods or services based on current prices. Meanwhile, real GDP measures the value of goods
or services based on the base year. Based on data from the Ministry of Cooperatives and
MSMEs (2021), MSMEs contribute 60.5% to the total national GDP. In addition, the total
investment of national MSMEs also reached 60% of the total investment activities carried out.
The increasing number of MSMEs has implications for increasing employment. Labor-
intensive MSMEs are an important factor in the absorption of the labor force due to the
potential growth of a large percentage of employment opportunities (Tambunan 2021). Data
from the Ministry of Cooperatives and MSMEs (2021) shows that there are 119.6 million
workers distributed in MSMEs. This number is equivalent to 96.92% of the total workforce in
Indonesia. This has implications for the equal distribution of community income due to the
absorption of a high enough workforce so that people's welfare also increases.
Export activities carried out by micro and small industries continue to increase. Data
from the Asian Development Bank (2021) shows fluctuations in the value of exports carried
out by MSMEs in Indonesia, where the total value of MSME exports is higher than the total
imports. Figure 1 shows the total exports and imports of MSMEs from 2015-2019. In 2019,
the value of MSME exports amounting to Rp399 trillion, which increased by 15.31% from the
previous year. The export value of MSMEs in 2019 also had a percentage contribution to
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Indonesia's total exports of 13.94%.
The existence of businesses in micro and small industries is spread across all regions in
Indonesia, including villages and isolated areas (Tambunan 2021). Micro and small industries
grow in villages to become one of the driving sources of the village economy. This is because
IMK expands employment opportunities so that equal distribution of income for rural
communities can be achieved. The significance of the role of IMK in the progress of the rural
economy makes the growth of IMK in the village one of the focuses of regional development.
The growth of IMK agribusiness can be seen from the relative increase of its business assets
either in terms of the number of units that increase or the increase in business scale (Neneh et
al. 2014). This study uses the number of business units as a variable used to see the growth of
agribusiness IMK.
Agribusiness covers business processes from upstream to downstream. Agribusiness is a
new paradigm in economic development based on agriculture with the main elements of
agribusiness development including businesses on a micro, small, medium and large scale
(Saragih 2018). In this case, agribusiness includes upstream, on-farm, and downstream
subsystems that are interconnected and supported by various agroindustries, inputs,
supporting services, and marketing so that many micro and small industries grow in it,
especially in the downstream subsystem. Food and non-food are the two main groupings in
agribusiness IMK. This is because 60% of IMKs are engaged in the food agribusiness IMK
category and the rest in the non-food category (Ministry of Cooperatives and SMEs of the
Republic of Indonesia 2021).
The distribution of loans to food and non-food agribusiness IMKs can be seen from
several business field groupings conducted by Bank Indonesia. Food agribusiness IMKs are
mostly engaged in the agriculture, forestry and fisheries business field categories; as well as
the provision of accommodation and eating and drinking. Non-food agribusiness IMKs are
mostly spread across field categories wholesale and retail trade, car and motorcycle repair.
Table 2 shows the distribution of loans from rural banks to each business sector. Table 2
shows different percentages of business sectors with dominance in food and non-food
agribusiness IMKs. For this reason, further studies on agribusiness IMK can be conducted
based on food and non-food groupings.
The crucial role of micro and small agribusiness industries in economic and social
aspects needs to be supported by good capital accessibility through financial institutions.
Research by Susanti et al. (2013), Indriyatni (2013), and Abrara et al. (2017) show that
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financial institutions are one of the factors in the growth of micro and small industries through
loans provided. However, financial institutions have not had a significant impact because
there is still a high percentage of MSMEs that have not been able to access credit in 2022 of
74% (Novita 2022). Therefore, studies on the influence of financial institutions, both banks and
non-banks, on the growth of MSMEs based on the number of units in the food and non-food
groups need to be investigated further.
1.1. Problem Formulation
Limited capital is one of the factors inhibiting the growth of micro and small industries.
Enterprises in the micro and small industry have a greater chance of facing credit constraints
from formal sources than medium-sized enterprises. There are 45 million MSMEs in the ultra-
micro segment that require capital assistance by 2022. However, only 15 million MSMEs that
can be served in formal financial institutions and the rest have not been able to access capital
(Syahrizal 2022). This is because businesses in micro and small industries (MSMEs) lack
valuable assets for collateral and financial records to achieve higher levels of productivity and
global competitiveness (Tambunan 2021). Limited access to finance leads to a lack of
resources to purchase production inputs such as new machinery, expand business networks,
hire trained employees, and innovate (Jinjirak and Wignaraja 2016).
The accessibility of micro and small industries (MSMEs) in accessing credit from bank
financial institutions is lower than that of medium-sized industries. MSMEs, which mostly
consist of micro and small enterprises, only obtain one-sixth of the national credit share
(Darwin 2018). This is because access to financial institutions, especially banks, for micro
and small enterprises is not easy and there is a lack of information regarding business
financing through financial institutions through credit. MSMEs mostly access capital from
non-bank financial institutions because not all MSMEs can access banks (bankable) and have
not been reached by banks (Nur et al. 2020). Figure 2 shows the credit position of MSMEs
based on business scale.
Figure 2 shows that micro and small businesses have a lower credit position than
medium-sized businesses. Bank Indonesia data (2021) shows that the October 2021 MSME
credit position in micro businesses amounted to IDR 228 Trillion (decreased -0.0758% YoY);
small businesses amounted to IDR 424 Trillion (increased 0.2021% YoY); and medium
businesses IDR 474 Trillion (decreased -0.0345% YoY). This was partly due to IMK relying
more on savings than credit. This is because IMKs operate in the informal sector, are not well
organized and managed, and are run by households that do not have enough assets as
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collateral.
Micro and small enterprises face various barriers to business growth. Suryajaya et al.
(2014) mentioned in their research that there are five factors that are the main obstacles to the
growth of formal sector micro and small enterprises in East Java, namely finance, location,
competition, labor, networks, and economy and technology. In the financial factor, the most
Many respondents felt that high credit interest rates from financial institutions for businesses
in the formal sector. Meanwhile, the difference in obstacles in micro and small enterprises in
the informal sector is the low optimization of government financial assistance to businesses in
this sector. Food and non-food agribusiness IMK are the two main categorizations of
agribusiness IMK. The two groupings have different characteristics in terms of capital
management for production purposes, post-production product handling, asset security
ownership, and others. The differences in these characteristics have implications for the
differences in accessibility of bank-sourced capital.
Various studies have been conducted to analyze the influence of financial institutions on
the growth of micro and small agribusiness enterprises. Research conducted by Osoro et al.
(2013) on micro and small enterprises in Kenya showed the provision of credit and training as
well as savings accounts provided by microfinance institutions can help the growth of MSEs.
Similar research was conducted by Bongomin et al. (2017) in Jinja and Iganda market centers
showed that access to financing has a significant positive effect on the growth of MSEs.
Different results were found by Hilmawati et al. (2021) who examined the effect of financial
inclusion on MSME performance. Good financial inclusion is characterized by MSMEs that
know, understand, and can access financial services, one of which is financial institutions.
The results showed that there was no significant effect of financial inclusion on the
performance and sustainability of MSMEs.
1.1 Factors Affecting Business Growth in Agribusiness Micro and Small Industries
Business growth in agribusiness micro and small industries (IMK) is one of the main
focuses in regional development because of its significant role in the economy and social
community. Business growth can be seen from the workforce, domestic investment, non-oil and
gas export value, number of business units, contribution to GDP, and business productivity
(Simatupang et al. 2019). Hapsari et al. (2014) in their research measured the growth of small
and medium enterprises by looking at SME capital, employment, number of SMEs, and
profits earned by SMEs. The same thing was also done in Firmansyah's research (2018) where
the growth of micro, small and medium enterprises was measured through the percentage
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increase in the number of business units. Osoro et al. (2013) in his research used business
growth variables by looking at the increase in sales volume and profits. The results showed
that 50% of respondents agreed that credit was the main factor in supporting business growth.
The growth of agribusiness IMK can be influenced by various factors. Research by
Abara et al. (2017) on IMK in Ethiopia showed that financial institutions contribute to the
growth of micro and small enterprises. A significant positive effect was found on loans from
financial institutions on the growth of IMK, although the contribution was very low. Research
by Susanti et al. (2013) with the object of Pekalongan batik cluster research shows several
factors that influence business growth, namely, the existence of supporting industries,
competition and strategic steps taken by businesses, as well as the role of government in the
form of business support programs. Indriyatni's research (2013) shows that the factors of
working capital, ability/skill, and business location have a significant positive effect on the
success of micro and small business operations. Government support factors, especially in
business licensing, coaching, and assistance, as well as infrastructure development (especially
product marketing) are also supporting factors for increasing business growth in IMK.
External factors that influence the growth of micro and small enterprises are shown by
research conducted by Ferejo et al. (2022) with the object of IMK research in Ethiopia. The
study shows that infrastructure access, workplace, government policy and market linkages are
factors that have a significant effect on the growth of IMK. IMK with good infrastructure
accessibility grows faster than IMK with limited infrastructure access. Access to finance will
relate to the smooth operation of the business through the capital owned. Similar results were
also found in the research of Cahyanti et al. (2017) in the processing industry of Malang City
showed that there are several factors that influence business growth, namely, the quality of
infrastructure and regulations, financial management systems, product production systems,
quality of human resources, marketing strategies, and partnership systems.
Barriers to business growth in agribusiness IMK can be caused by the limitations of
business actors and the surrounding environment. Barriers to the growth of textile IMK in
Eldoret are shown from the results of research by Mbugua et al.(2013). The study concluded
that insufficient cash, poor business management, marketing and poor entrepreneurial
attributes have a significant effect on inhibiting business growth. Similar research was also
conducted by Sherazi et al. (2013) in Pakistan mentioned the five biggest obstacles faced by
business actors in the micro and small industries, namely financial, corruption, social and
technological factors, and management skills.
The research that has been done shows that the growth of micro and small industries can
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be measured through several things, namely, the number of business units, IMK labor
absorption, IMK capital, profits earned, domestic investment, non-oil export value, business
productivity, and contribution to GDP. Factors that influence business can come from internal
and external factors. Internal factors include the entrepreneurial ability of business actors,
working capital, and business location. External factors include the presence of supporting
industries such as financial institutions, strategic steps taken by businesses, access to
infrastructure, government policies, and market linkages. Thus, this study uses the variable
number of business units to see business growth influenced by financial institutions as an
external factor. The scope of this study is broader with a unit of analysis of villages
throughout Indonesia, while previous studies focused more on one or several regions.
1.2 The Effect of Financial Institutions on Business Growth
Financial institutions provide accessibility to capital for business actors. Capital
accessibility allows businesses to have sufficient funds to purchase production inputs such as
raw materials, production equipment (machinery), and labor. Through the provision of capital
provided by financial institutions, businesses can streamline production and earn more profits
so that businesses can grow through the provision of capital by financial institutions in the
form of credit. The availability of external finance has a positive effect on increasing
entrepreneurship, firm development, and dynamics and innovation (Utami et al. 2020).
The role of financial institutions as a source of external capital has an impact on
business growth. Research by Anggraini (2013) with the object of MSME research in Medan
City shows the results that there is a positive influence of KUR (Kredit Usaha Rakyat) on the
increase in income of MSME entrepreneurs. Gandhiar's research (2013) supports this, where
the development of micro and small businesses can occur when business actors get working
capital loans from BPRs. This can be seen from the turnover obtained, the number of
consumers, and the net income that increases when using BPR credit. Similar research was
also conducted by Simatupang et al. (2019) on MSMEs in Bekasi city which shows that MFI
(Microfinance Institution) financing has a positive impact on the development of MSMEs.
However, research conducted by Hilmawati et al. (2021) shows that there is no significant
effect of financial inclusion on the performance and sustainability of MSMEs.
Microfinance increases the inclusiveness of access to financial institutions for
businesses in the micro and small industries. Business characteristics such as age of the
business, type of business, and capital ownership of business actors determine accessibility
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capitalization of a business (Diana 2019). Research by Wedelia et al. (2017) supports this,
which found a positive influence between asset ownership, education level, and the position
of business actors on formal financing in Bogor Regency. The results also explain that not all
businesses in the food industry have the same accessibility to formal financing, but businesses
with asset ownership greater than 50 million have higher accessibility to capital financing.
Research conducted by Nkansah et al. (2023) on IMKs in Ghana found that there are six
factors that hinder IMKs' access to finance, namely collateral, bank loan requirements, high
transaction costs, inadequate information, bank profit orientation, and short repayment
periods. These barriers arise due to small business size, lack of assets and capital, and lack of
capacity to meet the requirements of financial institutions. Therefore, microfinance
institutions are needed as a solution to these barriers, one of which is Ultra Microfinance
(UMi) provided by the Indonesian government.
The research that has been conducted shows varied or inconsistent results in measuring
the influence of financial institutions on business growth. Therefore, further studies on the
effect of financial institutions on business growth are still needed. This study also looks at the
influence of financial institutions based on the number of units in each village throughout
Indonesia, while previous studies focused more on the amount of credit provided and were
limited to one area.
3.1 Theoretical Framework
The results of this study are organized and based on concepts or theories related to
business financing in micro and small agribusiness industries that support this research. For
this reason, the following is the theoretical framework of this research.
3.3.1 Theory of Business Growth
Business growth in the micro and small industry (IMK) is shown through the percentage
change in total assets of the current period with the previous one. Business growth can also
show the level of business profitability between periods. Increased company assets can be
seen from the growth in the number of business units or the increase in business scale (from
micro to small businesses; from small businesses to medium businesses; from medium
businesses to large businesses). By knowing business growth through the relative increase in
business assets in business, business actors can have security guarantees to obtain external
financing that can be used to encourage business growth (Neneh et al. 2014). In this study, the
number of business units is the variable used to see the growth of agribusiness IMK.
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The pattern of business development in micro and small industries is explained through
"classical" and "modern" economic growth theories, especially in developing or low-income
countries (Tambunan 2021). In the classical theory, the number of businesses in micro and
small industries (MSEs) will decrease as income or economic growth increases. This theory
explains that the economy will be dominated by large businesses or the growth of IMK is
negatively correlated with economic development or growth rate. Meanwhile, the modern
theory explains that IMK will become more important in the economy or IMK growth is
positively correlated with people's income levels.
Public welfare is one of the indicators of economic growth. State policy in the economy
focuses on solving poverty, unemployment, income distribution inequality, and population
growth (Hamdani 2020). In this case, micro and small industries are one of the things that are
empowered to increase their role. This is because micro and small industries can help improve
people's welfare through increasing employment and equalizing income distribution,
especially in micro and small agribusiness industries that have a business scope from
upstream to downstream. Kusnandar (2012) in Hamdani (2020) says that the contribution of
micro and small businesses can be seen from several macro-scale indicators such as their
contribution to increasing per capita income, the formation of GRDP, and the regional
economy.
Business growth in IMK is one of the main focuses in regional development in the
regions. The Ministry of Cooperatives and SMEs measures the development of MSMEs based
on six aspects, namely, labor, domestic investment, non-oil and gas export value, number of
business units, contribution to GDP, and productivity per labor and per business unit. The
growth of IMK can also be seen from the utilization of IMK in a region. Indicators The
success used in the utilization of IMK in the region, especially villages, was conveyed by
Sumodiningrat (1999) in Hapsari et al. (2014), namely, increased community income,
increased welfare of poor families through increased businesses established, and increased
group independence through developed group productive businesses. From these indicators,
the growth of IMK can also be seen from the number of businesses, profits or profits earned
by businesses, employment, and business capital. This study measures business growth in
agribusiness micro and small industries (IMK) based on the growth of the number of business
units.
3.3.2 Business Growth Factors:
Business growth is influenced by various internal and external factors. FDRE (2011) in
Ferejo et al. (2022) divides these factors into internal and external factors. Internal factors
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consist of entrepreneurial characteristics, managerial capacity, and marketing capability.
Entrepreneurial characteristics in this context focus on the entrepreneur's educational
background, family, entrepreneurial intention, and entrepreneurial ability. Furthermore,
managerial capacity in this case is team management to achieve business success. Sidika
(2012) defines management capacity as a set of knowledge, skills and competencies that can
help small businesses become more efficient. Lack of management capability in IMK will be
an obstacle to growth (Olawale et al. 2010). Finally, product marketing capability is the most
important factor as it relates to achieving market targets from product sales.
External factors of business growth consist of access to finance,
environment/workplace, infrastructure, marketing competition, and the quality of human
resources. Lack of external financing can be an obstacle or even a failure in the growth of
IMKs. In this case, micro and small enterprises need assistance to increase the accessibility of
capital for daily fund turnover. Increased accessibility to capital is obtained from financial
institutions as a source of business credit. Furthermore, access to a good working environment
will support easy access to resources and markets. Access to infrastructure is particularly
important for micro and small enterprises located in villages or areas far from markets. Some
IMKs are located in areas with poor economic infrastructure such as no water and electricity,
poor transportation and telecommunication systems, and poor sanitation services. With
limited access, the cost of production per unit will be higher. Finally, public policy,
competition and human resources can be improved through programs provided by the
government, either in the form of training or mentoring. This study will measure the external
factors of IMK agribusiness growth, namely access to finance through the number of financial
institutions.
3.3.3 Characteristics of Financial Institutions
Financial institutions are financial companies with a focus on activities that channel
funds and raise funds. Financial institutions financial economic activities with main assets in
the form of financial assets and claims in the form of bonds, loans, and shares. Financial
institutions provide facilities and products in the form of financial accessibility and can turn
the flow of money in the economy. These facilities provide a large role for the institution as a
mediator or liaison for people with excess funds with people who need funds through credit.
For this reason, financial institutions are also often referred to as financial intermediaries
because they have the main function of connecting surplus and deficit parties.
Financial institutions have five main activities, namely asset transfer, liquidity, income
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allocation, transactions, and efficiency (Muchtar et al. 2016). First, asset transfer activities are
carried out by flowing "liquid" assets from surplus units (lenders) to deficit units (borrowers).
In addition, the transfer of assets can also be done in the form of financial institutions issuing
secondary securities such as pension funds, time deposits, demand deposits, and so on which
are purchased by parties who have excess funds and exchanged for primary securities
(commercial paper, bonds, stocks, and others) issued by parties who need funds. Second, the
liquidity activities that banks carry out serve to manage funds in accordance with the needs
and interests of those who have surplus liquidity. Third, income relocation activities are
carried out to store surplus funds in the form of secondary securities issued by financial
institutions, namely savings, insurance policies or shares, deposits, pension plans so that
assets owned by surplus units will be more liquid with a relatively very small risk of loss.
Fourth, financial institutions carry out transaction activities for goods and services. Finally,
efficiency is carried out by financial institutions to avoid incentive problems that occur due to
information that is not well conveyed between borrowers and users of capital.
Financial institutions are divided into two types, namely banks and non-banks. Bank
financial institutions are divided into several types such as central banks, commercial banks,
and rural banks. The central bank has the task of supervising national banking so that it does
not perform functions such as banking in general such as raising funds and providing credit.
The central bank in Indonesia is Bank Indonesia. Commercial banks have a business that is
run conventionally / sharia with its main activities are raising funds, providing credit, and
providing services in facilitating payment activities through the services provided (mobile
banking, electronic money, and others). Finally, people's credit banks (BPR) also run
conventional/sharia activities but may not provide services in payment traffic. Banks can also
serve as agents of development in the community economy. This is because banks can be
financial institutions that can increase investment activities, consumption, and sales of
goods/services in the community.
Non-bank financial institutions are an entity that has the main activity to raise funds
from the public in the form of securities and channel funds to the public in the form of loans
that can be used for business financing (Syafril 2020). Institutions Non-bank finance has
various types including pawnshops, capital markets, cooperatives, money markets, financial
technology, pension funds, insurance companies, factoring companies, and others (Labetubun
et al. 2021). One of the cooperatives that is engaged in increasing the accessibility of capital
for micro and small industries, especially in rural areas, is a savings and loan
cooperative/Kospin that provides capital loans to its members.
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The difference between bank and non-bank financial institutions can be seen from the
process of collecting and distributing funds (Muchtar et al. 2016). Banks can raise funds
directly (demand deposits, deposits, and savings) and indirectly (loans/credits from other
institutions and securities) in the community. Meanwhile, funds in non-bank financial
institutions can only be raised indirectly from the public (mainly through loans/credits from
other institutions or securities). The distribution of funds in banks is intended for investment,
consumption, and working capital which is given to individuals and business entities for the
short, medium, and long term. Meanwhile, non-bank financial institutions usually channel
funds for investment activities to business entities with medium and long terms.
Financial institutions provide accessibility to capital for businesses through credit.
According to the Banking Law, credit is the provision of money or bills that can be equated
with it, based on an agreement or borrowing agreement between a bank and another party that
requires the borrower to pay off the money after a certain period of time with interest. In
providing loans to customers, banks hold the 5C and 7P principles as a consideration for
approving loans (Syafril 2020). 5C consists of Character (payment behavior and risk profile
of default by the debtor), Capacity (the ability of the prospective debtor to pay obligations),
Capital (net worth of the prospective debtor), Collateral (collateral provided), and Condition
(estimates of the prospective debtor's ability to fulfill obligations according to industry
conditions, general economic conditions, and others that affect the ability to pay obligations).
Furthermore, the 7P analysis principle is also used by looking at the payment, prospect, party,
personality, purpose, profitability, and protection of the prospective debtor. In this study, the
analysis will be conducted by looking at the influence of bank and non-bank financial
institutions on the number of agribusiness IMKs so that the results obtained are more
comprehensive.
3.3.4 Micro and Small Industry Agribusiness
Industry is the process of converting raw goods into semi-finished or finished goods. In
economic activities, a business can be categorized as an industrial business when in the
business process there are economic activities that aim to produce goods or services and are
located in a certain location and have administrative records. Businesses in the industry can be
divided into three categories based on business scale, namely micro, small and medium.
Based on Government Regulation Number 7 of 2021, businesses are classified as follows:
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a) Micro Enterprises have a business capital of up to a maximum of Rp1,000,000,000.00
(one billion rupiah) excluding land and building of the business premises; Micro
Enterprises have an annual sales revenue of up to a maximum of Rp2,000,000,000.00
(two billion rupiah);
b) Small Businesses have a business capital of more than Rp1,000,000,000.00 (one billion
rupiah) up to a maximum of Rp5,000,000,000.00 (five billion rupiah) excluding land and
buildings of the place of business; Small Businesses have annual sales revenue of more
than Rp2,000,000,000.00 (two billion rupiah) up to a maximum of Rp15,000,000,000.00
(fifteen billion rupiah); and
c) Medium-sized Enterprises have a business capital of more than Rp5,000,000,000.00 (lina
billion rupiah) up to a maximum of Rp10,000,000,000.00 (ten billion rupiah) excluding
land and buildings of the place of business; Medium-sized Enterprises have annual sales
revenue of more than Rp15,000,000,000.00 (fifteen billion rupiah) up to a maximum of
Rp50,000,000,000.00 (fifty billion rupiah).
Agribusiness covers business activities from upstream to downstream. Davis et al.
(1975) in Krisnamurthi (2020) stated that agribusiness is the entirety of operational activities
concerning farming, processing, storage, distribution, and manufacturing of agricultural inputs
and other products produced. Harling (1995) in Krisnamurthi (2020) states that agribusiness is
an activity that includes the provision of agricultural production facilities such as seeds, tools
and machinery, as well as fertilizers, production, and distribution of products from upstream
to downstream. Based on this definition, agribusiness can be interpreted as a system of a
series of businesses (businesses) ranging from the procurement of agricultural production
facilities, sorting businesses, farming, post-harvest businesses, packaging and storage of
agricultural products; agricultural product processing industry businesses in a broad sense and
various businesses delivering agricultural (based) products to consumers; as well as a number
of supporting activities such as government institutions that issue related policies and
regulations, information service institutions, and financing service institutions. The
agribusiness subsystems are described in Figure 3.
Agribusiness emphasizes the business aspect and its business actors (Krisnamurthi
2020). This means that agribusiness activities will consist of one or many businesses with
organizational management that focuses on increasing the added value of a product by
producing goods or services needed by the market. The broad scope of agribusiness makes
many businesses in the micro and small industries develop in it. The most common
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agribusiness groups are food and non-food. Industries in the food group include everything
that comes from biological sources of plantation products, forestry, agriculture, fisheries and
water, waters, and livestock both processed and unprocessed. The non-food group includes
the cultivation of non-crops such as livestock, fish, and plants that are not for food as well as
agricultural and livestock services. In this study, food and non-food agribusiness IMKs are the
limitations of the objects to be studied.
3.2 Operational Framework
Agribusiness consists of four subsystems, namely upstream, farming, downstream, and
institutional supporting activities that are correlated with each other. The broad scope of
agribusiness makes many micro and small business units develop in it, which are referred to
as agribusiness micro and small industries (IMK). IMK Agribusiness has an important role in
improving the economy and the welfare of the community, starting from the expansion of
employment, labor absorption, equal distribution of income, and others. This important role
makes IMK an industrial sector that is targeted to have high growth in the number of business
units because it will be positively correlated with Indonesia's economic growth. In this case,
the growth of agribusiness IMK focuses on the growth of the number of business units.
IMK agribusiness is divided into two main groups, namely food and non-food. Both
groups have different business characteristics in terms of post-production product handling,
product expiry, and others. This has led to different capital management for the two groups.
Food agribusiness IMKs tend to have faster capital turnover than non-food agribusiness IMKs
due to the nature of their products which have a fast expiry period. This causes food
agribusiness IMKs to require capital so that current cash flow can continue to exist for
production activities carried out in a short period. Meanwhile, non-food agribusiness IMKs
tend to have longer production periods than food IMKs so that the turnover of cash flow
(capital) into profits is longer. This causes the industry to need financial institutions so that
production activities run smoothly even though the receipt of profits does not always occur in
a short time. For this reason, this study analyzes agribusiness IMKs based on their groups,
namely food agribusiness IMKs and non-food agribusiness IMKs.
Agribusiness IMK is included in the downstream subsystem because it consists of
various processing industry sectors. To support the growth of IMK, institutional subsystems
and supporting activities such as financial institutions and supporting infrastructure are
required. Financial institutions are needed to improve the accessibility of business capital.
With optimal credit utilization, capital accessibility can increase so that businesses have the
15
availability of funds to purchase production inputs (inputs, raw materials, production
equipment, labor). This is one of the stimuli in increasing entrepreneurial motivation for
prospective entrepreneurs. Financial institutions are divided into two types, namely, bank and
non-bank financial institutions. Both types of financial institutions have differences in terms
of function and how to raise funds. For this reason, this study divides financial institutions
into two types, namely bank and non-bank financial institutions represented by the number of
savings and loan cooperatives, the existence of pawnshops, and the existence of Baitul Maal
Wa Tamwil (BMT).
The availability of supporting infrastructure will increase entrepreneurial motivation
because it supports company operations, especially product distribution. The level of
readiness of supporting infrastructure can be seen from the electricity index, infrastructure and
distribution index, and telecommunications and information index. IMK areas or locations are
mostly in rural areas so that poor infrastructure will be an obstacle for IMK businesses.
Infrastructure equality that has an imbalance between Java and outside Java is also one of the
things that can affect the motivation to open a business in the region. Therefore, this study
analyzes the influence of financial institutions on IMK agribusiness based on the location of
the IMK, namely Java or outside Java. The relationship of each variable that affects the
growth of micro and small agribusiness industries is shown in Figure 4.
Increased entrepreneurial motivation will have implications for the emergence of new
business units in IMK Agribusiness. The increase in the number of business units will be a
reference to the growth of IMK Agribusiness in Indonesia. Based on this description, this
study focuses on the effect of financial institutions on the growth of food and non-food
agribusiness micro and small industries in Indonesia. The hypothesis of this study is that the
number of bank financial institutions, the number of savings and loan cooperatives/cospin, the
existence of pawnshops, the existence of baitul maal wa tamwil/BMT, the electricity index,
the infrastructure and distribution index, the telecommunications and information index have
a significant positive effect on the number of micro and small industries of food and non-food
agribusiness.
4.1 Data Analysis Method
This study analyzes the effect of financial institutions as measured by the variable
number of bank and non-bank financial institutions on the growth of micro and small
agribusiness industries in Indonesia in the food and non-food industry groups. The division
16
and unification of regions that occurred caused the number of villages censused to be not the
same in 2018 and 2022. The number of villages in 2018 was 83,931 villages and in 2022 was
84,096 villages. Therefore, data cleaning was conducted so that the total number of villages
analyzed was 82,900 villages in each year. Furthermore, the data were analyzed using
descriptive analysis and panel data regression analysis. Descriptive analysis was conducted to
see the distribution and variation of the data. Panel data regression was used to estimate the
causal relationship between IMK agribusiness variables and other selected independent
variables. Data disaggregation was also done based on the type of agribusiness IMK, namely,
food and non-food, as well as region, namely, Java and outside Java. This was done to obtain
more comprehensive results from the analysis conducted.
4.1.1 Model Estimation
Panel data is a combination of time series and cross-section data. To analyze the
relationship between variables in the study, panel data regression was conducted. The
formulation of the panel data regression model in this study is based on the research
objectives and research framework. The model used in this study is a growth model of the
number of agribusiness IMK units associated with the growth of bank financial institution
units which is the accumulated number of Government Commercial Banks, Private
Commercial Banks, and Rural Banks as well as non-bank financial institutions such as the
number of Saving and Loan Cooperative (Kospin) units, the existence of Pawnshops, and the
existence of Baitul Maal Wa Tamwil (BMT).
The model is also linked to supporting infrastructure, namely the level of infrastructure
readiness through the index. The index is based on infrastructure that supports the growth of
financial institutions and agribusiness micro and small industries (IMK), namely, electricity
index, infrastructure and distribution index, and telecommunications and information index.
The index is calculated based on the infrastructure conditions in each sample compared to the
average infrastructure conditions of the entire sample by taking into account the minimum
conditions and maximum conditions of the entire sample (Rachmina 2012). The formula for
calculating the index is as follows (Ashok et al. 2006):
Infrastructure readiness in each region is represented by the electricity index,
infrastructure and distribution index, and telecommunications and information index. Table 4
shows the analysis indicators used in each index.
The electricity index of an area is said to be good when the indicator analysis of lighting
on the main road of the village/kelurahan exists in most areas and SUTET and SUTTAS are
17
available. The infrastructure and distribution index is said to be good when the type of
western road surface is asphalt/concrete, the road can be passed through year-round by 4-
wheeled vehicles or more, POS offices operate, there are mobile posts, and private
expeditions operate. The telecommunications and information index is said to be good when
there is internet, an adequate number of BTS and mobile phone communication service
operators, and very strong signal strength.
A semi-log-linear model was used in this study to normalize the data distribution and
make the interpretation more meaningful (Benoit 2011). The dependent variable in the study
was transformed in log form or called the "log-lin model" (Gujarati et al. 2015). This is done
to avoid the non-linear shape of the distribution of IMK agribusiness as the dependent
variable. The interpretation of the log-lin model is different from the linear model. This is
because statistically there is only one group of variables, namely the dependent variable
analyzed in log form so that the interpretation needs to be adjusted by multiplying the result
coefficient by 100%.
4.1.2 Panel Data Regression Test
Analysis using panel data regression shows the relationship and influence of two or
more independent variables on the dependent variable of a panel data. The panel data
regression model selection test can be done with the Lagrange Multiplier test, Chow test, and
Hausman test. The following is an explanation of the selection process of each of these tests:
4.1.3 Classical Assumption Test
The standard error used in this study is a robust standard error to overcome potential
heteroscedasticity problems that can occur, thus the estimation results are robust (Wooldridge
2009) The classical assumption test is carried out as follows
1. Multicollinearity Test
Multicollinearity test is used to see the correlation in the independent variables.
Independent variables that are correlated with each other have the potential to cause
multicollinearity problems so that the regression model built cannot be used. The VIF
(Variance Inflation Factor) value or of each variable or the tolerance value (Tolerance) is an
indicator to see multicollinearity. Regression models with a tolerance value> 0.10 or a VIF
value < 10 indicate the absence of multicollinearity and the model can be used (Ghozali
2016).
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2. Autocorrelation Test
The correlation between the confounding error in period t and the error in period t-1
(previous) is seen using the Autocorrelation test. This test uses the Runs-Test to see the
random level of residual data in the model. Autocorrelation problems occur if there is a
correlation in the model variables that arise due to the correlation between residuals or errors
as long as observations take place in a time sequence. This happens because the residuals
(confounding errors) are not free from one other observation (Ghozali 2016).
3. Normality Test
Normally distributed data is a classic assumption that must be met by the data to be
studied. The normality of data distribution can be analyzed using a normality test. The
Kolmogorov-Smirnov non-parametric statistical test is performed to determine the normality
of residuals. The assumption of normality in the data is fulfilled when the test results show the
probability exceeds the 0.05 limit or the Kolmogorov- Smirnov value with the Asymp.sig (2-
tailed) value (Ghozali 2016).
4. Heteroscedasticity Test
A good regression model is modeling that is homoscedasticity or does not occur
heteroscedasticity. Homoscedasticity is indicated by the variance of the residuals of one
observation to another observation remains the same. Heteroscedasticity occurs when the
variance value of the residuals from one observation to another is different. For this reason,
the heteroscedasticity test is used to test the inequality of variances and residuals from one
observation to another in the model (Ghozali 2016).
4.1.4 Goodness of Fit Test
The accuracy of a regression model or function in estimating is measured through the
Goodness of Fit test. Three tests can be used to see this accuracy, namely:
a. Simultaneous Significance Test (F Statistical Test)
The level of influence of all independent variables on the dependent variable in the
model is measured through the F statistical test. The hypothesis (Ho) is rejected when the
independent variables can jointly affect the dependent variable. The hypothesis (Ho) is
accepted when the independent variables do not affect the dependent variable in the model.
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This happens because the independent variables selected in the model are not the main
variables that affect the dependent variable, so it is necessary to select the variables again to
be included in the model.
b. Individual Parameter Significance Test (t Statistical Test).
The t statistical test basically shows how far the influence of one explanatory /
independent variable individually in explaining the variation in the dependent variable. The
hypothesis is intended to determine whether an independent variable has a significant effect
partially / individually on the dependent variable.
c. Coefficient of Determination (R2)
The coefficient of determination is to measure how good the regression line we have.
In this case we measure how much the proportion of variation in the dependent variable is
explained by all dependent variables (Widarjono 2013).
5.1 Overview of Agribusiness Micro and Small Industries in Indonesia
A business can be categorized as an industrial business when in its business process
there are economic activities aimed at producing goods or services and is located in a certain
location and has administrative records. The categorization of micro and small industries
(IMK) in the Village/Kelurahan Potential data collection is carried out with the criteria that
the business has a workforce of less than 20 people. Based on the data collection of
Village/Kelurahan potential (2022), agribusiness IMKs are spread throughout Indonesia with
a total of 2,177,775 industries in 2022. This number increased by 25.59% from the previous
data collection period in 2018 of 1,734,058 industries.
Agribusiness IMKs are spread across various regions in Indonesia. Table 5 shows the
distribution of agribusiness IMK by region (Java and outside Java) and group (food and non-
food) in 2022. The percentage of agribusiness IMK distributed in Java is 55.28% and outside
Java is 44.72%. There are 1,203,906 agribusiness IMK units distributed in Java with 381,339
units in the food category and 822,567 units in the non-food category. Meanwhile, the number
of agribusiness IMK units spread outside Java is 973,869 units with 390,944 units in the food
category and 582,925 units in the non-food category. This shows that Java Island has more
agribusiness IMK units than outside Java Island.
The detailed distribution of agribusiness IMKs is shown in Table 6, which presents the
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10 provinces with the largest number of agribusiness IMK units in their regions. The
provinces with the largest number of agribusiness IMKs are Central Java, East Java, West
Java, East Nusa Tenggara, West Nusa Tenggara, South Sulawesi, Bali, DI Yogyakarta, North
Sumatra, and Banten, respectively. Table 3 shows that five of the 10 provinces with the
largest number of agribusiness IMKs are located in Java, although the area of Java is smaller
than outside Java. This shows that there is still great potential for the development of
agribusiness IMKs in areas outside Java. If optimization is done, the role of IMK agribusiness
from the social aspect of increasing income equality can occur.
Agribusiness IMKs have a large diversity of types that can be divided into two main
groups, namely food and non-food. The grouping of food and non-food agribusiness IMKs is
based on the categorization of IMKs found in the Village Potential data collection. Food
agribusiness IMK consists of the food industry (milk, oil and fat, fish, meat processing and
preservation, vegetables, fruit, and others) and the food industry beverages (mineral water,
bottled drinks, refill water, etc.). Food products have special characteristics that need to be
considered such as the duration of product consumption, compliance with applicable
standards (MOH, BPOM, and the like), variability of ingredients to be processed from one
product to another, product storage, as well as packaging and post-production treatment
(Nugroho 2010).
Non-food agribusiness IMK has a different range of product types from food
agribusiness IMK. Based on the Village Potential data collection conducted by the Central
Bureau of Statistics, non-food agribusiness IMK consists of various industries, namely:
a. Apparel industry (convection, clothing, shirts, skirts, pants, embroidered mukena)
b. Leather, leather goods and footwear industry (bags, shoes, sandals, belts, etc.)
c. Textile industry (ulos cloth, songket cloth, woven cloth, and batik printing, etc.)
d. Furniture industry from wood, rattan/bamboo, plastic, metal (tables, chairs, beds,
cabinets, etc.)
e. Manufacture of wood, wood products, woven bamboo, rattan and the like (wooden
battens, boards, woven bags and mats, frames, etc.)
f. Non-metallic minerals industry/pottery/ceramic/brick industry (roof tiles, bricks,
porcelain, tiles, ceramics, stained glass, cups, jars, etc.)
g. Paper and paper goods industry (paper bags, post cards, cardboard, cement bags)
h. Tobacco processing industry (cigarette industry, drying and others)
i. Repair and installation of machinery and equipment (mobile welding, dynamo repair,
21
rice milling machine repair and others)
j. Other transportation equipment industry (boats, klotok, rafts, wheelchairs, etc.)
k. Handicraft and other industries (handicrafts, children's toys, agate, gold/imitation
jewelry,)
l. Printing and reproduction industry of recorded media (books, brochures, business cards,
calendars, banners, etc.)
5.2 Overview of Bank Financial Institutions in Indonesia
IMK agribusiness has an important role in the Indonesian economy so that an optimal
role is needed from financial institutions as an alternative capital to support business
development. Bank financial institutions in this study are an aggregation of Government
Commercial Banks, Private Commercial Banks, and Rural Banks. Government Commercial
Banks are banks whose shares are wholly or partially owned by the government. Private
Commercial Banks are banks in which the majority of shares are owned by the national
private sector. In addition, the deed of establishment and profit sharing are also managed by
the national private sector. Meanwhile, Rural Banks (BPR) are banks that only accept deposits
in the form of savings, time deposits, and so on and distribute funds. BPR also does not
provide services in payment traffic. Figure 5 shows the development of the number of bank
financial institution units by type.
Figure 5 shows that Government Commercial Banks (BUP) and Rural Banks (BPR)
experienced an increase in the number of units although not significant, but Private
Commercial Banks (BUS) experienced a reduction in the number of units in 2022 compared to
2018. Figure 5 shows that BUP has more units than BUS and BPR. This shows that BUP has
a greater opportunity to act as an alternative financial institution for agribusiness IMKs in
accessing capital. However, BPR is a type of bank financial institution that focuses more on
financing agribusiness IMKs micro businesses. This is due to the function of BPR, which
focuses on lending to the community, micro and small businesses, and as a depository
institution. Optimizing the role of BUP as a financial institution that has the largest number of
units and BPR as a financial institution with a focused role in providing credit for IMK needs
to be done.
Non-bank financial institutions include savings and loan cooperatives (kospin),
pawnshops, and Baitul Maal Wa Tamwil (BMT). Kospin is a type of cooperative that focuses
on saving and lending funds to its members. This is done to assist the business capital of its
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members. Table 9 shows the 10 provinces with the largest number of kospin in their region in
2022.
Table 9 shows that the most cooperatives are spread in Central Java Province, with
21,279 units or 29.44% of the total kospin in Indonesia. The second province with the highest
number of kospin is East Java with 14,897 units or 20.61% of the total kospin in Indonesia.
The third province with the highest number of kospins is West Java with 5,151 units or
around 7.13% of the total kospins in Indonesia. The provinces with the highest number of
kospins are Bali, East Nusa Tenggara, North Sumatra, West Sumatra, Aceh, Lampung, and
South Sulawesi, respectively. Table 9 shows that cooperatives are most widely spread in Java
compared to islands outside Java. This indicates that kospin has not been spread evenly and it
is still necessary to optimize the role of kospin in all regions of Indonesia.
Pawnshops are an alternative to capital sourced from non-bank financial institutions.
Pawnshops are different from kospin because they do not have permanent members. The main
activity of pawnshops is to provide capital assistance (loans) by pledging a number of
movable goods from the borrower which is carried out conventionally or sharia. Table 10
shows the 10 provinces with the largest number of pawnshops. Table 10 shows that 6 of the
10 provinces are outside Java and the rest are in Java. Nevertheless, the accumulated
percentage of villages with pawnshops in Java is greater than that outside Java. Central Java is
the first province with the highest number of villages with pawnshops, with 1,962 villages.
The second province with the highest number of The province with the most villages with
pawnshops is East Java with 1,276 villages. The third province with the highest number of
villages with pawnshops is West Java with 688 villages. The provinces with the highest
number of villages with pawnshops are Lampung, West Sumatra, Aceh, Yogyakarta, Riau,
West Kalimantan, and North Sumatra. This indicates that pawnshops are not evenly available
in every region in Indonesia, especially outside Java.
Baitul Maal Wa Tamwil (BMT) is an alternative capital for IMK agribusiness that
comes from non-bank financial institutions. In general, BMT is a sharia financial institution
whose main activity is to collect and distribute funds from and to the public with a profit
motive. BMT has its own uniqueness because it is a microfinance institution with a
cooperative legal entity. However, the capital lending system is profit-sharing or similar to
Islamic banks. Table 11 shows the 10 provinces with the highest number of areas that have
BMTs.
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5.3 Influence of Bank and Non-bank Financial Institutions on IMK Agribusiness
The statistical description shows the average value and growth of the research variables
at each time period of the Village/Kelurahan Potential data collection. Table 9 shows the
statistical description of the research variables. The statistical description shows the average
value and growth of the research variables at each data collection time period. Overall, there
was positive average growth in each variable. The number of agribusiness IMKs increased by
25.59% in 2022 compared to 2018. On average, there are 26 agribusiness IMK units spread
across every village in Indonesia. The number of bank financial institutions which is an
accumulation of the number of government commercial banks, rural banks, and private
commercial banks also increased in 2022 by 2.08% compared to 2018. The average number
of bank financial institution units is less than one unit in 2022. This shows that bank financial
institutions are not well distributed or not every village has a bank financial institution in its
area.
Table 12 shows the statistical description of non-bank financial institutions represented
by the variables of savings and loan cooperatives (kospin) and the existence of Baitul Maal
Wa Tamwil (BMT) showing negative average growth of -7.92% and -3.36%, respectively.
Meanwhile, the presence of pawnshops showed a positive average growth of 3.82%. The
average number of kospin is 0 to 1 unit in 2022 and the presence of pawnshops and BMT is
close to 0 (none). This shows that non-bank financial institutions are not evenly distributed or
not every village has a non-bank financial institution in its area.
The readiness of supporting infrastructure is reflected through the variables of
electricity index, infrastructure and distribution index, and telecommunication and
information index. These indices experienced positive average growth of 18.25% in the
electricity index; 2.31% in the infrastructure and distribution index; and 48.35% in the
telecommunications and information index. The telecommunications and information index
had the largest average percentage growth. However, the average telecommunications and
information index has the lowest value. This indicates that infrastructure-related policies and
development are currently focused on the telecommunications and information index because
it has not been spread and distributed evenly in Indonesia. The average value of the electricity
index is the highest compared to the average value of other indices. This shows that the
infrastructure and distribution index, which consists of indicators analyzing the type of road
surface, road passability by four-wheeled vehicles or more, the existence of post offices,
mobile postal services, and the existence of private expeditions, is better available than other
24
Selection of the best panel regression model between the Common Effect Model, Fixed
Effect Model, or Random Effect Model is based on the test results conducted. Based on the
chow test results (Appendix 1), the Prob>F value in the Fixed Effect test results is 0.000
which is smaller than the F-stat value of (0.005) so that panel regression is best using the
Fixed Effect Model. Furthermore, the hausman test results (Appendix 2) show the Prob>Chi2
value of 0.000 which is smaller than the p-value (0.005) so that the panel regression is best
using the Fixed Effect Model. Thus, the panel regression analysis model uses the Fixed Effect
Model.
The classical assumption test, namely the multicollinearity test, is carried out by looking
at the correlation coefficient between the independent variables attached in Appendix 3.
<0.9 so it is concluded that there is no correlation in the independent variables. The panel
regression analysis in this study has also been estimated using the variance-covariance (VCE)
matrix. The use of VCE matrix aims to overcome the problems of autocorrelation and
heteroscedasticity. Thus, all classical assumptions on the data used in this study have been
met.
The results of data processing using panel data regression are information to determine
the effect of the independent variables tested in the study on IMK agribusiness. Table 13
shows the panel regression results on the independent variables on the dependent in this study.
Financial Institutions Banks
The results of the analysis in Table 13 show that the variables that have a significant
effect on the growth of agribusiness IMK are non-bank financial institutions (savings and loan
cooperatives) and all supporting infrastructure displayed through the electricity index,
infrastructure and distribution index, and telecommunications and information index. The
results of the analysis also show that the bank financial institution variable has no significant
effect at the 1% real level. The increase in the number of units of bank financial institutions in
the village such as Government Commercial Banks, Rural Banks, and Private Commercial
Banks has not had a significant and even negative effect on the increase in agribusiness IMK.
This indicates that optimizing the role of bank financial institutions as capital providers for
IMK must be done not only in terms of increasing the number of bank units, but also the
amount of credit provided and control over the use of credit for productive activities.
25
Savings and Loan Cooperative (Kospin)
The saving/borrowing cooperative (kospin) variable has a significant positive effect on
the growth of agribusiness IMK with a coefficient of 0.02 at the 0.02 level real 1%. These
results indicate that an increase in the number of kospin units by 1 unit will increase the
number of agribusiness IMK units by 2% assuming other independent variables are constant
(ceteris paribus). Capital provided by kospin has requirements that are easier for businesses to
fulfill (no collateral and complete business legality data are required) than banks with adjusted
interest rates (flat, declining, effective declining, or annuity). This is because cooperatives aim
to improve the welfare of its members so that the provision of business capital is given with
the hope that its members can have a better income and prosper. However, cooperative
members are also encouraged to make timely repayments (installments) and loans are
allocated for productive activities (Fadliansyah et al. 2022).
Similar results were obtained by research by Edelia et al. (2022) on cooperatives and
MSMEs in the city of Medan and Beik et al. (2011) on the role of Pekalongan Sharia Savings
and Loan Cooperative as a source of financing from micro and small enterprises which shows
that there is a positive relationship and a strong role of cooperatives in business development
through expanding accessibility to capital. Cooperatives provide an alternative source of
funds for businesses that are mostly used for working capital so that businesses can generate
higher profits. The profit can then be used to escalate the business so that business
development can occur.
Alternative sources of capital provided by Kospin provide motivation for prospective
entrepreneurs to open new businesses in the micro and small industries. Alternative capital by
kospin can also have an impact on entrepreneurs who have run businesses to increase the
number of businesses (branches). However, the statistical description in Table 12 shows that
not every village has a kospin in its area, so synergy is needed from the government,
especially the relevant ministries and agencies to develop kospins in each region and optimize
the role of existing kospins.
Electricity Index
Supporting infrastructure has a significant positive effect on the growth of agribusiness
IMK as seen through the electricity index, infrastructure and distribution index, and
telecommunications and information index. The electricity index variable has a significant
positive effect on the growth of IMK agribusiness with a coefficient of 0.176 at a real level of
26
1%. The electricity index in this study has an analysis indicator, namely lighting on the main
road of the village / kelurahan and the presence of SUTET and SUTTAS. The results show
that an increase in the electricity index by one unit can increase the number of agribusiness
IMK units by 17.6% assuming other independent variables are constant (ceteris paribus).
Availability of sufficient electricity for production such as to run machinery (projected
through the presence of SUTET and SUTTAS) The availability of lighting on the main roads
of the village so that distribution channels can be passed has implications for increased
business productivity because production and distribution factors are fulfilled. This will also
increase the motivation of prospective entrepreneurs because the supporting infrastructure of
electricity in the region is well available so that the growth of IMK can occur. Similar results
were obtained by Grimm et al. (2012) which shows that electricity provides a role in
supporting business production. However, the role of electricity does not provide so much
impact, but electricity also needs to be accompanied by other infrastructure aspects into a
unity that supports the operation of the business.
Infrastructure and Distribution Index
The infrastructure and distribution index variable has a significant positive effect on the
growth of agribusiness IMK with a coefficient of 0.01 at a real level of 5%. The infrastructure
and distribution index in this study has analysis indicators, namely road accessibility (type of
road surface, road passability by 4-wheeled vehicles or more) and the existence of expedition
services (existence of post offices, mobile post services, and the existence of private
expeditions). The results show that an increase in the infrastructure and distribution index by
one unit can increase the number of agribusiness IMK units by 1% assuming other
independent variables are constant (ceteris paribus). This shows that road accessibility and
the presence of expedition services as infrastructure that supports the distribution of products
can increase the number of agribusiness IMKs.
A high infrastructure and distribution index will increase the number of agribusiness
IMK units. Road surfaces covered by asphalt will facilitate product traffic using land
transportation modes. Roads that can be traveled at any time and do not have access
limitations (cannot be passed during certain seasons such as rain/dry) make product
distribution to consumers possible at any time. The availability of freight forwarding services
such as the Post Office or private expedition services is an alternative to shipping products to
consumers.
27
Good access to product distribution alternatives will reduce production costs so that
business profits will increase. This will also increase the motivation of prospective
entrepreneurs so that the number of agribusiness IMKs will also increase. Good road
accessibility allows businesses to reach an area so that there is an increase in employment and
the number of businesses, especially in areas far from the market (Gibbons et al. 2019). The
availability of expedition services in an area has a strategic function to increase the flow of
goods from one region to another (Nansi 2022). Expedition services have a role as a means of
transportation for products from producers to consumers. Product delivery by expedition
services also allows businesses to reach a wider range of consumers. The availability of
expedition services is one of one factor that prospective entrepreneurs consider to open a new
business in IMK agribusiness.
Telecommunications and Information Index
The telecommunications and information index variable has a significant positive effect
on the growth of agribusiness IMK with a coefficient of 10.483 at a real level of 1%. These
results indicate that an increase in the telecommunications and information index by one unit
can increase the number of agribusiness IMK units by 1,048.3% assuming other independent
variables are constant (ceteris paribus). The telecommunications and information index in this
study has analysis indicators, namely the number of cellular telephone communication service
operators, the presence of the internet, the number of cellular telephone towers/Base
Transceiver Station (BTS), and signal strength. This shows that access to information
disclosure for both producers and consumers is important for business development. The
existence of the internet has an impact on the availability of access to broader market
information, analyzing the needs and characteristics of potential consumers, and becoming a
new method of marketing products, namely through e-commerce. Good information
dissemination has implications for increased business productivity because businesses can
produce in quantity and quality products according to market needs at competitive prices.
Consumers also get complete information both in terms of price and quality of the product to
be purchased.
The availability of communication services seen from the presence of BTS,
communication service providers, and good signals will make businesses able to access the
internet with optimal conditions. The existence of BTS spread in each region indicates that
people have a greater chance of getting a signal to access the internet and communicate well.
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Areas that are covered by communication service providers or providers are more likely to
have good signals than areas that are not covered by communication services. Communication
services can also make it easier for entrepreneurs to communicate and cooperate with raw
material providers and consumers so that businesses can produce at optimal costs. These
conditions create an open business climate so that the motivation of potential entrepreneurs
increases and agribusiness IMK growth occurs.
Similar results were found in the research of Heryasa and Purmiyati (2022) and
Saparuddin et al. (2020) which showed a positive correlation of internet and
telecommunication usage to micro and small business production. Urban businesses are more
likely to experience business growth and develop new products or services than businesses
that do not use mobile phones. Enterprises in remote areas including rural areas that use
mobile devices and websites are also more likely to develop new products or services. Gaglio
et al. (2022) also found that digital communication including the use of social media and
internet access has a positive effect on innovation growth and labor productivity.
Table 13 shows that the coefficient of panel data regression results on the
telecommunications and information index is the highest compared to other indices. This
shows that the equal distribution of information to both producers and consumers through the
existence of the internet and the availability of service providers in each region is important.
This is because the accessibility of information received by businesses in the form of
information on potential customers, product trends in each IMK agribusiness category, and
business competitors can help determine business strategies so that business profits can
increase and escalation such as increasing the number of business units can occur. Good
information accessibility will also increase the motivation of prospective entrepreneurs to
open new business units, resulting in an increase in the number of agribusiness IMK.
The existence of Pawnshops
The variable of non-bank financial institutions, namely the existence of pawnshops, has
not significantly affected the growth of agribusiness IMK. Pawnshops are credit institutions
with a pawn system with the aim of providing capital and making a profit. However, the
existence of pawnshops has not had an optimal impact on business improvement. This shows
that the growth of pawnshops in terms of numbers has not had enough impact, but needs to be
supported by optimizing the credit or loans provided and controlling the institution. The role
of pawnshops that has not been optimized can be due to the absence of a well-integrated
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information system in terms of data archiving, storage / release of goods, recording pawn
goods, and reporting transaction results (Fuzianti et al. 2019).
The existence of Baitul Mal Wa Tamwil (BMT)
The existence of Baitul Mal Wa Tamwil (BMT) as a variable that reflects non-bank
financial institutions has not significantly affected the growth of agribusiness IMK. The main
activity of BMT is to collect and provide funds to productive and profitable small businesses
based on the sharia system. However, BMT has not yet had a significant impact because
optimization of the role of BMT has not yet occurred. This can be seen from the absence of a
special law governing BMT so that the procedure for establishing BMT has not been
coordinated in a structured manner, there is legal uncertainty, overlap between existing
regulations and limited space for BMT (Nurkhaerani 2019).
5.4 Effect of Bank and Non-bank Financial Institutions on Agribusiness IMK by Group
(Food and Non-food)
The number of food and non-food agribusiness IMK business units has increased over
time. Figure 6 shows that the growth in the number of food agribusiness IMK units increased
by 25.54% in 2022, totaling 1,118,903 units compared to 615,155 units in 2018. Non-food
agribusiness IMK also experienced an increase in the number of units by 25.61% in 2022,
totaling 1,405,492 units compared to 772,283 units in 2018.
Food agribusiness IMK has a wide business development because humans always need
food for consumption so that the development of the business has increased sharply. The
success of production in agribusiness IMK depends on several things, namely health aspects,
the availability of raw materials, the way the products are handled, the time period or age of
consumption, and product compliance with applicable food product standards (Nugroho
2010). Food agribusiness IMKs are vulnerable to fluctuations in the price of raw materials for
production purposes, so businesses need to have good capital and financial management.
Support from city and district governments to provide opportunities for micro and small
enterprises to develop their businesses is needed, especially in access to funding and
marketing (Warcito 2016).
Non-food agribusiness IMK has different characteristics from food agribusiness IMK.
Non-food agribusiness IMK has products with a relatively longer shelf life (durable) than
food agribusiness IMK products. However, the storage of non-food products still requires
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special handling so that the quality of the products produced is maintained well until the end
of the shelf life to consumers. Raw material prices for non-food products tend to be stable
compared to food products but are relatively higher. Non-food businesses have a longer
turnover of receivables than food businesses. This is because payments for products usually
require a certain period of time for repayment. Non-food agribusiness IMK entrepreneurs
need good working capital management and alternative capital to turn around cash flow in
their business.
The regression model is disaggregated by group (food and non-food) to see more
comprehensively the effect of financial institutions on each major group of agribusiness
IMKs. Table 14 shows a comparison of the regression results of the independent variables on
food and non-food agribusiness IMK.
Comparison of panel data regression results in Table 14 shows 3 variables that have a
significant positive effect on the growth of food and non-food agribusiness IMK, namely,
savings and loan cooperatives (kospin), electricity index, and telecommunications and
information index. The difference in results is in the infrastructure and distribution index
variable which only has a significant positive effect on non-food agribusiness IMK with a
coefficient of 0.095 at a real level of 10%. This means that when there is an increase in the
infrastructure and distribution index by one unit, it will increase the number of non-food
agribusiness IMK by 9.5%. Infrastructure and distribution index has a significant positive
effect on IMK agribusiness non-food products because non-food products require a wider
distribution range for product delivery so that road accessibility and the availability of
expedition services in the village/kelurahan play an important role in business continuity.
The infrastructure and distribution index has not had a significant effect on food
agribusiness IMK. This is an indication that the index of available facilities and infrastructure
has not been able to support the development of food agribusiness IMK. Table 12 in the
statistical description shows that the infrastructure and distribution index has an average of 0.57
with an average growth of 2.31% in 2022 from 2018. This figure proves that the infrastructure
and distribution index is uneven, while food agribusiness IMK has product characteristics that
are not durable so that it requires a relatively fast time for the product to reach consumers.
The lack of synchronization between the needs and availability of supporting infrastructure,
especially in infrastructure and distribution facilities, has caused the infrastructure and
distribution index not to play a role in increasing food agribusiness IMK.
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5.5 Effect of Bank and Non-bank Financial Institutions on Agribusiness IMK by Region
(Java and Outside Java)
Supporting infrastructure for business development is not yet evenly available in
Indonesia. Limited infrastructure availability is one of the main causes of low investment
inflows and high logistics costs (Bappenas 2014). This is because economic activities are
supported by the supporting infrastructure available in the region. Economic inequality in
Indonesia occurs within the scope of the island of Java and other islands (Muta'ali 2015).
Research by Kusuma et al. (2019) also shows that the development and maintenance of
various infrastructure buildings is very high in various provinces in Java compared to other
islands.
The number of agribusiness IMKs in Java and outside Java shows an increase from year
to year. Java Island consists of 7 provinces, namely Banten, DKI Jakarta, West Java, Central
Java, DI Yogyakarta, and East Java. Figure 7 shows the growth in the number of agribusiness
IMK units in Java and outside Java. The figure shows that the number of agribusiness IMK
units in Java is more than agribusiness IMK outside Java. Agribusiness IMKs located in Java
increased by 21.27% in 2022 with a total of 1,203,906 units compared to 992,766 units in
2018. IMK agribusiness located outside Java shows a percentage increase of 31.37% in 2022
with a total of 973,869 units compared to 2018 which amounted to 741,292 units.
The regression model is disaggregated by region (Java and outside Java) to see more
comprehensively the effect of financial institutions supported by equitable infrastructure
readiness of the two regional groupings on agribusiness IMK. Table 15 shows the comparison
of panel data regression results of independent variables on IMK agribusiness in Java and
outside Java. Table 15 shows that IMK agribusiness in Java and outside Java is positively and
significantly influenced by saving and loan cooperatives (kospin), electricity index, and
telecommunication and distribution index.
Significantly different coefficient values are found in the telecommunication and
distribution index variables which are higher in agribusiness IMK outside Java at 11.571 and
Java at 9.020. This shows that the products produced by IMK agribusiness outside Java are
still strongly influenced by internet accessibility, the number of BTS, the number of cellular
telephone communication service operators, and signal strength for business development,
especially in reaching a wider market. The population that is more concentrated in Java also
makes the potential distribution of product information to potential consumers more evenly
distributed in Java than outside Java, especially in areas that are still not covered by the
Internet. The Central Bureau of Statistics (2022) issued the Indonesian ICT Development
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Index which shows that 4 of the 10 provinces with the highest index levels are in Java,
namely, Banten, DKI Jakarta, West Java, and DI Yogyakarta.
Table 15 shows that agribusiness IMK in Java and outside Java is positively and
significantly influenced by saving and loan cooperatives (kospin), electricity index, and
telecommunication and distribution index. Significantly different coefficient values are found
on the telecommunication and distribution index variables.
The distribution is higher in IMK agribusiness outside Java at 11.571 and Java at 9.020
at a real level of 10%. This shows that products produced by IMK agribusiness outside Java
are still strongly influenced by internet accessibility, the number of BTS, the number of
cellular telephone communication service operators, and signal strength for business
development, especially in reaching a wider market. The population that is more concentrated
in Java also makes the potential distribution of product information to potential consumers
more evenly distributed in Java than outside Java, especially in areas that are still not covered
by the Internet. The Central Bureau of Statistics (2022) issued the Indonesian ICT
Development Index which shows that four of the 10 provinces with the highest index levels
are in Java, namely, Banten, DKI Jakarta, West Java, and DI Yogyakarta.
Disaggregation by region, namely Java and outside Java, has a significant difference in
results on the infrastructure and distribution index, which has a significant negative effect on
agribusiness IMK in Java but a significant positive effect outside Java. These results indicate
that infrastructure related to road accessibility and expedition availability have two different
effects on the growth of agribusiness IMK when categorized by region. The positive effect of
the infrastructure and distribution index on agribusiness IMK outside Java occurs because
adequate transportation routes (passable by various modes of transportation) and available
expedition services help businesses in product distribution, especially in distant areas Good
product distribution accessibility has implications for a wider product market share so that
business profits can increase and IMK agribusiness can develop rapidly.
The infrastructure and distribution index has a negative and significant effect on
agribusiness IMK in Java. The negative effect is due to the existence of several "special
cases" due to infrastructure development, especially road development, which allows people
to have alternative roads. This is usually done to overcome the problem of road congestion
(traffic jams) in the area. For example, the construction of the Nagrek ring road in 2022 was
successful in reducing the load on the arterial route during the homecoming flow (Agus
2022). Alternative roads allow people not to focus on one main road so that the number of
potential customers of local businesses located on the main route decreases. A decrease in
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business profits occurred for entrepreneurs in the Setono Wholesale Market, which is the
center of the batik economy in Pekalongan City due to toll road construction. This happens
because potential customers, namely travelers, prefer toll roads to non-toll roads when
traveling, resulting in a decrease in income for local businesses (Official Portal of Central
Java Province 2023). However, this is a special case or a temporary effect of infrastructure
development which is still in a state of adaptation. In the long run, the government can make
supporting policies to increase the turnover of local businesses on the main route.
The overall panel data regression results show that non-bank financial institutions,
especially savings and loan cooperatives (kospin), have a more significant influence on
agribusiness IMK growth than bank financial institutions. Disaggregation by group and region
also shows that only kospin as a financial institution has a significant positive effect on
agribusiness IMK. This can happen because the regulation of taking loans or credit at kospin
is more flexible and not as rigid as that of bank financial institutions. IMK agribusiness as a
business that relatively does not have assets as collateral is a major obstacle in taking credit at
banks because the creding score will be low so that credit requests will be rejected. Kospin,
with its cooperative concept oriented towards the welfare of its members, is able to help
agribusiness IMKs grow through loans provided for business operations.
5.6 Policy Implications
The policy implication in this context is a recommendation for related parties with the
aim of optimizing the role of financial institutions and other supporting factors that can
increase the number of IMK agribusiness units. Policy implications are based on the results of
the analysis in the research that has been described. Based on the results of the panel data
regression analysis that has been carried out, the strategic steps that can be taken are:
a. Linkage Program
Saving and loan cooperatives (kospin) have a significant positive effect on the growth of
the number of agribusiness IMK units. The role of kospin needs to be optimized because it is
proven that the increase in the number of cooperatives in each village in Indonesia can
significantly increase the number of agribusiness IMK units. Optimizing the role of
cooperatives can be done through a linkage program which is a collaboration between
commercial banks and kospin. The linkage program scheme is that commercial banks provide
credit/loans to businesses indirectly through kospin. The linkage program aims to increase
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financing for businesses and increase the diversification and penetration of financing by banks
channeled through kospin. Loans provided by commercial banks can be in the form of KUR.
The distribution of KUR funds indirectly through kospin will be more effective because
kospin can better reach micro and small businesses.
Linkage programs provide benefits to both bank and non-bank financial institutions.
This is because cooperatives can increase their access to sources of funds to be channeled to
their members (business actors) and open access for cooperatives to grow. Banks also benefit
through an increase in the amount of credit disbursed. Thus, the accessibility of capital that
can be provided by kospin to agribusiness IMKs can be optimized.
The linkage program benefits the government because the distribution of KUR in
commercial banks or BPRs can be more evenly distributed due to cooperation with kospin.
This program also provides benefits for business actors because they get alternative forms of
credit channeled through kospin. IMK agribusiness can take a strategic step in the form of
taking KUR distributed by kospin. Easier access to capital will also have implications for the
motivation of prospective entrepreneurs to start their businesses so that businesses in
agribusiness IMK can grow in terms of numbers.
b. Equitable Infrastructure Development
Supporting infrastructure reflected through the variables of Electricity Index,
Infrastructure and Distribution Index, and Telecommunication and Information Index has a
significant positive effect on the growth of the number of agribusiness IMK units.
Optimization of existing infrastructure and equitable distribution of infrastructure availability
need to be done in every region of Indonesia because it is proven to increase the number of
agribusiness IMKs. All components of the supporting infrastructure index (electricity,
infrastructure and distribution, as well as telecommunications and information) must have
synchronization with the level of availability in Indonesia. All parts of Indonesia are the same.
When one of these components is not available in good condition, the other infrastructure
components cannot be utilized properly.
Equitable infrastructure development has a positive impact on the growth of IMK
agribusiness in the region. This is because areas with good infrastructure development can
support all business activities of business actors such as access to good electricity resources,
access to smooth distribution of raw materials and products, access to complete market
information, and others. Thus, business productivity can increase and motivate prospective
35
entrepreneurs to open their businesses so that there is growth in agribusiness IMK in the
region.
c. Policy Orientation to Local Enterprises
Policies related to equitable development of existing infrastructure need to be optimized
for implementation. Equitable infrastructure development is needed especially in areas with
good natural and human resource potential but do not have good supporting infrastructure.
Repair, maintenance, and optimization of existing infrastructure need to be carried out in good
cooperation between the government and the community. Existing policies also need to be
oriented towards local agribusiness IMKs in the areas under development through equal
access to raw materials, consumer information, and market information. The policy will have
a positive impact on local agribusiness IMK because it still has competitiveness with medium
and large enterprises. In addition, the development goal of improving community welfare can
be achieved.
d. Technology Utilization Optimization
The telecommunications and information index has the highest influence compared to
other indices. The development of telecommunications and information infrastructure in the
regions through policies that support the use of technology such as digitization of machinery,
communication tools, and the internet needs to be improved and become a special concern by
the government. The government can take this into consideration in making policies oriented
to the growth of IMK agribusiness. The policy made can also be an underlying policy so that
IMK agribusiness can take advantage of it through the existence of extension programs,
assistance (internet provision in the region), and others. Thus, the accessibility of market
information can be well accessed throughout Indonesia.
Conclusion :
Based on the results and discussion, research on the influence of financial institutions on
agribusiness IMK in Indonesia can be concluded as follows:
1. The influence of non-bank financial institutions is greater than bank financial
institutions in increasing the number of agribusiness IMK units. Non-bank financial
institutions, namely savings and loan cooperatives (kospin), have a significant positive
effect on the growth of agribusiness IMK units. Supporting infrastructure reflected
36
through the electricity index, infrastructure and distribution index, and
telecommunications and information index have a significant positive effect on the
growth of agribusiness IMK.
2. Disaggregation by group (food and non-food) shows that both IMK groups are
positively and significantly influenced by the cospin, electricity index, and
telecommunications and information index. Meanwhile, the infrastructure and
distribution index variable only has a significant positive effect on non-food
agribusiness IMK. The results of disaggregation by region (Java and outside Java) show
that IMK in both regions are positively and significantly affected by cosponsorship,
electricity index, and telecommunications and information index. Meanwhile, the
infrastructure and distribution index has a negative effect on agribusiness IMK in Java
but a positive effect on agribusiness IMK outside Java.
