##plugins.themes.bootstrap3.article.main##

Micro and Small Enterprises (MSEs) have an important and strategic role in the national economy. MSEs have received considerable attention from various groups, both from the government and financial institutions because they have proven to be part of the savior of the national economy which was experiencing a downturn at that time. The government and financial institutions have made various efforts to support the progress of MSEs, one of which is by providing business capital loans. Therefore, it is necessary to analyze the benefits of providing capital loans to MSEs. The research aims to: [1] analyze the benefits of credit that has been distributed by PT BPR Martapura Banjar Sejahtera and [2] analyze the factors that influence the decision of micro and small enterprises MSEs in agriculture to take credit at PT BPR Martapura Banjar Sejahtera. The data analysis method used in this research is quantitative descriptive analysis. The sampling method used is proportionate random sampling and accidental sampling. Data were analyzed through: [1] descriptive, [2] scoring method, and [3] tested through binary logistic regression. The results showed that the credit channeled by PT BPR Martapura Banjar Sejahtera to agricultural MSEs in Banjar Regency is effective in increasing the turnover of MSEs. It is also known that the variables of business risk and credit socialization are variables that significantly influence the decision of micro and small enterprises of MSEs in agriculture to take credit at PT BPR Martapura Banjar Sejahtera.

Introduction

Micro and small enterprises (MSEs) in the agricultural sector have emerged in recent decades and these MSEs have been able to survive the national economic downturn. The existence of MSEs, which have limited capital constraints, has even been able to sustain the national economy from the global economic downturn. Although the role of MSEs in the national economy is very important, MSEs still face obstacles both in obtaining financing assistance and in developing their businesses. In terms of financing problems, there are still MSE actors who experience limitations in accessing credit from banks or other financial institutions. These limitations include technical limitations such as not having or insufficient collateral, and non-technical limitations such as lack of access to information from banks or other institutions. In terms of business development, MSE actors still have difficulties in obtaining information related to the financing mechanism for a product.

The government has made efforts to improve the accessibility of MSEs and the availability of capital sources through various programs such as the development of microfinance institutions and various other programs. However, there are still many micro and small business actors who only use their own capital to build and develop their businesses, even though there are already several financial institutions that carry out financing functions such as State-Owned Commercial Banks, National Private Banks, Foreign Banks, Regional Development Banks, Rural Banks, and Non-Bank Financial Institutions. One of the credit service providers operating to provide micro business loans in Banjar Regency is PT BPR Martapura Banjar Sejahtera. PT BPR Martapura Banjar Sejahtera is a Regionally Owned Enterprise (BUMD) owned by the Banjar Regency Government and is engaged in banking. This study aims to analyze the benefits of providing credit to MSEs in agriculture that have been channeled by PT BPR Martapura Banjar Sejahtera as a financial institution owned by the Banjar Regency Regional Government towards improving the welfare of MSEs and what factors influence the decision of agricultural MSEs in taking credit at PT BPR Martapura Banjar Sejahtera.

Materials and Methods

Place and Time Research

This research was conducted since March 2023. The research location is Banjar Regency, South Kalimantan Province with 30 respondents who are credit customers at PT BPR Martapura Banjar Sejahtera and 30 respondents who are not customers of PT BPR Martapura Banjar Sejahtera.

Data Type and Source

The data collected in this study include primary and secondary data. Primary data is data obtained from agricultural MSE actors who are credit customers of PT BPR Martapura Banjar Sejahtera and agricultural MSE actors who do not take working capital loans through interviews using a list of questions arranged on a Guttman scale. Meanwhile, secondary data is data obtained in the form of documents, reports that support from various sources including from BPS Banjar Regency and PT BPR Martapura Banjar Sejahtera.

Sampling Methods

The sampling method used to analyze the first problem formulation is proportionate random sampling. In this method, sampling from each member of the population gets the same opportunity to be sampled proportionally. The sample criteria to be used are: [1] MSE actors in the agricultural sector which includes agriculture, fisheries and livestock businesses [2], MSE actors who take credit at PT BPR Martapura Banjar Sejahtera and have been running for at least one year [3]. The credit taken is working capital credit, and [4] The length of business is more than two years. In an effort to see the benefits after being given capital credit. To analyze the second problem formulation, proportionate random sampling and accidental sampling methods were used. Samples were selected without prior planning and taken based on research needs.

The results of various sampling methods and taking into account the sampling rules mentioned above, the number of samples used in this study were 30 samples of PT BPR Martapura Banjar Sejahtera customers and 30 non-customer samples taken accidentally.

Research Variables

The object of this study is the decision of business actors in taking credit. The decision to take credit (Y) is a dependent variable, where the provisions of number 1 are categorized as high desire to take credit and number 0 as low desire to take credit. Meanwhile, the independent variables in this study were business experience (X1), business scale (X2), business risk (X3), credit access (X4) and credit socialization (X5).

Research Hypothesis

The research hypothesis is a temporary answer to the problem, basic theoretical, literature review and then tested through data collected in the field. Based on this, the research hypothesis is:

  1. There was an increase in turnover after the credit from PT BPR Martapura Banjar Sejahtera.
  2. There is a significant influence between business experience, business scale, business risk, credit access and credit socialization on the decision of micro and small businesses in agriculture to take credit at PT BPR Martapura Banjar Sejahtera.

Data Analysis

The data analysis method used to analyze the first formulation in this study is quantitative descriptive analysis. This analysis aims to create a picture based on existing data and then tested with a paired sample t-test analysis to see the difference between before and after obtaining PT BPR Martapura Banjar Sejahtera credit which includes an increase in business turnover.

To analyze the formulation of the second problem, data analysis is carried out by giving scores to respondents from a list of questions (questionnaires), which are then processed with a Guttman scale. In this study, the Guttman scale is used to analyze the factors that influence the decision to take credit from PT BPR Martapura Banjar Sejahtera with the following criteria: [1] 0%–50% means that MSE actors are categorized as low willingness to take credit, and [2] 51%–100% means that MSE actors are categorized as high willingness to take credit.

Furthermore, binary logistic regression analysis was conducted. This analysis is an equation model for categorical data analysis where the dependent variable consists of two categories (binary) and the independent variable is a categorical or continuous variable with the following stages: [1] model building [2], Goodness of Fit testing [3], simultaneous testing [4], partial testing, and [5] odds ratio.

Results and Discussion

Characteristics of Respondents

Gender, based on the gender characteristics of the respondents, it can be seen that the overall respondents used in this study were mostly male respondents, namely a total of 38 male respondents (63%). While the total number of female respondents was 22 people (37%). This is because men are more productive in increasing family income. However, both men and women can open businesses that start from micro businesses. With perseverance and hard work, it will increase everyone’s income even if they do not have a high level of education. Characteristics of respondents based on gender can be seen in the following Table I.

Gender Customer Non-customer
Person % Person %
Man 15 50 23 77
Woman 15 50 7 23
Total 30 100 30 100
Table I. Gender Characteristics of Respondents

Age, respondents aged less than equal to 25 years were 2 people (3%) of the total respondents, for ages 26–35 years were 20 respondents (33%), ages 36–45 years were 22 people (37%) and ages over 45 years were 16 people (27%). Based on the age of the respondents used in this study, the most respondents were aged 36–45 years, namely 22 people (37%) of the total respondents.

People with an age range of 26–45 years are included in the highly productive age group because ages under 20 years are considered to be individuals who do not have sufficient maturity and are also still in the education process. Meanwhile, at the age of over 45 years, there is a decline in physical ability so that productivity has decreased. People in this age range already have enough experience in doing business because they are considered capable in the labor process and have the burden of supporting the lives of residents who fall into the category of unproductive and non-productive populations. The characteristics of respondents based on age can be seen in the following Table II.

Ages (years) Person Percentage (%)
≤25 2 3
26–35 20 33
36–45 22 37
>45 16 27
Total 60 100
Table II. Age Characteristics of Respondents

Level of Education, the education that a person has undergone is certainly not the same between one individual and another, thus instilling a different mindset where different mindsets can certainly influence a person’s behavior in making credit decisions. The last education of respondents at the SD/MI level was 12 people (20%) of the total respondents. At the SMP/MTs level there were 11 people (18%), and the SMA/SMK/MA level was 19 people (32%) while the D3/S1 level was 18 people (30%).

This happens because the higher a person’s level of education will affect the level of productivity of a person in business and affect the income earned. Between the level of education and the level of income, there is a relationship, namely that human resources are able to improve their quality of life through a process of education, training and development which ensures increased work productivity. The characteristics of respondents based on education level can be seen in the following Table III.

Level of education Person Presentage (%)
Elementary/middle school (SD/MI) 12 20
Junior/senior high school (SMP/MTs) 11 18
SMA/SMK/MA 19 32
D3/S1 18 30
Total 60 100
Table III. Education Level of Respondents

Benefits of Lending

Credit not only provides benefits to individuals, but can also provide broad benefits to society, including to increase economic stability and increase community income. People who have a business, in this case MSE actors, can obtain business capital credit from financial institutions in order to fulfill the capital needed to strengthen the capital structure and develop their business.

The credit provided can be utilized properly by MSE actors in accordance with their business wants and needs. Therefore, the existence of this credit can increase the income of MSE actors. This increase in business income can be seen from the increase in turnover received by business actors. The turnover assessed is the overall income/gross income received by MSE actors for a year before receiving credit and a year after receiving credit. In this study, the research respondents were business actors who were customers of PT BPR Martapura Banjar Sejahtera totaling 30 people with a range of capital loans received which can be seen in the following Table IV.

Loans received (Rp) Respondents Percentage (%)
<10,000,000 11 36.67
10,000,000–50,000,000 12 40.00
51,000,000–100,000,000 4 13.33
>100,000,000 3 10.00
Total 30 100
Table IV. Credit Received by Respondents

Based on Table IV, the most credit received by respondents is in the range between Rp10,000,000–Rp50,000,000 with a total of twelve respondents (40%) consisting of 8 people from the agricultural business sector, 2 people from the fisheries sector and 2 people from the livestock business sector. The 8 respondents in the agricultural sector are mostly rubber farmers who also have a business selling rubber products, 2 respondents in the fisheries sector are MSE actors processing fish products, namely making mpek-mpek and fish chips, and 2 people from the livestock sector who are MSE actors buying and selling duck eggs and young duck meat. Most of the respondent MSEs are business actors engaged in the downstream agribusiness subsystem. Downstream agribusiness is an activity in post-harvest handling and processing of agricultural products into various kinds of processed products and derivative products (agro-industry). In downstream agribusiness subsystem more emphasized on marketing activities, with the form of product sales can be in the form of primary materials, semi-processed and processed materials ready to be served. The activities carried out by respondents include rubber farmers but mostly carry out activities to buy and sell rubber products, fish processing businesses such as crackers, mpek-mpek, fish chips and business actors who carry out marketing activities for duck eggs and young duck meat.

With the capital credit received by MSE actors, there was a significant increase in income. The increase in income in this study is seen from the amount of turnover received by MSE actors during the year after receiving credit. MSE actors who are respondents are customers who started receiving credit in January–March 2022, either for the first time or customers who extend credit, so that the calculation of turnover in this study is the turnover received by MSE actors for a year before receiving credit, namely the turnover received in 2021 and a year after receiving business capital credit, namely in 2023 based on the classification of business fields can be seen in Fig. 1 above.

Fig. 1. Changes in average turnover before and after receiving credit.

The highest increase in turnover occurred in the agriculture business sector, which increased from Rp64,494,737 to Rp161,473,684 (150.37%). The average turnover of all business sectors before receiving credit was Rp248,650,292, and the average turnover after a year of MSEs receiving credit was Rp606,762,573. This shows that the credit received by MSE actors provides very significant benefits to the increase in business turnover of MSE actors. The average increase in turnover that occurred was 144.02%.

If the credit provided can be utilized properly by MSE actors in accordance with their business needs, the business can experience an increase in turnover which can then have an impact on increasing the income and welfare of the MSE actors. With the increase in turnover of all MSE actors who were respondents in this study, there is no need to test again with a paired sample t-test analysis.

Factors that Influence Credit Decision Making

The test results in this study were carried out with validity and reliability tests. The validity test is used to measure whether a questionnaire is valid or not. A questionnaire can be said to be valid if it is able to explain what the questionnaire will measure. Validity testing is done using SPSS by looking at the significance value. In the validity test that has been conducted on 60 respondents of MSE actors in Banjar Regency, it shows that the significance value of the entire instrument used to test each variable, namely the variables of business experience, business scale, business risk, credit access and credit socialization, is smaller than α (0.05) so that it can be declared valid. The next analysis is the reliability test. The reliability test is carried out to determine whether the questionnaire used is said to be realibel or reliable if the answers to the questions are consistent over time. An instrument is said to be reliable if the Cronbach Alpha value is >0.60 [7]. In the reliability test that has been carried out on 60 respondents of MSE actors in Banjar Regency, it shows that the Cronbach Alpha value is >0.60. This shows that all research variables have met composite reliability and have a high reliability value, which means that the questionnaire used is reliable.

After conducting the validity test and reliability test above, then proceed with binary logistic regression analysis. Binary logistic regression analysis in this study is used to determine the effect of business experience (X1), business scale (X2), business risk (X3), credit access (X4) and credit socialization (X5) on the decision of MSE actors in taking credit at PT BPR Martapura Banjar Sejahtera.

Goodness of Fit, the test used in this study is the Hosmer and Lemeshow Goodness of Fit Test. In this test, the hypothesis used is as follows:

H0: The model does not fit.

H1: The model is fit.

Based on the Hosmer and Lemeshow Goodness of Fit Test, significant value of chi-square is 0,814. This significance value is greater than the α used, which is 0.05. It can be concluded that the decision to reject H0 or can mean that the regression model is appropriate/fit with the data used so that parameter testing can be carried out. The overall percentage value is 80%. This value indicates that the model as a whole has the ability to predict business decisions in taking credit well, which is 80%.

Simultaneous Testing, the simultaneous test results obtained by comparing the value of the G test statistic with the value of α (0.05) can be seen from Table V. Table V shows that the significance value of the G test statistic is 0.000 with a chi-square value of 35.649. The value is compared with α (0.05) which results in the conclusion of rejecting H0 because the significance value is smaller than α (0.05), so it can be concluded that there is at least one explanatory variable that significantly affects the decision of MSE actors in taking credit at PT BPR Martapura Banjar Sejahtera.

Chi-square df Sig.
Step 35.649 5 0.000
Block 35.649 5 0.000
Model 35.649 5 0.000
Table V. Results of G Test Statistics

Partial Testing and Odds Ratio, the next stage is to conduct partial parameter testing in order to determine how many independent variables have a significant influence on the decision of MSE business actors to take credit in Banjar Regency. Partial parameter testing is conducted with the Wald test statistic. In partial testing, the hypothesis used is as follows:

H0: j = 0

H1: j ≠ 0

In Table VI, shows that the independent variables that have a significant effect on the decision of MSE actors in taking kerdit at PT BPR Martapura Banjar Sejahtera are variables of business risk and credit socialization. Business risk has a positive sign and a significance value of less than α (0.05), namely 0.002, so it can be concluded that the decision to reject H0. This means that business risk has a positive and significant influence on the decision of MSE actors in taking credit. Likewise, the credit socialization variable has a positive sign and a significant effect on the decision of MSE actors in taking credit with a significance value of 0.005, so it can be concluded that the decision to reject H0. This means that credit socialization also has a positive and significant influence on the decision of MSE actors in taking credit.

Variables Koef B Sig. Exp (B)
Business experience −0,214 0,027 0,807
Business scale −0,061 0,782 0,941
Business risk 3,760 0,002 42,961
Credit access 0,008 0,770 1,008
Credit socialization 3,592 0,005 36,307
Constant −4,460 0,017 0,012
Table VI. Partial Test with Wald Analysis

The business experience variable has a negative sign but has a significance value of 0.027 smaller than α (0.05), which means that business experience has a significant effect on credit decision making but has a negative relationship. This can mean that there are other variables that affect business experience but are not included in this study. The business scale variable has a negative sign and has no significant effect on credit decision making because the significance value of the business scale is greater than α (0.05), namely 0.782, so it can be concluded that the decision fails to reject H0. The credit access variable has a positive sign but is not significant because the significance value of credit access is greater than α (0.05), namely 0.770. The credit access variable has a positive sign but its significance value is 0.770, which means it is greater than α (0.05), so it can mean that credit access has a positive but significant effect on business decisions in taking credit.

From the partial test results and the decision to keep all variables in the regression model, the binary logistic regression equation formed is as follows: g⌢(x)=−4,460−0,241X1−0,061X2+3,760X3 +0,008X4+3,592X5

Description:

X1 = Business Experience

X2 = Business Scale

X3 = Business Risk

X4 = Access to Credit

X5 = Credit Socialization

The next step is the interpretation of the odds ratio of the research variables. The odds ratio value of the business experience variable is 0.807, which means that the tendency of business actors’ willingness to take credit is times higher. The odds ratio value of the business scale variable is 0.941, which means that the tendency of business actors’ desire to take credit is times higher. The odds ratio value of the business risk variable of 42.961 means that high business risk has a tendency for business actors to take credit of 42.961 or 43 times greater than low risk business actors. The odds ratio value of the credit access variable of 1.008 means that the tendency of business actors’ willingness to take credit is times higher. The odds ratio value of the credit socialization variable of 36.307 means that the existence of socialization has a tendency for business actors to take credit of 36.307 or 36 times greater than the absence of credit socialization.

Independents Variables

Business Experience, the slope value for the business experience variable is −0.241, but has a significance value smaller than α (0.05), namely 0.027 so that business experience has a negative relationship with credit decision making but can have a significant effect on credit decision making. High business experience but low desire to take credit is due to the fact that the MSEs who are respondents in this study already have a stable or established business in terms of income so that they have sufficient capital and do not wish to take credit.

Socioculturally, the community in Banjar Regency is known as a religious community, so financial transactions involving interest on loans are avoided. This causes the high level of business experience in this study to have no effect on the willingness of business actors to take credit.

Business Scale, the slope value for the business scale variable is −0.061, has a negative relationship with the decision to take credit and a significance value of 0.782. The business scale in this study focuses on the number of workers. Respondents in this study were dominated by business actors categorized as micro-scale businesses that mostly conduct household businesses. Most of these MSE actors find it difficult to develop their businesses because they have limited business capital so they really need additional capital. However, this is not the case with a business scale with a larger number of workers whose desire to take credit is lower. This is because MSEs with a large workforce already have a stable or established business in terms of income, so they already have sufficient capital and do not wish to take out credit. In addition, this group of MSEs has no plans to increase the scale of their business, so they feel that they do not need additional capital through credit mechanisms.

Business Risk, the slope value of the business risk variable is 3.760, has a positive relationship and has a significant effect on credit decision making with a significance value smaller than α (0.05), namely 0.002. Business risk is the result of business or business activities that cause several problems or losses in a certain period of time. The greater the risk that occurs in a business, the greater the chance that the business will experience losses, so that business actors have a high desire to apply for credit at financial institutions. Due to conventional bank policies, especially in terms of the nature of collateral to be submitted, most businesses in Banjar Regency that are high risk find it difficult to access such credit, so these businesses choose to take credit at PT BPR Martapura Banjar Sejahtera.

In addition, the Banjar Regency Government [6] has a program called “Kurma Manis” (Kredit Usaha Rakyat Martapura Maju Mandiri dan Agamis), which is a business capital loan program for businesses in agriculture, fisheries, livestock, trade, small industries and others with 0% interest or no interest and no administration fees channeled through PT BPR Martapura Banjar Sejahtera. The Kurma Manis program has attracted many MSEs to apply for credit at PT BPR Martapura Banjar Sejahtera, including high risk customers.

In mitigating the risks arising from high risk MSE loans, PT BPR Martapura Banjar Sejahtera has ensured that the collateral received can be used to mitigate the risks when the debtor (MSE) defaults. The form of collateral submitted is specific to the business activities financed and PT BPR Martapura Banjar Sejahtera ensures that the collateral has sufficient value in the event of default, although the collateral set is still below conventional banks. This is what causes some MSE actors whose credit applications to conventional banks are rejected to switch to applying for credit to PT BPR Martapura Banjar Sejahtera. Based on these conditions it can be concluded that the higher the business risk of MSE actors, the higher the desire of MSE actors to take credit at PT BPR Martapura Banjar Sejahtera.

Credit Access, the slope value of the credit access variable is 0.008, has a positive relationship with credit decision making and a significance value of 0.770. Credit access in this study focuses on the distance from the respondent’s residence to the PT BPR Martapura Banjar Sejahtera office. Respondents in this study were dominated by respondents who had a closer distance to the PT BPR Martapura Banjar Sejahtera office. The closer the distance so that access to information related to credit programs will be easier to obtain, besides that it also affects the ease when verifying collateral and the completeness of other credit requirements.

Based on the results of this study, close location distance does have a positive effect but does not have a significant effect on the decision to take credit from MSEs, so it can be concluded that the distance between the location of respondents and the PT BPR Martapura Banjar Sejahtera office does not affect the decision of MSEs in Banjar Regency to take credit.

Credit Socialization, the slope value of the credit socialization variable is 3.592, has a positive relationship and a significant effect on the decision to take credit with a significance value smaller than α (0.05), namely 0.005. Credit socialization is the provision of information by PT BPR Martapura Banjar Sejahtera and other parties to MSE actors in order to know the benefits and requirements of taking credit both from bank officers and from the community who have first become customers of PT BPR Martapura Banjar Sejahtera.

From this study it is found that the higher the socialization of credit, the higher the desire to take credit. This is because PT BPR Martapura Banjar Sejahtera has conducted massive socialization, both through marketing officers and people who have become customers. In addition, with the “Kurma Manis” program (Kredit Usaha Rakyat Martapura Maju Mandiri dan Agamis) which is a business capital loan program to business actors in the fields of agriculture, fisheries, animal husbandry, trade, small industry and others with 0% interest or no interest and no administrative costs channeled through PT BPR Martapura Banjar Sejahtera, the Banjar Regency Regional Government [6] and FORKOPIMDA have participated in socialization activities so as to increase the interest of MSE actors to take credit.

Conclusion

Credit channeled by PT BPR Martapura Banjar Sejahtera to MSEs in Banjar Regency is very effective in increasing business turnover with a percentage increase of 144.02%. The increase in turnover in the agricultural business sector amounted to 150.37%, fisheries 134.92% and livestock 150%.

Factors that have a positive and significant effect on the decision of MSE actors in taking credit at PT BPR Martapura Banjar Sejahtera are business risk and credit socialization. The higher the business risk of MSE actors, the higher the desire of MSE actors to take credit, and the more intense the socialization carried out, the higher the desire of MSE actors to take credit at PT BPR Martapura Banjar Sejahtera.

References

  1. BPS Kabupaten Banjar. Kabupaten Banjar Dalam Angka 2023. Kabupaten Banjar, Indonesia: CV Karya Bintang Musim; 2023.
     Google Scholar
  2. Efriyenty Dian, Viola Syukrina E Janrosl. Analisis faktor-faktor yang mempengaruhi pengambilan kredit oleh pelaku usaha kecil menengah pada debitur bank perkreditan rakyat Kota Batam. Akrab Juara: Jurnal Ilmu-Ilmu Sosial. 2017 June;2:46–54, Indonesia.
     Google Scholar
  3. Ghozali I. Aplikasi Analisis Multivariate dengan Program IBM SPSS 21 Update PLS Regresi. Semarang, Indonesia: Badan Penerbit Uni- versitas Diponegoro; 2013.
     Google Scholar
  4. Kasim F. Metodologi Penelitian Biomedis. Bandung, Indonesia: PT Danamartha Sejahtera Utama; 2008.
     Google Scholar
  5. Kasmir. Analisis Laporan Keuangan. Jakarta, Indonesia: Edisi Per- tama. PT Raja Grafindo Persada; 2014.
     Google Scholar
  6. Pemerintah Kabupaten Banjar. Kajian Analisis Kelayakan Kebi- jakan Pemberian Pinjaman Kepada Masyarakat Dalam Bentuk Kredit Modal Usaha Mikro. Kabupaten Banjar, Indonesia: Pemerintah Kabupaten Banjar; 2021.
     Google Scholar
  7. Sugiyono. Metode Penelitian Kuantitatif, Kualitatif dan R&D. Bandung, Indonesia: CV Alfabeta; 2016.
     Google Scholar