International Journal of Business, Economics and Law, Vol.

16, Issue 5 (August)

ISSN 2289-1552 2018

DISTRIBUTING WORKING CAPITAL LOAN AND INVESTMENT LOAN OF MICRO,

SMALL AND MEDIUM ENTERPRISES

Muhammad Aris Zulkarnain

Meina Wulansari Yusniar
Asrid Juniar

ABSTRACT

Regional Development Bank is a bank owned by local governments that located in each province in Indonesia. The purpose of
establishing Regional Development Bank is to encourage economic growth in the region, such as providing loan to micro, small
and medium enterprises. The aim of this research is to study the influence of Capital Adequacy Ratio (CAR), Third-Party Fund
(TPF), Return on Assets (ROA), Loan to Deposit Ratio (LDR), Non-Performing Loan (NPL) and external factors, such as:
Inflation and the central bank rates against working capital loans and investment loans at Regional Development Bank of South
Kalimantan-Indonesia, regional inflation index and the central bank rates in 2015-2017. Data analysis with panel data
regression used software EViews 10. The results showed that the variable of Capital Adequacy Ratio (CAR), Third-Party Fund
(TPF), Return on Asset (ROA), Loan to Deposit Ratio (LDR), Non-Performing Loan (NPL), Inflation and Bank Indonesia Rate
influence simultaneously to MSME working capital loans and MSME investment loans. For partial test results, the variables
which significantly affected MSME Working Capital Loans were CAR, TPF, LDR and BI Rate. The Partial test results affected
MSME investment loans. They were CAR, TPF, LDR, NPL, Bank Indonesia Rate.
Keywords: working capital loan, investment loan, MSME, regional development bank

INTRODUCTION

Micro, Small and Medium Enterprises (MSME) are the backbone of the Indonesian economy that has a strategic and important
role in national development also plays a role in economic growth and employment. SME’s are also proven to survive in the face
of the economic crisis that hit Indonesia in 1997-1998. After the economic crisis, the number of MSME actually increased even
able to absorb 85 million to 107 million workers until 2012.

The government now provides a bigger opportunity for MSME by issuing Law Number 20 of 2008 on MSME, in which it
regulates the extension of funding and facilitation by banks and non-bank financial institutions. The law provides for the banking
sector to assist the government's efforts to increase its loan-to-lending ratio by 2015 to 5% of total loans, 2016 by 10% of total
loans, 2017 by 15% of total loans, and by 2018 reached 20% of total credit.

The banking began aggressively to distribute credit to MSME. The MSME business is no longer seen as a second-class business.
Loan disbursement to MSME sector experienced rapid growth. The largest share is held by Government Bank by 50%, National
Bank by 40%, Regional Development Banks 7%, and Foreign Bank and a mixture of about 3% (Bank Indonesia, LPPI, 2015:
p.2). The percentage of MSME loan disbursement by Regional Development Banks is still relatively small due to the largest
market share that has been cultivated is consumer credit to Civil Servants, this is the concern of ASBANDA (Association of
Regional Development Banks) so that arranged roadmap transformation to Regional Champion which aims to realize Regional
Development Banks become a strong bank, highly competitive, can contribute to economic growth in the region.

The credit of MSME showed good resilience in the fourth quarter of 2017. This was indicated by credit growth which was still
quite high, which reached 9.10% with a credit risk that declined compared to the previous period. By sector, slowing growth in
credit of MSME was mainly in the agriculture, mining, construction, trade and accommodation sectors. The slowing growth in
these sectors is one of the factors causing increased banking prudence in lending. This is reflected in the distribution of working
capital loans and investment loans. The NPL ratio of MSME credit was recorded at 4.32%, decrease from the third quarter of
2017 which was 4.87%. The NPL ratio decrease occurred in almost all economic sectors.

Table 1. Growth and NPL of MSME in Indonesia

Indicator & Area Credit Growth (% YoY) NPL (%)
2016 2017 2016 2017
IV III IV IV III IV
Total Credit 10.56 10.55 9.10 4.38 4.87 4.32
- Working Capital Loan 11.06 10.79 10.49 4.36 4.88 4.42
- Investment Loan 9.43 10.01 5.98 4.43 4.84 4.07
- Agriculture 17.35 30.26 25.92 2.83 2.81 2.08
- Mining (7.08) 29.77 (3.71) 7.98 7.24 4.74
- Industry 11.88 6.73 10.58 4.07 4.13 4.08
- Construction 9.12 8.38 2.48 10.74 10.51 10.22
- Trade 10.79 5.97 5.94 3.70 4.59 4.14
- Accommodation 19.81 19.28 12.77 5.00 5.68 4.28
Kalimantan 7.14 10.91 9.57 4.95 5.16 4.27

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Sulawesi 8.97 8.95 9.88 4.46 4.87 4.60

Maluku & Papua 10.89 12.23 0.77 7.26 8.34 7.39
Bali & Nusa Tenggara 17.11 11.56 10.91 2.43 3.21 2.89

South Kalimantan Bank is one of the Regional Development Banks owned by the Provincial Government and Local Government
in South Kalimantan-Indonesia, which has the vision to be a bank that excels in the region and play a role in encouraging
economic growth. The mission is to mobilize and encourage the local economy and to assist the establishment of credit
institutions or Rural Banks owned by Provincial and Local Governments. South Kalimantan Bank was appointed by Bank
Indonesia as “Apex BPR” which is the guard against 23 Rural Banks in South Kalimantan. Apex's own function is focused on
the role of pooling, providing financial assistance and technical support.

During 2015, the MSME loan portfolio of South Kalimantan Bank has experienced a drastic decline both in terms of the number
of debtors and outstanding loans. In October 2015, the KUR program (people’s business credit) is re-run by Indonesian
Government, but the South Kalimantan Bank is not appointed as the channeling bank of KUR in 2015 to September 2016. South
Kalimantan Bank still provides credit with its own MSME products that have a higher lending rate than KUR interest rate only
9% effective per year. No significant increase, the number of debtors reduced every month, while the outstanding credit is still
fluctuating.
Table 1. The Growth of MSME Credit

Debtor Outstanding (million)

Period NPL Share
Amount +/- Amount +/-
Quarter I 6,345 - 1,070,286 - 1.71% 15.68%
Quarter II 6,204 -141 986,608 -83,678 1.66% 14.10%
2015
Quarter III 5,952 -252 885,460 -101,148 1.64% 12.48%
Quarter IV 5,444 -508 696,339 -189,121 1.63% 9.77%
Quarter I 5,145 -299 727,904 31,565 1.63% 9.89%
Quarter II 4,991 -154 856,770 128,867 1.88% 10.71%
2016
Quarter III 4,865 -126 871,003 14,233 1.80% 11.17%
Quarter IV 4,658 -207 751,959 -119,044 1.88% 9.82%
Quarter I 4,624 -34 762,058 10,099 2.25% 9.69%
Quarter II 4,712 88 810,721 48,663 2.25% 10.11%
2017
Quarter III 4,403 -309 819,856 9,135 2.07% 10.33%
Quarter IV 4,208 -195 653,752 -166,104 1.40% 8.50%

The phenomenon of the decline in the number of borrowers and the credit distribution of the South Kalimantan Bank is
interesting to do research. As a bank owned by the Provincial Government and Local Government that operates to serve the
people in South Kalimantan, it is better to know the potential of the region and the characteristics of the community. The South
Kalimantan region also has many industries and trades belonging to micro and small businesses that can be targeted for market
credit products.

Bank lending is likely to be influenced by several factors, either internal or financial ratios such as Capital Adequacy Ratio
(CAR), which is the main capital for banks to develop their business, Third-Party Fund (TPF) is a community fund collected by
banks to be distributed to loan, Return on Assets (ROA) as a measure of asset returns indicating the percentage of profit earned
by the bank, Loan to Deposit Ratio (LDR) is the amount of loan volume disbursed compared to Third-Party Funds, Non-
Performing Loans (NPL) are non-performing loans that fall under the Substandard, Doubtful and Loss criteria. While the
external factors that can affect the lending of SME’s such as Inflation, related to the increase in the price of goods thereby
decreasing the interest of public spending, then the Bank Indonesia Rate is the policy of interest rate reference issued by Bank
Indonesia. Several previous studies show the effect of CAR, TPF, ROA, LDR, NPL, and Inflation variables on credit
distribution.

LITERATURE REVIEW
1. Credit
According to Golin and Delhaise (2013, p.1), credit is the realistic belief or expectation, upon which a lender is willing to
act, that funds advanced will be repaid in full in accordance with the agreement made between the party lending the funds
and the party borrowing the funds.
2. Bank
According to Golin and Delhaise (2013, p.89), a Bank is one type of financial intermediary and probably the most
ubiquitous but not the only type.
3. Capital Adequacy Ratio
Bank capital is the ultimate measure of bank creditworthiness. The CAR as a measure of bank soundness and the capital
measure functions as some supreme indicator of the market’s confidence. Although these functions of capital are operative
in all businesses, they are especially critical to banks. This may be explained by a very peculiar attribute of banks that
historically has served to underline the comparative importance of their capital levels: high leverage. (Golin and Delhaise,
2013, p.450).

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The formula of Capital Adequacy Ratio is described as follows:

𝑇𝑖𝑒𝑟 1 𝐶𝑎𝑝𝑖𝑡𝑎𝑙 + 𝑇𝑖𝑒𝑟 2 𝐶𝑎𝑝𝑖𝑡𝑎𝑙

𝐶𝑎𝑝𝑖𝑡𝑎𝑙 𝐴𝑑𝑒𝑞𝑢𝑎𝑐𝑦 𝑅𝑎𝑡𝑖𝑜 𝐶𝐴𝑅 % = 𝑥100
𝑅𝑖𝑠𝑘 𝑤𝑒𝑖𝑔ℎ𝑡𝑒𝑑 𝐴𝑠𝑠𝑒𝑡𝑠

The numerator, capital, was separated into core (Tier 1) capital and supplementary (Tier 2).

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4. Third-Party Funds (Customer Deposits)

Funding liabilities can be broadly divided into customer deposits and purchased Funds. Third-Party Funds or Customer
Deposits are also referred to as core deposits, although core deposits might sometimes include stable or relatively stable
deposits from other sources (Golin and Delhaise, 2013, p.210).
According to Bank Indonesia Regulation (2015, p.3), Third-Party Funds or customer deposits is a Bank's obligation to
residents and non-residents in Rupiah and foreign currencies covering Third-Party funds covering demand deposits, savings
deposits and time deposits in Rupiah and foreign currency, excluding interbank funds.
5. Return on Assets
Profitability is measured using ratios such as Return on Assets. Return on equity (ROE) and ROA are two fundamental
return-type ratios used in bank credit analysis. ROA shows how efficiently the enterprise is able to extract earnings from its
assets (Golin and Delhaise, 2013, p.275).
The formula of Capital Adequacy Ratio is described as follows:
𝑁𝑒𝑡 𝐼𝑛𝑐𝑜𝑚𝑒
𝑅𝑂𝐴 (%) = 𝑥100
𝑇𝑜𝑡𝑎𝑙 𝐴𝑠𝑠𝑒𝑡𝑠
6. Loan to Deposit Ratio
According to Golin and Delhaise (2013, p.605), Loan to Deposit Ratio (LDR) is the availability of credit. The LDR may be
expressed in terms of customer lending (excluding interbank lending) or in terms of total bank lending. It is also calculated
to include credit provided by nonbank financial intermediaries as well. These include the bank intermediation ratio, growth
in credit (lending) and the loan-to-deposit ratio.

According to Bank Indonesia Regulation (2015, p.4), Loan to Deposit Ratio is the ratio of credits granted to third parties in
Rupiah and Foreign Currency excluding credits to other banks. Used to measure the total amount of credit granted by banks
to funds obtained from third parties (savings, demand deposits, and time deposits).

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7. Non-Performing Loan
Non-Performing Loan (NPL) are problem loans. Bank Indonesia categorize into 5 parts there is: substandard, doubtful and
stuck. According to Bank Indonesia Regulation (2015, p.6), Non-Performing Loan (NPL) hereinafter referred as NPL Ratio
of Total Credit is the ratio between total credit with substandard, doubtful and stuck to Total Credit. Used to measure the
number of non-performing loans (criteria: Doubtful, Substandard, Stuck) on total loans disbursed by banks. NPLs shall not
exceed 5% of total credit.
According to Golin and Delhaise (2013, p.337), not all of a bank’s customers will pay back the funds they have borrowed.
Some will make repayments for a period of time and then default on the full payment of interest and principal. In other
words, some loans that a bank makes will become non-performing. Indeed, that a portion of a bank’s loans will become
non-performing loans or NPLs, is practically certain and an inherent risk and cost of banking.
8. Inflation
According to Golin and Delhaise (2013, p.596), monetary inflation is the increase in money supply, and price inflation is
the actual upward changes to the price of a set of goods or service.
9. Bank Indonesia Rates
The reference rate is determined by the central bank, is one of the monetary policies including official discount rate,
interbank rate, real interest rate, yield curve shape (Golin and Delhaise (2013, p.587),
According to Bank Indonesia Regulation (2005, p.3), Bank Indonesia rate is the interest rate with a tenor of one month
periodically determined for a certain period by Bank Indonesia and announced to the public as a signal of monetary policy.

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RESEARCH HYPOTHESIS
Research Models:
This research was conducted on two research models as follows:

CAR (X1)

TPF (X2)

ROA (X3)

LDR (X4)
MSME Working Capital
Loan (Y1)
NPL (X5)

Inflation (X6)

Bank Indonesia Rate

(X7)

Figure 1. First Research Model

Figure 2. Second Research Model

CAR (X1)

TPF (X2)

ROA (X3)

LDR (X4) MSME Investment Loan

(Y2)
NPL (X5)

Inflation (X6)

Bank Indonesia Rate

(X7)

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Hypothesis:
1. Influence of Capital Adequacy Ratio (CAR) on MSME Loans
According to Barus and Lu (2013) in his research hypothesis states that CAR affects both simultaneously and partially to
the credit distribution of MSME. According to Santoso and Dewi (2017) in his research hypothesis states that CAR partially
and simultaneously affect credit on PT. Bank Mandiri (Persero) Tbk.
H1: CAR variable suspected to negatively affects toward MSME working capital loans
H2: CAR variable suspected to negatively affects toward MSME investment loans

2. Influence of Third-Party Funds (Customer Deposits) on MSME Loans

According to Sari and Abundanti (2016) in his research hypothesis stated that Third-Party Funds has a positive and
significant impact on the banking credit distribution.
H3: Third-Party Funds variable suspected to positively affects toward MSME working capital loans
H4: Third-Party Funds variable suspected to positively affects toward MSME investment loans

3. Influence of Return on Assets (ROA) on MSME Loans

According to Riadi (2018) in his research hypothesis that ROA has a positive effect on lending. According to Sari and
Abundanti (2016) in his research hypothesis states that ROA has a positive and significant impact on lending.
H5: ROA variable suspected to positively affects toward MSME working capital loans
H6: ROA variable suspected to positively affects toward MSME investment loans

4. Influence of Loan to Deposit Ratio (LDR) on MSME Loans

According to Barus and Lu (2013) in the research, the hypothesis states that the LDR effect both simultaneously and
partially to the credit distribution of MSME by commercial banks in Indonesia. According to Riadi (2018) in his research
hypothesis states that the LDR has a positive and significant effect on lending. According to Santoso and Dewi (2017) in his
research hypothesis states that the LDR effect both simultaneously and partially on the channeling of credit.
H7: LDR variable suspected to positively affects toward MSME working capital loans
H8: LDR variable suspected to positively affects toward MSME investment loans

5. Influence of Non-Performing Loan (NPL) on MSME Loans

According to Barus and Lu (2013) in his research hypothesis states that the NPL has an effect both simultaneously and
partially on the channeling of MSME loans disbursed by Commercial Banks in Indonesia. According to Riadi (2018) in his
research hypothesis states that the NPL has a negative effect on lending. According to Santoso and Dewi (2017) in his
research hypothesis states the NPL effect on lending.
H9: NPL variable suspected to negatively affects toward MSME working capital loans
H10: NPL variable suspected to negatively affects toward MSME investment loans

6. Influence of Inflation on MSME Loans

According to Sari and Abundanti (2016) in his research hypothesis states that Inflation has a negative and significant effect
on lending.
H11: Inflation variable suspected to negatively affects toward MSME working capital loans
H12: Inflation variable suspected to negatively affects toward MSME investment loans

7. Influence of Bank Indonesia Rate on MSME Loans

According to Barus and Lu (2013) explain the results of his research that Spread interest rates negatively affect the lending
of SMEs.
H13: Bank Indonesia Rate variable suspected to negatively affects toward MSME working capital loans
H14: Bank Indonesia Rate variable suspected to negatively affects toward MSME investment loans

RESEARCH METHODS
Research Object
The object of research are Capital Adequacy Ratio (CAR), Third-Party Funds (Customer Deposits), Return on Assets (ROA),
Loan to Deposit Ratio (LDR), Non-Performing Loan (NPL), Inflation and Bank Indonesia Rate.

Research Methods
The research population used in this research is all Branch of South Kalimantan Bank which distributed MSME credit period
2015-2017 as many as 15 Branches. Sampling method in this study using purposive sampling is desirable to sample criteria
based on the research objectives of the South Kalimantan Bank Branch operating in South Kalimantan region, Jakarta Branch
removed from the sample.

Data Collection
The data used in this study is secondary data sourced from:
1. Monthly data of financial reports and the distribution of South Kalimantan Bank MSME working capital loan and MSME
investments loan, period 2015-2017.
2. Monthly data on Inflation and Bank Indonesia Rate, period 2015-2017.

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Data Analysis Methods

Data were analyzed by the panel data regression analysis model using software EViews version 10 to determine the effect of
CAR, DPK, ROA, LDR, NPL, Inflation and Bank Indonesia Rate on Working Capital Loans and Investment Loans for MSME
in South Kalimantan Bank Branch in South Kalimantan Province.
Panel data regression test used Generalized Least Squares (GLS) or Weighted Least Square (WLS) estimators to obtain BLUE
estimator values (Best Linear Unbiased Estimator).

OPERATIONAL VARIABLES
The operational definition of the variables in this study as follows :
Table 2. Operational Variables
Variable Notation Concept Variable Measurement of Variables
Independent Variable
1. Capital Adequacy Ratio X1 Capital Adequacy Ratio of CAR = (tier 1 capital + tier 2 capital
(CAR) Banks / ATMR) x 100%
2. Third-Party Funds X2 Demand deposits, savings TPF = total demand deposits + total
(Customer Deposits) deposits, and time deposits savings deposits + total time
deposits
3. Return on Assets (ROA) X3 Profitability indicator ROA = (Net Income / Total Assets)
x 100%
4. Loan to Deposit Ratio X4 Availability of credit LDR = (Total Credit / Third-Party
(LDR) Funds) x 100%
5. Non-Performing Loan X5 Problem loans (criteria: NPL = (Total NPL / Total Credit) x
(NPL) Doubtful, Substandard, Stuck) 100%
6. Inflation X6 the actual upward changes to Measured by Consumer Price Index
the price of a set of goods or (CPI)
service
7. Bank Indonesia Rate X7 Reference interest rate by the Data available on www.bi.go.id
central bank
Dependent Variable
8. Working Capital Credit Y1 lending of working capital of Monthly data of MSME working
MSME capital credit
9. Investment Credit Y2 lending of investment of Monthly data of MSME investment
MSME credit

DATA ANALYSIS METHOD

The data obtained from the results of further research is analyzed by the panel data regression analysis model using Software
EViews version 10 to determine the effect of CAR, TPF, ROA, LDR, NPL, Inflation and Bank Indonesia Rate on Working
Capital Loans and Investment Loans for MSME at Branch of South Kalimantan Bank in South Kalimantan Province.
The data panel regression equation in this study as follows:
𝒴1𝒾𝓉 = 𝑏J + 𝑏K 𝒳K𝒾𝓉 + 𝑏M 𝒳M𝒾𝓉 + 𝑏N 𝒳N𝒾𝓉 + 𝑏O 𝒳O𝒾𝓉 + 𝑏P 𝒳P𝒾𝓉 + 𝑏Q 𝒳Q𝒾𝓉 + 𝑏R 𝒳R𝒾𝓉 + ℯ𝒾𝓉
𝒴2𝒾𝓉 = 𝑏J + 𝑏K 𝒳K𝒾𝓉 + 𝑏M 𝒳M𝒾𝓉 + 𝑏N 𝒳N𝒾𝓉 + 𝑏O 𝒳O𝒾𝓉 + 𝑏P 𝒳P𝒾𝓉 + 𝑏Q 𝒳Q𝒾𝓉 + 𝑏R 𝒳R𝒾𝓉 + ℯ𝒾𝓉
Explanation :
𝒴K𝒾𝓉 : MSME working capital credit
𝒴M𝒾𝓉 : MSME investment credit
β0: Constanta
β1: CAR regression coefficient
𝒳K𝒾𝓉 : CAR variable
β2: TPF regression coefficient
𝒳M𝒾𝓉 : TPF variable
β3: ROA regression coefficient
𝒳N𝒾𝓉 : ROA variable
β4: LDR regression coefficient
𝒳O𝒾𝓉 : LDR variable
β5: NPL regression coefficient
𝒳P𝒾𝓉 : NPL variable
β6: Inflation regression coefficient
𝒳Q𝒾𝓉 : Inflation variable
β7: Bank Indonesia Rate regression coefficient
𝒳R𝒾𝓉 : Bank Indonesia Rate variable
ℯ𝒾𝓉 : error

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RESULT AND DISCUSSION

1. Panel Data Regression
1.1. First Research Model
Table 7. Panel Data Regression Test of First Research Model

Variable Coefficient Std. Error t-Statistic Prob.

X1_CAR -3.30E+08 60362132 -5.470481 0.0000

X2_TPF 0.010572 0.001978 5.345257 0.0000
X3_ROA 2.47E+08 2.18E+08 1.135850 0.2566
X4_LDR -4.71E+08 96487014 -4.879867 0.0000
X5_NPL -1.66E+08 1.61E+08 -1.029667 0.3037
X6_INFLASI -1.75E+08 4.11E+08 -0.425264 0.6708
X7_BIRATE 2.65E+10 2.66E+09 9.963769 0.0000
C 4.69E+10 3.24E+09 14.48065 0.0000

Weighted Statistics

R-squared 0.969476 Mean dependent var 1.01E+11

Adjusted R-squared 0.968212 S.D. dependent var 7.85E+10
S.E. of regression 1.23E+10 Sum squared resid 7.25E+22
F-statistic 767.0387 Durbin-Watson stat 0.354305
Prob(F-statistic) 0.000000

1.1.1. t-Test

In the panel data regression analysis, the t-test is used to test the effect of independent variables (CAR,
TPF, ROA, LDR, NPL, Inflation and Bank Indonesia Rate) partially to dependent variable (MSME
Working Capital Loans).
Table 8. t-Test Summary of First Research Model
Variable Coefficient Prob. Hypothesis Results
CAR -3.30E+08 0.0000 < 0.05 Negative effect and significant
TPF 0.010572 0.0000 < 0.05 Positive effect and significant
ROA 2.47E+08 0.2566 > 0.05 Positive effect and not significant
LDR -4.71E+08 0.0000 < 0.05 Negative effect and significant
NPL -1.66E+08 0.3037 > 0.05 Negative effect and not significant
Inflation -1.75E+08 0.6708 > 0.05 Negatif effect and not significant
Bank Indonesia 2.65E+10 0.0000 < 0.05 Positive effect and significant
Rate

1.1.2. F-Test
The Simultaneous Test (F-Test) is conducted to find out whether the independent variables in the model
has an effect simultaneously on the dependent variable.
Hypothesis:
H0: Prob. (F-statistic) > 0.05 received H0
Ha: Prob. (F-statistic) < 0,05 received Ha
Based on Table 7. obtained F-statistic value 767.0387 with Prob. (F-statistic) 0.000 < 0.05 Ha accepted, it
can be concluded that independent variables CAR, TPF, ROA, LDR, NPL, Inflation and Bank Indonesia
Rate simultaneously affect the dependent variable.
1.1.3. Determination Coefficient-Test (R2)

Table 7. shows the amount of Adjusted R-squared (R-squared value that has been corrected by standard
error value) of 0,968212, it means that 96.82% of MSMEs Working Capital Loan variables can be
explained by variations of independent variables CAR, TPF, ROA, LDR, NPL, Inflation and Bank
Indonesia Rate, the rest of 3.18% is explained by other causes outside the model.
1.1.4. Regression Equation

𝒴1𝒾𝓉 = 𝛽J + 𝛽K 𝒳K𝒾𝓉 + 𝛽M 𝒳M𝒾𝓉 + 𝛽N 𝒳N𝒾𝓉 + 𝛽O 𝒳O𝒾𝓉 + 𝛽P 𝒳P𝒾𝓉 + 𝛽Q 𝒳Q𝒾𝓉 + 𝛽R 𝒳R𝒾𝓉 + ℯ𝒾𝓉

MSME Working Capital Loanit = 4.69E+10 + (-3.30E+08)xCARit + 0.010572xTPFit + 2.47E+08xROAit +
(-4.71E+08)xLDRit + (-1.66E+08)xNPLit + (-1.75E+08)xInflasiit + 2.65E+10xBIRATEit + eit
1.1.5. Interpretations

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1) The result of panel data regression in Table 7. shows the CAR regression coefficient was -3.30E+08
and the probability value 0.0000 < 0.05 which states CAR has a negative and significant effect on the
distribution of MSME Working Capital Loans. The results accepted the H1 hypothesis which states
CAR has a negative effect on the distribution of MSME Working Capital Loans. The results of this
study support the research conducted by Barus and Lu (2013) in the results of his research stated that
the CAR negatively affects the lending of SMEs. Riadi (2018) in the results of his research that the
CAR has a significant effect on credit.
2) The result of panel data regression in Table 7. shows the TPF regression coefficient was 0.010572 and
the probability value 0.0000 < 0.05 which states the TPF has a positive and no significant effect on the
distribution of MSME Working Capital Loans. These results accepted H3 hypothesis that TPF has a
positive effect on the distribution of MSME Working Capital Loans. The results of this study support
research conducted by Sari and Abundanti (2016) in the results of his research that TPF has a positive
effect and significant to lending.
3) Results of panel data regression in Table 7. shows ROA regression coefficient was 2.47E+08 and the
probability value 0.2566 > 0.05 which states that ROA has a positive and no significant effect to the
distribution of MSME Working Capital Loans. These results accept the hypothesis H5 which states
ROA has a positive effect on the distribution of MSME Working Capital Credits. The results of this
study support research conducted by Sari and Abundanti (2016) in the results of his research states
that ROA has a positive and not significant effect on lending.
4) The result of panel data regression in Table 7. shows the LDR regression coefficient was -4.71E+08
and the probability value 0.0000 < 0.05 which states LDR has a negative and significant effect on the
distribution of MSME Working Capital Loans. The results rejected the H7 hypothesis that LDR has a
positive effect on the distribution of MSME Working Capital Credits. The results of this study support
research conducted by Barus and Lu (2013) in the results of his research states LDR has a negative
and significant impact on the MSME lending. Riadi (2018) in the results of his research states LDR
has a significant effect on credit. Santoso and Dewi (2017) in the results of his research states LDR
has a significant effect on lending.
5) The result of panel data regression in Table 7. shows the NPL regression coefficient was -1.66E+08
and the probability value 0.3037 > 0.05 which states NPL has a positive and no significant effect on
the distribution of MSME Working Capital Loans. The results of this study support research
conducted by Riadi (2018) in the results of his research NPL has a positive effect is not significant to
credit.
6) The result of panel data regression in Table 7. shows the Inflation regression coefficient was -
1.75E+08 and the probability value 0.6708 > 0.05 which states Inflation has a negative and no
significant effect on the distribution of MSME Working Capital Loans. The results of this study
support research conducted by Jenkins and Hussain (2014) in the results of his research stated
Inflation has a negative effect on Small and Medium Enterprise Bank Credit.
7) The result of panel data regression in Table 7. shows the regression coefficient of BI Rate of 2.65E+10
and the probability value 0,0000 < 0.05 which states Bank Indonesia Rate has a positive and
significant effect to the distribution of MSME Working Capital Loans. The results of this study
support research conducted by Sari (2013) in the results of his research stated Bank Indonesia Rate has
a positive and significant effect on bank lending.
1.2. Second Research Model

Table 9. Panel Data Regression Test of Second Research Model

Variable Coefficient Std. Error t-Statistic Prob.

X1_CAR -1.35E+08 13831556 -9.734901 0.0000

X2_TPF -0.001781 0.000412 -4.324933 0.0000
X3_ROA 11489190 49731089 0.231026 0.8174
X4_LDR -90710992 22016694 -4.120101 0.0000
X5_NPL 1.75E+08 39134439 4.465462 0.0000
X6_INFLASI -85626115 85801917 -0.997951 0.3188
X7_BIRATE 5.54E+09 5.60E+08 9.891069 0.0000
C 1.25E+10 8.02E+08 15.54479 0.0000
Weighted Statistics

R-squared 0.959255 Mean dependent var 1.45E+10

Adjusted R-squared 0.957568 S.D. dependent var 1.15E+10
S.E. of regression 2.38E+09 Sum squared resid 2.74E+21
F-statistic 568.5617 Durbin-Watson stat 0.294085
Prob(F-statistic) 0.000000

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1.2.1. t-Test

In the panel data regression analysis, t-test is used to test the effect of independent variables (CAR, TPF,
ROA, LDR, NPL, Inflation and Bank Indonesia Rate) partially to dependent variable (MSME Investment
Loans).
Table 8. t-Test Summary of Second Research Model
Variable Coefficient Prob. Hypothesis Results
CAR -1.35E+08 0.0000 < 0.05 Negative affect and significant
TPF -0.001781 0.0000 < 0.05 Negative affect and significant
ROA 11489190 0.8174 > 0.05 Positive affect and not significant
LDR -90710992 0.0000 < 0.05 Negative affect and significant
NPL 1.75E+08 0.0000 < 0.05 Positive affect and significant
Inflation -85626115 0.3188 > 0.05 Negative affect and not significant
Bank 5.54E+09 0.0000 < 0.05 Positive affect and significant
Indonesia
Rate

1.2.2. F-Test
The Simultaneous Test (F-Test) is conducted to find out whether the independent variables in the model
has an effect simultaneously on the dependent variable.
Hypothesis:
H0: Prob. (F-statistic) > 0.05 received H0
Ha: Prob. (F-statistic) < 0,05 received Ha
Based on Table 9. obtained F-statistic value 568.5617 with Prob. (F-statistic) 0.000000 < 0.05 Ha accepted,
it can be concluded that independent variables CAR, TPF, ROA, LDR, NPL, Inflation and Bank Indonesia
Rate simultaneously affect the dependent variable.
1.2.3. Determination Coefficient-Test (R2)

Table 9. shows the amount of Adjusted R-squared (R-squared value that has been corrected by standard
error value) were 0.957568, it means that 95.7% of MSME Investment Loan variables can be explained by
variations of independent variables CAR, TPF, ROA, LDR, NPL, Inflation and Bank Indonesia Rate, 4.3%
is explained by other causes outside the model.

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1.2.4. Regression Equation

𝒴2𝒾𝓉 = 𝛽J + 𝛽K 𝒳K𝒾𝓉 + 𝛽M 𝒳M𝒾𝓉 + 𝛽N 𝒳N𝒾𝓉 + 𝛽O 𝒳O𝒾𝓉 + 𝛽P 𝒳P𝒾𝓉 + 𝛽Q 𝒳Q𝒾𝓉 + 𝛽R 𝒳R𝒾𝓉 + ℯ𝒾𝓉

MSME Investment Loanit = 1.25E+10 + (-1.35E+08)xCARit + (-0.001781)xTPFit + 11489190xROAit + (-
90710992)xLDRit + 1.75E+08xNPLit + (-85626115)xInflasiit + 5.54E+09xBIRATEit + eit
1.2.5. Interpretations
1) The result of panel data regression in Table 9. shows the CAR regression coefficient was -1.35E+08
and the probability value 0.0000 < 0.05 which states CAR has a negative and significant effect on the
distribution of MSME Investment Loans. These results accepted H2 hypothesis which states CAR has
a negative effect on the distribution of MSME Investment Loans. The results of this study support the
research conducted by Barus and Lu (2013) in the results of his research stated CAR negatively affect
the lending of SMEs. Riadi (2018) in the results of his research CAR has a significant effect on credit.
2) The result of panel data regression in Table 9. shows the TPF regression coefficient was -0,001781
and the probability value 0.0000 < 0.05 the TPF has a negative and significant effect on the
distribution of MSME Investment Loans. The result rejects the H4 hypothesis which states TPF has a
positive effect on the distribution of MSME Investment Loans. The results of this study support
research conducted by Sari and Abundanti (2016) in the results of his research that TPF has a positive
effect and significant to lending.
3) The result of panel data regression in Table 9. shows the ROA regression coefficient was 11489190
and the probability value of 0.8174 > 0.05 which states ROA has a positive and no significant effect
on the distribution of MSME Investment Loans. These results accepted the H6 hypothesis which states
ROA has a positive effect on the distribution of MSME Investment Loans. The results of this study
support research conducted by Sari and Abundanti (2016) in the results of his research states that ROA
has a positive and not significant effect on lending.
4) The result of panel data regression in Table 9. shows the LDR regression coefficient was -90710992
and the probability value 0.0000 < 0.05 which states LDR has a negative and significant effect on the
distribution of MSME Investment Loans. The results of this study support research conducted by
Barus and Lu (2013) in the results of his research states LDR has a negative and significant impact on
the MSME lending. Riadi (2018) in the results of his research states LDR has a significant effect on
credit. Santoso and Dewi (2017) in the results of his research states LDR has a significant effect on
lending.
5) The result of panel data regression in Table 9. shows the NPL regression coefficient was 1.75E+08
and the probability value 0.0000 < 0.05 which states NPL has a positive and significant effect on the
distribution of MSME Investment Loans. These results rejected the H10 hypothesis which states NPL
has a negative effect on the distribution of MSME Investment Loans. The results of this study support
the research conducted by Sari (2013) in the results of his research states NPL has a significant effect
on bank lending.
6) The result of panel data regression in Table 9. shows the regression coefficient of Inflation of -
85626115 and Probability 0.3188 > 0.05 which states that Inflation has a negative and no significant
effect on the distribution of MSME Investment Loans. The result accepts H12 hypothesis which states
Inflation has a negative effect on the distribution of MSME Investment Loans. The results of this
study support research conducted by Jenkins and Hussain (2014) in the results of his research stated
Inflation has a negative effect on Small and Medium Enterprise Bank Credit.
7) The result of panel data regression in Table 9. shows the regression coefficient of Bank Indonesia Rate
of 5.54E+09 and the probability value 0.0000 < 0.05 which states Bank Indonesia Rate has a positive
and significant effect on the distribution of MSME Investment Loans. These results rejected the
hypothesis H14 which states Bank Indonesia rate has a negative effect on the distribution of MSME
Investment Loans. The results of this study support research conducted by Sari (2013) in the results of
his research stated Bank Indonesia Rate has a positive and significant effect on bank lending.

CONCLUSIONS
1. Capital Adequacy Ratio (X1) has a negative and significant effect on the distribution of MSME Working Capital Loans.
The probability value of 0.0000 is less than 0.05 with a regression coefficient of -3.30E+08 which means that every increase
of CAR of 1% will reduce the distribution of MSME Working Capital Loans by IDR 330 million. Capital Adequacy Ratio
(CAR) also has a negative and significant effect on the distribution of MSME Investment Loans. The probability value is
0.0000 less than 0.05 with a regression coefficient of -1.35E+08 which means that every increase of CAR by 1% will
reduce the distribution of MSME Investment Loans by IDR 135 million.
2. Third Party Funds (X2) have a positive and significant effect on the distribution of MSME Working Capital Loans. The
probability value is 0.0000 less than 0.05 with a regression coefficient of 0.010572, which means that each DPK increase of
IDR 1 billion will increase the distribution of MSME Working Capital Loans with a value that is not too high. Third Party
Funds (DPK) have a significant negative effect on the distribution of MSME Investment Loans. The probability value of
0.0000 is less than 0.05 with a regression coefficient of -0.001781 which means that each DPK increase of IDR 1 billion
will reduce the distribution of MSME Investment Loans with a value that is not too large.
3. Return on Assets (X3) has a positive and insignificant effect on the distribution of MSME Working Capital Loans and
MSME Investment Loans. The probability value for Working Capital Credit is 0.2566 more than 0.05 with a regression
coefficient of 2.47E+08, while the probability value for Investment Credit is 0.8174 more than 0.05 with a regression
coefficient of 11489190.

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4. Loan to Deposit Ratio (X4) has a negative and significant effect on the distribution of MSME Working Capital Loans. The
probability value of 0.0000 is less than 0.05 with a regression coefficient of -4.71E+08, which means that each LDR
increase of 1% will reduce the distribution of MSME Working Capital Loans by IDR. 471 million. Loan to Deposit Ratio
(LDR) also has a negative and significant effect on the distribution of MSME Investment Loans. The probability value of
0.0000 is less than 0.05 with a regression coefficient of -90710992 which means that every LDR increase of 1% will reduce
the distribution of MSME Investment Loans by IDR. 90.7 million.
5. Non-Performing Loans (X5) have a negative and insignificant effect on the distribution of MSME Working Capital Loans.
The probability value of 0.3037 is more than 0.05 with a regression coefficient of -1.66E+08, inversely proportional to the
distribution of MSME Investment Loans which have a positive and significant effect. The probability value of 0.0000 is less
than 0.05 with a regression coefficient of 1.75E+08 which means that every increase in NPL of 1% will increase the
distribution of MSME Investment Loans by IDR 175 million.
6. Inflation (X6) has a negative and insignificant effect on the distribution of MSME Working Capital Loans and MSME
Investment Loans. The probability value for Working Capital Credit is 0.6708 more than 0.05 with a regression coefficient
of -1.75E+08, while the probability value for Investment Credit is 0.3188 more than 0.05 with a regression coefficient of -
85626115.
7. The Bank Indonesia Rate (X7) has a positive and significant effect on the distribution of MSME Working Capital Loans.
The probability value is 0.0000 less than 0.05 with a regression coefficient of 2.65E+10, which means that every 1%
increase in the Bank Indonesia Rate will increase the distribution of MSME Working Capital Loans by IDR. 26.5 billion.
The Bank Indonesia Rate also has a positive and significant effect on the distribution of MSME Investment Loans. The
probability value is 0.0000 less than 0.05 with a regression coefficient of 5.54E+09, which means that every 1% increase in
the Bank Indonesia Rate will increase the distribution of MSME Investment Loans by IDR 5.54 billion.

SUGGESTION
1) Capital Adequacy Ratio (CAR) is an important factor as a measure of bank health. The decline in the value of the CAR will
increase lending to MSME. This means that the bank has channeled a lot of credit resulting in an increase in Risk Weighted
Assets (RWA). The banks need to maintain capital balance by making additional capital deposits from shareholders and
from profit gains so that the CAR ratio is maintained according to the provisions.
2) Third-Party Funds (TPF) are factors that significantly influence the distribution of credit to MSME, but statistically only
increase with a nominal amount that is relatively small to increase in working capital loans and investment loans. This
reflects the still very low lending to the MSME sector with funding from the public. In this case, the Third-Party Fund can
still be optimized for distribution in the form of credit.
3) Return on Assets (ROA) has a low probability (probability 0.2566 for working capital credit and 0.8174 for investment
credit), thus it can be concluded that ROA is not too strong in influencing lending to MSME.
4) Loan to Deposit Ratio (LDR) is a factor that significantly influences lending to MSME. Each increase in the LDR will
reduce the distribution of working capital loans and investment loans. This illustrates the still low lending to the MSME
sector. Ideally, an increase in the LDR ratio will increase lending, in line with the Third-Party Funds that can still be used
by optimizing credit distribution.
5) Non-Performing Loans (NPL) have a significant influence on investment loan distribution but have no effect on working
capital loans. Every increase in NPL will increase the distribution of investment credit in the bank. This happened because
the percentage of investment credit distribution was lower than the working capital loan distribution. Management can
consider if the bank's NPL consolidation increases can further increase investment loan distribution.
6) Inflation has a low probability (probability 0.6708 for working capital credit and 0.3188 for investment credit), thus it can
be concluded that inflation is not too strong in influencing lending to MSME.
7) The Bank Indonesia Rate has a significant influence on the distribution of working capital loans and investment loans.
Every increase in the Bank Indonesia Rate actually increases lending. Bank management does not need to worry about
raising the interest rate reference from the central bank. It is expected that lending to the MSME sector can be optimized.

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Muhammad Aris Zulkarnain

Lambung Mangkurat University, Banjarmasin, South Kalimantan - Indonesia
Email: ariszulkarnain@gmail.com

Meina Wulansari Yusniar

Lambung Mangkurat University, Banjarmasin, South Kalimantan - Indonesia
Email: meina_unlam@yahoo.co.id

Asrid Juniar,
Lambung Mangkurat University, Banjarmasin, South Kalimantan - Indonesia
Email: asridjuniar@unlam.ac.id

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