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2365
FACTORS AFFECTING THE FINANCIAL PERFORMANCE OF CREDIT
UNION IN INDONESIA
Daniel Halomoan Simamora
*
, Willem A. Makaliwe, Eugenia Mardanugraha, Zahra
Kemala Nindita Murad
Master of Economic Planning and Development Policy, Universitas Indonesia, Depok, West Java, Indonesia
*
daniel.halomoan@ymail.com
ARTICLE INFO
ABSTRACT
Published: Januari 31
st
, 2023
The research aims to find out a number of things in terms of macro and
micro data that affect the condition of the financial performance of Credit
union in all provinces in Indonesia both in terms of internal factors and
external factors both in terms of microeconomics and macroeconomics.
Therefore, the assessment of the financial performance of Credit union
throughout Indonesia has an important role to play in terms of profitability
ratios which are influenced by a number of variables. Empirical evidence in
this study shows that the total assets, the age of the cooperative and the
number of members have a positive and significant relationship to the
profitability ratio of return on assets of credit union in Indonesia. In
addition, Number of Branches, Merger Activities have a negative influence
and a significant relationship to the financial performance of credit union.
Meanwhile, macroeconomic variables such as provincial GRDP do not have
a significant relationship and influence on the activity performance of the
return on asset profitability ratio of credit union. This finding has an
important role in improving services to credit cooperative members who are
SMEs so that they can increase their contribution to the percentage of
economic growth.
Keywords: financial performance,
credit union, microeconomics,
macroeconomics
This work is licensed under CC
BY-SA 4.0
INTRODUCTION
The Indonesian economy experienced a national growth of 3.69% (yoy) in 2021. Indonesia's
GDP per capita has increased to IDR 62.2 million (or the equivalent of US$ 4,349.5) where the
position of this growth rate is in a higher position when compared to GDP per capita in 2019 is
59.3 million. The achievement of this percentage increase categorizes Indonesia into the category
of countries that have an upper middle-income country. This classification category becomes a
barometer in driving national economic recovery as well as a stimulus for structural reforms to be
able to find a way out of the trap at the middle class/middle income trap category level. Gross
Regional Domestic Product (GRDP) data, either based on current prices or constant prices, is one
of the indicator points in knowing an economic condition in an area within a certain period of time.
(BPS, 2021). GRDP at constant national prices shows a decline that occurred throughout 2018 to
2020 with a decrease in growth of -126% and an increase in growth in 2021 of + 437%. (BPS,
2022)
The Indonesian economy experienced a national growth of 3.69% (yoy) in 2021. Indonesia's
GDP per capita has increased to IDR 62.2 million (or the equivalent of US$ 4,349.5) where the
position of this growth rate is in a higher position when compared to GDP per capita in 2019 is
59.3 million. The achievement of this percentage increase categorizes Indonesia into the category
of countries that have an upper middle-income country. This classification category becomes a
Factors Affecting the Financial Performance of Credit Union in Indonesia
2366 | I n d o n e s i a n J o u r n a l o f M u l t i d i s c i p l i n a r y S c i e n c e , 2 ( 4 ) , Jan,
2023
barometer in driving national economic recovery as well as a stimulus for structural reforms to be
able to find a way out of the trap at the middle class/middle income trap category level. Gross
Regional Domestic Product (GRDP) data, either based on current prices or constant prices, is one
of the indicator points in knowing an economic condition in an area within a certain period of time.
(BPS, 2021). GRDP at constant national prices shows a decline that occurred throughout 2018 to
2020 with a decrease in growth of -126% and an increase in growth in 2021 of + 437%. (BPS,
2022).
Figure 1. Active Indonesian Cooperatives in 2011-2021
Savings and Loans Cooperatives in particular have an entity in the form of a Credit
Cooperative which has the function of helping the credit needs of members, who really need it
with light conditions, Educating members to actively save regularly so as to form their own capital
and increase knowledge about cooperatives (Widiyawati, 2013). Credit Cooperative is a type of
Cooperative that has a focus on the scale of the Savings and Loans Business unit. Credit union
have an important role in providing financial services to the agribusiness sector. Location factors
and environmental conditions of credit union have an influence on the capacity of credit union in
driving operational performance. Significantly, this can be seen where credit cooperative branch
offices look less representative when compared to banking branch offices which are located far
from urban areas. targeting the segmentation of customers in the middle and upper economic class
who have high incomes (Quarter, 2016).
Credit union are entities that are quite widely established as part of the financial system in
most countries in the world where the need for financing by members is very high but is not
supported by large enthusiasm from members' savings. This has relevance to the variables of
available cooperative capital, the basic principles of cooperatives, gender issues and economic
conditions in a country (Choez & Mart 2022). The Takera Credit Cooperative in Canada has a
fairly high non-performing loan (NPL) ratio of 6.6 percent, which is measured in terms of financial
ratios in measuring the performance of the cooperative. This is in line with looking at several
factors such as the performance evaluation variable of the Takera Credit Cooperative based on the
Factors Affecting the Financial Performance of Credit Union in Indonesia
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2023
Balanced Scorecard approach and alternative credit cooperative internal policies influencing the
rate of loan repayments by members of the Takera Credit Cooperative in order to reduce Non
Performing Loans (NPL) below 5 percent. Loans are given to members using a group-by-group
model so that this maximizes the return on loans and investment assets. (Rasyidi et al, 2015).
Analysis of the relationship between credit risk and credit cooperative efficiency indicates that the
greater the credit risk score, the lower the operational efficiency score. In certain economic periods
of a country, credit union have also succeeded in maintaining their existence in the market and
diversifying loan products so that efficiency scores become higher and produce greater benefits
for members (Bressan et al., 2020).
There are institutions similar to credit union, namely the main cooperative banks operating
under the provisions of the 1949 banking regulations incorporated in the Cooperative Societies
(AACS), there are findings between the linkage of debt to asset ratios and the scale of operations
affecting the financial performance of cooperatives, based on a combined data sample for three
years from 140 well-distributed cooperative banks, showing significant differences between
capital adequacy, leverage and net interest margin (NIM). However, banks with higher leverage
ratios benefit in terms of return on equity (Srivastava, 2022) This is also the case with microfinance
institutions that always provide financial services to low-income people and banking customers
with minimal savings. In addition, the percentage of female loan members has a higher
contribution to the existence of microfinance institutions due to the higher loan repayment ratio
compared to men. So that microfinance institutions deliberately go through a policy mechanism
for selecting members with female gender status along with an increase in credit facilities provided
to female borrowers which has a positive influence on the performance and performance of
microfinance institutions (Fadikpe et al, 2022). Based on some of these studies, the authors can
see that there is a research gap that there are several variable factors that can influence the financial
performance of a credit cooperative so that research related to factors that influence financial
performance in the credit cooperative industry in Indonesia will be further investigated.
METHOD
This research data uses secondary data types. Secondary data was taken from the credit
cooperative annual report data from the Ministry of Cooperatives and SMEs Regency/Municipal
Cooperative and SMEs Office, Provincial Cooperative and SMEs Office and KUMKM Revolving
Fund Management Institution. In addition, macroeconomic secondary data came from data from
the Central Bureau of Statistics. The data in this study is secondary data which presents information
related to the profile and annual financial reports of credit union starting from financial ratios, total
assets, number of branches, number of members, age of credit cooperative legal entities, merger
activity and provincial GRDP. The unit of analysis in this research is credit union spread
throughout 33 provinces with a data period spanning 2021 of 270 credit union using a cross section
data model. Researchers used six independent variables (X) and one dependent variable (Y). with
an explanation of the definition of each variable is as follows:
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Table 1. Research Variables
Independent
Variable
Definition
Indicator
Unit
Literature
Asset Total
(X1)
The overall wealth owned by the
credit cooperative. The amount of
asset value in the balance sheet
financial statements 2021
The amount of
asset value in
the balance
sheet financial
statements
known book
2021
Rupiah
Hessou &
Lai, 2017
Member
Total (X2)
Number of members of the kreedit
cooperative in 2021 the amount of
asset value in the balance sheet
financial statements 2021
The amount of
asset value in
the balance
sheet financial
statements 2021
Nominal
Pille &
Paradi,
2002
Branch Total
(X3)
The number of branches to expand
the segmentation of the reach of
members so that this also has an
influence. Number of branches
owned by a credit cooperative
Number of
branches owned
by a credit
cooperative
Nominal
Hessou &
Lai, 2017
Legal Entities
of Credit
Cooperatives’
Age (X4)
The age of the legal entity of the
credit cooperative based on the
deed of establishment as the
number of years that the credit
cooperative started to run the
operational business in the year of
establishment of the credit
cooperative according to the deed
of establishment
Year of
establishment of
the credit
cooperative
according to the
deed of
establishment
Year
Hessou &
Lai, 2017
Provincial
GDRP (X6)
Indicators are important for
knowing the economic conditions
in a region in a certain period, both
on the basis of prevailing prices
and on the basis of constant prices
in each province
Percent
Hessou &
Lai, 2017
Merger
Activity (X6)
Merger or merger activities
between credit cooperatives within
the last 3 years and if credit
cooperatives that carry out merger
or merger activities between
1 =
Merger
0 = Not
Merger
Fried et
al., 1999
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cooperatives have joined in the last
three years
Dependent
Variable
Definition
Indicator
Unit
Literature
Return On
Asset
(Y)
A ratio that can measure a
Company's Ability can look for
profit levels. Profitability in this
study uses the return on asset ratio,
which shows the amount of asset
contribution in creating net profit.
ROA = Net Profit/Total Assets
ROA = Net
Profit/Total
Assets
Percent
Hessou &
Lai, 2017
The analytical method is used to determine the effect of the dependent variable with two or
more independent variables using the multilinear regression equation formula. To answer the
research questions, the researcher adopted the approach of Hessou & Lai (2017). The dependent
variable is the return on assets or the ratio of net income in a certain period (t) to the total value of
credit cooperative assets. Xi is the independent variable that includes credit union (i). N represents
the total number of independent variable factors which the authors consider against each credit
cooperative. i is cross-sectional data collected at one time on many credit cooperative entities,
considering that the purpose of this research is to find significant factors that can affect the
performance of credit union, the authors use cross-sectional data analysis in the 2021 timeframe
to obtain a significant relationship statistically between independent variable factors and return on
assets as a financial performance matrix in 270 credit cooperative entities as a research sample.
Multilinear regression test using cross section data in this study aims to determine the effect of
independent variables consisting of financial ratios, total assets, number of branches, number of
members, age of credit cooperative legal entity, merger activity, percentage of productive loans,
interest rates and variables macroeconomic GRDP of the Province on the dependent variable return
on assets of credit cooperative entities. The multilinear regression model in this study is formulated
with the following equation:
Information :
Y = ROA (Return On Assets)
α = Constant
β = Regression Coefficient
X1 = Total Assets
X2 = Number of Members
X3 = Number of Branches
X4 = Age of Credit Cooperative Legal Entity
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X5 = Provincial GRDP
X6 = Merger Activity
e = Error terms
i = Data Cross Section
RESULT AND DISCUSSION
Based on the table, information is obtained about the research variable, namely the Return
On Assets (ROA) variable which has a maximum value of 3.98 percent and a minimum value of
0.13 percent, with an average value (Mean) of 1.765 percent and a standard deviation value of 1.
017933 of the total research data as many as 270 data. The highest Return On Assets percentage
is owned by the Mandiri Soax Credit Cooperative located in Sanggau Regency, West Kalimantan
Province, while the lowest Return On Assets percentage is owned by the Karya Bakti CU Credit
Cooperative located in Pematang Siantar Regency, North Sumatra Province. The Total Assets
variable has a maximum value of IDR 75,420,000,000 and a minimum value of IDR 100,000, with
an average/mean value of IDR 5,140,000,000 and a standard deviation value of IDR
9,430,0000,000 with a total of all data research as much as 270 data. The lowest total assets are
owned by the Manaekat Credit Savings and Loans Cooperative, Ngada Regency, East Nusa
Tenggara Province while the lowest total assets are owned by the CU Koperasi Kredit Bersatu in
Manado City, North Sulawesi Province. In the variable Age of Cooperative Legal Entity there is a
maximum value of 61 years and a minimum value of 11 years with an average value (mean) of
19.13 years and a standard deviation value of 9.49 years with a total of 270 research data. The
oldest Cooperative Legal Entity is owned by the Imogiri KKGI Guru Credit Cooperative located
in Bantul Regency, Yogyakarta Province, while the youngest Cooperative Legal Entity is owned
by the Village Credit Agency Microfinance Services Cooperative located in Bojonegoro Regency,
East Java Province.
The Number of Members variable has a maximum value of 226,337 members and a
minimum value of 2 people, with an average (Mean) value of 5,295 members and a standard
deviation value of 17,200 members with a total of 270 research data. The highest number of
members is owned by the Mandiri Soax Credit Cooperative located in Sanggau Regency, West
Kalimantan Province, while the lowest number of members is owned by the South Sulawesi
Bekatigade Credit Cooperative Center in Makassar City, South Sulawesi Province. The Number
of Branches variable has a maximum value of 16 branches and a minimum value of 0 branches,
with an average (mean) value of 1.403704 and a standard deviation value of 2.401205 with a total
of 270 research data. The largest number of branches, 16, are owned by the Manaekat Savings and
Credit Cooperative, Ngada Regency, East Nusa Tenggara Province, while there are several small-
scale Credit union spread throughout Indonesia that do not have branches. The provincial GRDP
variable has a maximum value of 2,914,581 billion and a minimum value of 48,564 billion with
an average value (mean) of 978181.2 and a standard deviation value of 962220.9 with a total of
270 research data. Meanwhile, DKI Jakarta Province has the highest provincial GRDP with 13
credit union and the lowest provincial GRDP is Maluku Province with 2 credit union. The Merger
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Activity variable has a maximum value of 1 and a minimum value of 0, with an average (mean)
value of 0.0148148 and a standard deviation value of 0.1210355 with a total of 270 research data.
This illustrates that most credit cooperative entities rarely process merger activities
The results of the T Statistical Test in this study obtained several conclusions consisting of
the Total Assets Variable (X1) obtained a t-count value of 3.15 with a P-value of 0.002 which
means it is smaller than the significance value (0.05). Thus H1 is accepted so that it can be
concluded that the total asset variable has a significant effect on the Return On Assets variable.
The Cooperative Age variable (X2) obtained a t-count value of 3.34 with a P-value of 0.001 which
is smaller than the significance value (0.05). Thus H2 is accepted so that it is concluded that the
Cooperative Age variable has a significant effect on the Return On Assets variable. Then the
Number of Members Variable (X3) based on the results obtained from the t test obtained a t-count
value of 3.56 with a P-value of 0.000 which means it is smaller than the significance value (0.05).
Thus H3 is accepted so that it is concluded that the Number of Members variable has a significant
effect on the Return On Assets variable. The number of branches variable (X4) obtained a t-count
value of -3.37 with a P-value of 0.001 which means it is smaller than the significance value (0.05).
Thus H4 is accepted so that it is concluded that the number of branches variable has a significant
effect on the variable Return On Assets. The Provincial GRDP variable (X5) is based on the
acquisition of a t-count value of 0.53 with a P-value of 0.595 which means it is greater than the
significance value (0.05), thus H5 is rejected so that it is concluded that the Provincial GRDP
variable has no significant effect on the Return On Assets variable. Then in the Merger Activity
Variable (X6) a t-count value of -0.16 is obtained with a P-value of 0.871 which means that it is
greater than the significance value (0.05) thus H6 is rejected so that it is concluded that the
Provincial GRDP variable has no significant effect on the Return On Assets variable.
This research further looks at whether all the independent variables contained in the model
have a simultaneous (together) influence on the dependent variable through the F Statistical Test
Results where the probability value (Prob > F) = 0.000 <0.05, it can be concluded that Assets (X1),
Cooperative Age (X2), Number of Members (X3), Number of Branches (X4), Provincial GRDP
(X5) and Merger Activities (X6), simultaneously or jointly affect Return on Assets (Y). Then how
far the model's ability to explain the dependent variables is measured using the Coefficient of
Determination Test (R2) which obtains a coefficient of determination (R-squared) of R^2=0.1260.
Test Results for the Coefficient of Determination (R2) The coefficient of determination test (R2)
was carried out with the aim of measuring how far the ability of the model is to explain the
dependent variables. In this study the R2 test (R-square) was used to determine the Assets,
Cooperative Age, Number of Members, Number of Branches, Merger Activities, and Provincial
GRDP on Return on Assets. The coefficient of determination can be seen in table 4.11 below.
Based on Figure 4.4, it is known that the value of the coefficient of determination (R-squared) is
R^2=0.1260. This value can be interpreted as Assets (X1), Cooperative Age (X2), Number of
Members (X3), Number of Branches (X4), Provincial GRDP (X5) and Merger Activity (X6)
simultaneously or jointly affect ROA (Y) of 12.6%, the rest is influenced by other factors outside
the model and variables studied. According to Chin (1998), the R-Square value is categorized as
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strong if it is more than 0.67, moderate if it is more than 0.33 but lower than 0.67, and weak if it
is more than 0.19 but lower than 0.33. The value of the coefficient of determination is between 0
and 1. If the value is close to 1, it means that the independent variable provides almost all the
information needed to predict the dependent variable. However, if the value of R2 is getting
smaller, it means that the ability of the independent variable to explain the dependent variable is
quite limited.
The analytical method used in this study is multiple linear regression analysis using data for
the 2021 timeframe by taking data on credit union of 270 credit union as research samples.
Figure 2. The Result of Multiple Linear Regression Analysis
Based on the test results in the table above, the following equation is obtained.
Y_ROA = -0.86 + 0.07Asset + 0,021CooperativeAge + 0,000014MemberTotal -
0,106BranchTotal +0,253ProvincialGDRP – 0,099MergerActivity
Based on the regression equation above, the value of the constant shows a number of -0.86,
which means that if the independent variables, namely Total Assets, Age of Cooperative, Number
of Members, Number of Branches, Province GRDP and Merger Activities are worth 0, then the
magnitude of the value variable Return On Assets will decrease by 0.86 percent. Then the
coefficient value of the Asset variable shows the number 0.07060, which means that every increase
in assets by one percent will increase the Return On Assets by while the Cooperative Age shows
the number 0.021 which means that every one year increase in age will increase the Return On
Assets ratio by 2.1 percent. and the variable Number of Members shows the number 0.000014
which means that each additional member will increase the Return On Assets ratio by 0.0014
percent. then the coefficient value on the Number of Branches variable shows the number -
0.10686, which means that every addition of one branch will reduce the Return On Assets ratio by
10.6 percent and have no significant effect. Then the coefficient value of the Provincial GRDP
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variable shows a number of 0.02538 which means that every one percent increase in the Province's
GRDP value will increase the Return On Assets ratio by 2.5 percent and has no significant effect.
The Merger Activity variable shows the number 0.099, which means that if a merger activity
occurs, it will reduce the return on assets ratio by 9.9%.
Interpretation of Research Results
Based on the research above, several things can be interpreted, such as assets having a
positive and significant effect on Return On Assets where the results of this study are in line with
Almehdawe et al. (2020) which states that total assets have an effect on return on assets. This is
due to the company's ability to generate profit for one year by using the company's assets, both
current and fixed in production activities. Without profit, companies cannot attract external capital
sources to invest their funds in the company. Companies with high returns on investment will use
relatively low debt. Then the age of the cooperative has a positive and significant effect on return
on assets where the results of this study are in line with Hessou & Lai (2017) which states that the
age of credit union has an effect on return on assets. This is because the longer the credit
cooperative operates in the middle of the market, the more it influences the contribution of return
on assets. Credit union as time goes by, the experience in managing risk management is getting
better so that they have a higher capital adequacy ratio and have a higher interest rate than credit
union that have only been operating on the market in a relatively short time. The effect of the
number of members has a positive and significant effect on return on assets where the results of
this study are in line with Almehdawe et al. (2020) which states that the number of members has
an effect on return on assets. This is because credit union are different from banking where credit
union have a focus on good service quality for several existing members compared to maximizing
the number of members in each branch. Based on this philosophy, credit union are characterized
by rapid development in every dense population in a settlement when compared to bank financial
institutions which are growing rapidly in urban centers. In addition, several credit union that have
a member empowerment segmentation in the agribusiness sector will tend to have a higher variable
return on assets.
The effect of the number of branches also has a negative and significant effect on return on
assets where the results of this study are in line with Almehdawe et al. (2020) which states that the
number of branches has a negative effect on return on assets. This is because these factors, namely
costs, selling prices, and the volume of operational and non-operating costs, will cause expenses
that can reduce the assets and equity of credit union. Then the Total Provincial GRDP has a
negative and insignificant effect on Return On Assets where the results of this study are in line
with Almehdawe et al. (2020) which states that total has no effect and is not partially significant
to Return On Assets. Economic growth and inflation do not have a partial and simultaneous effect
on profitability. Observations using two macroeconomic variables so that in subsequent
observations using different variables that can affect the profitability of the company. Economic
growth does not directly affect the level of profitability of credit union. Meanwhile, provincial
GRDP influences economic activity but does not determine profitability ratios such as return on
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assets. Then Merger Activity has a negative and significant effect where the results of this study
are in line with Almehdawe et al. (2020) which states that the amount of merger activity has no
effect and has no partial significance on return on assets. The process of merger activity will
generate operational costs thereby reducing the percentage of return on assets profitability ratio.
CONCLUSION
Based on the results of data analysis and interpretation of the results of research that has been
done previously, it can be concluded that credit union that have large amounts of assets will be
linear with an increase in financial performance in terms of return on investment. Credit union that
are able to increase the number of assets owned will have a better influence on financial
performance than the cooperative itself. This is supported by the legal age of the Credit
Cooperative which goes hand in hand with the relatively sustainable operational business age with
a high rate of return on investment. the cooperative itself. The above is also supported by the
presence of members who are shareholders of credit cooperative entities who also participate in
improving the financial performance of cooperatives through contributions from member loans,
principal savings, mandatory savings and voluntary savings and time deposits against capital
flows.
Some of these things contradict with the element of increasing the number of branches which
will actually reduce the performance of the financial ratios of return on assets due to high operating
expenses by not carefully considering the output rather than the expansion process of opening
branches. This is also in line and linear with the merger activity process and will also lead to a
decrease in the ratio of return on assets where in the case of the merger activity process it will also
increase operational costs without being based on careful planning by credit union, this is due to
the absence of a target number of candidates definite members and unverified member
segmentation as well as qualified governance in managing branches. In addition, indirectly, from
a macroeconomic perspective, the provincial GRDP will contribute to an increase in the financial
performance of a credit cooperative, but indirectly due to the high GRDP value in a province where
the credit cooperative is located, it can indicate that the production of goods and services in a
province is high so that this will affect the absorption of workers who carry out production
activities and will stimulate credit loans to MSMEs through credit union
For credit cooperative entities, it is hoped that they can maximize governance efficiently and
effectively in order to increase Member Income by providing competency stimulus in the field of
SMEs that are carried out so that members who are SMEs can become classed in terms of capital
and enter the industrial world so as to create value added for the credit cooperative itself which is
expected to become an institution driving the people's economy in the future.
Decisions on opening branches and merger activities have no effect on increasing the return
on assets of credit union, so it is necessary to have policies that are more targeted internally at
credit union, such as increasing the number of qualified human resources and specializing in tasks
and functions to be able to have a better effect on increasing the profitability ratios for credit
cooperative.
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The researchers hope that this study can become a reference for future studies. More factors
regarding the financial performance and credit union are expected to emerge in subsequent
research to enrich public’s knowledge.
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