1. Introduction
The main section of an article should start with an introductory section that provides more details about the paper’s purposes, motivation, research methods, and findings. The introduction should be relatively nontechnical yet clear enough for an informed reader to understand the manuscript’s contribution.
Indonesia was known as an agrarian country, which means a country that relied on the agricultural sector as a source of livelihood and development support (Central Bureau of Statistics, 2007). The agricultural sector was one of the main pillars based on the majority of the Indonesian population’s livelihood and the second largest contributor to GDP (Utama et al., 2019). However, most poor people in this country work in the agricultural sector. Although the agricultural sector contributed significantly to the national economy, many farmers still live below the poverty line. Omodero and Dandago (2020) showed the significant impact of agriculture on regional gross domestic product. The strategic role of the agricultural sector was explained in the contribution of the agricultural sector as a provider of food and industrial raw materials, contributor to GDP, foreign exchange earner, absorber of labor, primary source of rural household income, provider of feed and bioenergy, and has a vital role in efforts to reduce greenhouse gas emissions (Ministry of Agriculture, 2015).
Indonesia already had food granaries spread across various provinces. There were eight regions whose rice production was more significant than their consumption (Hikam, 2019). Indonesia planned to become a world of food barn targeted by the Indonesian government through the Ministry of Agriculture in 2045. During the golden era, Indonesia has declared sovereignty over rice, sugar, garlic, soybeans, rice, chilies, and shallots so that we were no longer an importing nation but an exporting nation (Cahyana et al., 2020).
During the 2015–2019 period, agricultural GDP showed significant growth. In 2017 and 2018, it reached 3.6%, a reasonably high increase compared to 2015 with a growth of 3.00%. Whereas in 2019, there was a decrease in growth compared to the previous year due to a decrease in the increase in food crop production due to the long dry season (Directorate General of Horticulture, 2019). According to the strategic plan, in 2020–2024 (Figure 1), the agricultural sector was a relatively significant contributor to GDP, although its role decreased due to the faster growth of the non-agricultural sector. In 2015, the agricultural sector’s contribution in a narrow sense (food crops, horticulture, plantation, and livestock sub-sectors) to GDP was 10.27%. In 2019, the agricultural sector’s contribution in a narrow sense indicated a transformation of the national economy, which was initially dominated by primary agricultural products in a narrow sense shifting to other sectors (Directorate General of Food Crops - Ministry of Agriculture, n.d.). The agricultural sector was one of the sectors that contributed to GDP and still has advantages and has promising opportunities for competitive advantage in world competition. No wonder the label of Indonesia as an agrarian country was still attached to this nation.
The agricultural sector could still develop, and more have progressed with the intake of capital that can cover the shortfall in the weak aspect of capital. Furthermore, the policy model provided by the government was suitable (Directorate General of Horticulture - Ministry of Agriculture, n.d.). Many aspects and sectors must be considered to support agriculture capital (Saragih, 2017). The capital aspect has always been a significant problem; due to limited capital, farmers cannot develop and produce sustainable agricultural products (Kopein et al., 2018). As time goes by, the need for capital will increase due to the continuous increase in the price of raw materials such as the price of fertilizer, land rent, seeds, pest control, and other things that support agriculture (Saragih, 2017).
Nowadays, the change of the perspective and treatment of the way in the management system in the agricultural sector, especially in capital resources, requires an agribusiness system so that the business actors in the agricultural sector can access it easily (Gumilang, 2017). Businessmen in the agricultural sector, especially farmers, could not finance their agricultural businesses with their funds. The role of financial institutions at this time was needed to support businesses in the agricultural sector financially. The government also continued to seek various things to support the financial aspect as stated in the 2020–2024 national agricultural development policy contained in the main program number 2, which reads, financing facilities and infrastructure (Ministry of Agriculture, 2020).
Currently, the government has provided financing facilities for farmers to facilitate access to capital. However, in its implementation, farmers found it difficult to get capital assistance, so the results were not as targeted. It was illustrated by the low realization of KUR distribution in the agricultural sector (Directorate General of Horticulture, 2019). The inability of farmers to access formal sources of capital was due to the difficulty and complexity of the procedures in applying for credit and the absence of collateral required in the application. In line with this question, Saragih (2017) explained that financing for the agricultural sector usually got loans far from financing rather than other sectors such as the industrial sector, trade, services, and other economic sectors. Funds transferred to finance economic/business activities that produce added value through the process of manufacturing, trade, or service delivery are referred to as financing activities (Muthoifin, 2021).
Financing was one of the crucial things in realizing a sustainable and profitable agricultural business. However, in the field, farmers’ access to finance was the main problem that farmers often complained about. It was due to the lack of information about financing that farmers could access. On the other hand, financial institutions still see and place the agricultural sector as a less attractive sector because it was considered a risky sector (high risk), depending on the season and uncertain price guarantees (Saqib et al., 2021).
The Islamic banking industry plays a critical role in the globalization of the Islamic financial system. When compared to other Islamic financial products, it still reigns supreme (Isnurhadi et al., 2021). Reporting from the OJK, after the development of the Sharia banking system in Indonesia, in the last two decades, the development of national Sharia finance has made much progress, both in terms of supporting institutions and infrastructure, regulatory tools, and supervisory systems, as well as in terms of public awareness and knowledge of services Sharia-based financial services (Financial Services Authority, 2015). However, Islamic banking literature includes studies from emerging markets and developing nations, whereas conventional banking literature includes reports from both developed and developing countries (Noor et al., 2020).
Islamic banks are distinguished from conventional banks by the prohibition of interest, excessive uncertainty, excessive gambling, funding for illegal activities, and the ethical basis and Shari’ah oversight boards (Khediri et al., 2021). The concept of Islamic financial institutions stands based on a prohibition on taking and giving loans in the form of interest, which in Islam includes usury, as well as a prohibition on investing close to things that were forbidden (Kaleem & Wajid, 2009). In practice, Sharia banks must use a profit-sharing system to stay away from interest practice which includes usury (Zulfikar & Sri, 2019). The profit sharing system determines the ratio or profit-sharing ratio based on profit and loss, so the financing system from Islamic banks was very suitable for financing the agricultural sector (Yulhana, 2017). As a whole way of life, Islam provided a comprehensive alternative way for farmers and Islamic banks to carry out various trade-based transactions that were commercially viable, feasible, and beneficial for all stakeholders. Financing transactions between Islamic financial institutions and farmers can be based on Murabaha Salam and Istishna contracts (Hussain & Saqib, 2017).
Although the agricultural business financing scheme is available, the condition of farmers was still faced with the small scale of land tenure and exploitation, which resulted in the limitation of farmers’ capacity and did not increase the capital through financing and investment institutions (Ministry of Agriculture, 2020). The portion of banking credit for the agricultural sector was far from the other sectors (Tsabita, 2014). The cause of the low credit allocation for the agricultural sector was because there was no particular program for the agricultural sector from the financing institution. Because the policies applied to the agricultural sector were the same and be as one with the financing policies for the non-agricultural sector, financing in the agricultural sector was not competitive. To ensure the availability of capital for farmers and agricultural business actors, it was necessary to have financing under the models and characteristics of the agricultural sector (Tsabita, 2014).
The policies in the distribution of loan funds for financing activities in the agricultural sector were influenced by two internal variables. The first variable originated from the internal bank, among others, relating to the ratio of Non-Performing Financing (NPF), the amount of Third Party Funds (TPF), the exchange rate, or the exchange rate of the IDR (rupiah) against the US dollar. Meanwhile, the following variable was a variable that came from outside the bank or was called an external variable. The variables were the interest rate for Bank Indonesia Sharia certificates (SBIS) and Islamic financing for the agricultural sector.
According to Sa’diyah (2019), Non-Performing Financing (NPF) or non-performing loans was a condition where the customer was unable to pay part or all of his obligations agreed with the BMT in the financing agreement. The cause of Non-Performing Finance (NPF) was due to financial difficulties faced by customers. Non-Performing Financing (NPF) could also occur due to factors recognized by financing officials due to elements of weakness both internally from the debtor, bank and external debtor, and bank (Sa’diyah, 2019). According to Kasmir (2015), the ability of Islamic banks to provide financing was strongly influenced by the ability of Islamic banks to absorb third-party funds from the public. Generally, the funds raised by banks from the public would be used to fund actual sector activities through lending. Based on the Sharia concept, the collection of funds from the public was carried out by Islamic banks using savings products, deposits, current accounts, which were usually referred to as Third Party Funds that use wadi’ah and mudharabah contracts (Kasmir, 2015).
According to Karim (2007), the Exchange Rate or Rupiah Exchange Rate, better known as the currency exchange rate, was a record (quotation) of the market price of each currency (foreign currency) in the price of the domestic currency, or domestic currency in foreign currency. Currency exchange rates described the level of exchange rates from one currency to another and were used in various transactions, including international trade transactions or short-term money rules between countries that cross geographical or legal boundaries (Karim, 2007). Based on Bank Indonesia Regulation No. 10/11/2008, Bank Indonesia Sharia Certificates, commonly referred to as SBIS, were short-term securities based on Sharia Principles in rupiah currency issued by Bank Indonesia. Bank Indonesia issued SBIS as one of the instruments for open market operations in monetary control based on Sharia principles (Bank Indonesia, 2008). This study aimed to examine the effect of the variables of Third Party Funds (TPF), Non-Performing Financing (NPF), Exchange Rates (ER), and Indonesian Sharia Securities on financing in the agricultural sector (PP). This study was expected to be a reference for business stakeholders’ agriculture and Islamic banking in improving the agricultural sector industry supported by Islamic financial institutions.
2. Literature Review
Hastuti and Arifin (2016), in their research, concluded that the TPF and FDR variables had a significant effect on the volume of financing. Meanwhile, the NPF variable did not affect the volume of financing. Karnasih and Purnomo (2017), in their research, showed that the USD/ IDR Exchange Rate (Exchange rate) in the short and long term has a significant effect on the Indonesian Sharia Stock Index (ISSI). In comparison, the error correction test showed that in the short term, the IDR/ USD Exchange Rate (Exchange rate) variable has a significant effect on the Indonesian Sharia Stock Index (ISSI). In the long run, the inflation variable, the value of Exchange of IDR/ USD (Exchange rate), Bank Indonesia Sharia Certificates (SBIS), the World Oil Prices have a significant effect on the Indonesian Sharia Stock Index (ISSI).
Beik and Aprianti (2013) stated that the bonus of Bank Indonesia Sharia Certificates, interest on Bank Indonesia Certificates (SBI), the equivalent rate of third party funds positively and significantly affects agricultural financing in the long term. Meanwhile, the number of third-party funds and conventional interest rates negatively affect agricultural financing. Furthermore, inflation and Non-Performing Financing (NPF) do not affect agricultural financing, both short and long term. Apriyanthi et al. (2020), in their research entitled “Factors that Influencing the Financing of the Construction Sector in Islamic Banking in Indonesia.” This research used multiple linear regression analysis methods. The results showed that the variables of NPF, Exchange Rate, and TPF affect the financing of the construction sector. The findings of this study contributed to Islamic Commercial Banks from the financial aspect, namely regarding the priority of the allocation of financing funds provided.
The research of Qolbi et al. (2020), showed that NPF, GDP, and interest rates simultaneously have an effect on ROA, and partially GDP had a positive and significant effect in the long and short term. NPF had a positive and significant effect in the long term. The interest rates have no significant effect on ROA. Meanwhile, the research that was conducted by Hasmarini and Azmi (2014) stated that inflation had a positive and significant effect on ROE, CAR had a positive and insignificant effect so the high and low CAR did not affect the level of profitability (ROE) of Islamic banking. The NPF variable had a negative and insignificant effect on the ROE of Islamic banks. From the distribution of funds other than financing, the bank will obtain income to increase profits.
In line with the research from Agustina and Purnomo (2014), the results showed that simultaneously buying and selling financing, profit-sharing financing, and NPF ratios have a significant effect on profitability as proxied through ROA. Partially, profit sharing and NPF ratios have no significant effect on ROA at Islamic commercial banks in Indonesia, so a decrease or increase in the amount of financing channeled by buying and selling contracts, profit sharing, and the level of non-performing financing do not affect the ROA value of Islamic commercial banks in Indonesia.
Research conducted by Soebagyo and Panjawa (2016) showed that in the long term and short term, the exchange rate variable had a significant positive effect, while inflation and the BI rate have a significant adverse effect on stock prices the Jakarta Islamic Index. This study had differences from previous studies. The first difference was the use of the OLS (Ordinary Least Square) method to estimate the variables that affected the Islamic financing of the agricultural sector. In addition, there was an update in the research year, where this research covered seven years from 2014 to 2020. Thus, it could be expected that this research could provide an update on which variables of this research affect Islamic Financing in the agricultural sector in Indonesia.
3. Research Methods and Materials
3.1. Data and Sources
This study used a quantitative approach and secondary data. The secondary data used in this study was the annual time-series data for 2014–2020. The secondary data sources used in this study were obtained from the Bank Indonesia (BI) website, namely the Rupiah exchange rate against the US Dollar and Islamic banking statistics, which came from the Financial Services Authority (OJK). The data source used was the number of Third-Party Funds (TPF). Non-Performing Financing (NPF), the exchange rate of the Rupiah against the US Dollar (Exchange Rate), and the Return of the Bank Indonesia Sharia Certificate (SBIS) for the Sharia Financing of the Agricultural Sector. The quantitative data analysis method in this research used the modified OLS (Ordinary Least Square) approach from Mughits and Wulandari (2016).
3.2. Model Specifications and Tools
\(Y=\widehat{\beta_{0}}+\widehat{\beta}_{1} X_{1}+\widehat{\beta}_{2} X_{2}+\widehat{\beta_{3}} X_{3}+\widehat{\beta_{4}} X_{4}+\varepsilon\)
Y = Agricultural Sector Sharia Financing
β0 = Interception or Constants
X1 = Third Party Funds (TPF)
X2 = Non-Performing Finance (NPF)
X3 = Exchange rate
X4 = Bank Indonesia Sharia Certification (SBIS)
ε = Error term/ Residual/ Error
3.3. Statistical and Econometric Analysis
The regression method used was as follows:
a) Estimated Ordinary Least Square (OLS)
The Ordinary Least Square (OLS) analysis method was first proposed by a mathematician from Germany named Carl Friedrich Gauss. The OLS method was used to analyze the relationship between the dependent and the independent variables. This method was one of the most powerful and widely used analytical methods (Gujarati & Porter, 2009).
b) Classical Assumption Test
The classical assumption test was an important step to do. If there were no symptoms of classical assump- tions, it was expected that a reliable regression model could be produced based on the Best Linear Unbiased Estimator (BLUE) rule, which produced an unusual and reliable regression model as an estimator (Sujarweni, 2015). The classical assumption test consisted of several tests, including the Normality Test, Multicollinearity Test, Autocorrelation Test, Heteroscedasticity Test, and Model Specification Test.
c) Model Goodness Test
The goodness-of-fit test of the model was conducted to determine whether the result of the regression model was feasible to be used as a basis for decision making. The goodness of this model includes testing the existence of the model (F-test), individual test (t-test), and interpretation of the regression determination coefficient (R2) (Ghozali, 2009).
3.4. Hypothesis
H1: Third-Party Funds (TPF) positively affected Islamic financing in the agricultural sector.
H2: Non-Performing Finance (NPF) had a negative effect on Islamic financing in the agricultural sector.
H3: The exchange rate had a negative effect on Islamic financing in the agricultural sector.
H4: Bank Indonesia Sharia Certificates (SBIS) had a negative effect on Islamic financing in the agricultural sector.
4. Results and Discussion
4.1. The Development of Sharia Banking in Sector of Agricultural Sharia Banking Commercial in Indonesia
According to Rivai and Arvian (2010), the term financing means trust, which is the bank trusting someone to carry out the mandate given by the bank as shahibul mal. These funds must be appropriately used fairly and accompanied by clear and mutually beneficial terms and conditions for both parties (Rivai & Arvian, 2010). According to Ilyas (2015), financing was funding provided by a party to another party to support planned investments, either by themselves or by institutions. In other words, financing was funding issued to support planned investments (Ilyas, 2015).
Based on Figure 1, it was known that Shariah Financing in the Agricultural Sector had increased every year and experienced a very significant increase in 2019 until it reached the highest point in September 2019, reaching IDR 13, 818 billion. It could be seen that every year the financing provided by Islamic Commercial Banks for the agricultural sector had increased, and the need for funds in the agricultural sector was also getting higher. Meanwhile, the lowest agricultural financing was in February 2015 of IDR 4, 152 billion. The average Agricultural Financing provided by Islamic Commercial Banks is IDR 7, 971 billion every year.
Figure 1: Graph of Agricultural Financing Development in Indonesia Source: OJK Shariah Banking Statistics
4.2. The Development of the Third Party Funds (TPF) in Sharia Commercial Banks
According to Aziz and Nurdiansyah (2021), Third Party Funds were funds entrusted by the public to banks based on fund deposit agreements made in three forms, namely demand deposits, time deposits, and savings. If the third party funds were increasing, the bank’s budget would also increase. The level of public trust in banks was measured by the size of the funds that have been collected by the bank (Aziz & Nurdiansyah, 2021). According to Hawa and Rosyidi (2019), it showed that the size of Third Party Funds affected the distribution of Islamic bank funds. Banks that had significant TPF make it possible to carry out large amounts of financing, which could benefit Islamic banks in generating time and running their operations every day (Hawa & Rosyidi, 2019).
Based on Figure 2, it was known that Third Party Funds (TPF) in Sharia Commercial Banks was continuously increased every year. It indicated that the public had great confidence in Islamic Banking in Indonesia. On the five year chart, Third Party Funds reached the highest value in December 2019 of IDR 288, 978 billion, while the lowest value was in June 2015 of IDR 162, 817 billion. The average for Third Party Funds (TPF) provided by Islamic Commercial Banks was IDR 217, 027 billion.
Figure 2: Graph of Third Party Fund Development in Indonesia Source: OJK Sharia Banking Statistics
4.3. The Development of NPF (Non-Performing Financing) in Sharia Commercial Banks
According to Almunawwaroh and Marliana (2018), in Sharia banks, the term Non-Performing Loan was changed to Non-Performing Financing (NPF) because Islamic banks were financing principles. NPF was the level of risk faced by banks. NPF was the amount of financing that was problematic, and there was a possibility that it could not be collected. In accordance with the rules set by Bank Indonesia, the amount of a good NPF was below 5%. NPF was measured by the ratio between the ratio of non-performing loans to the total loans granted. The larger the NPF, the lower the bank’s profit/ profitability because uncollectible funds resulted in reduced bank income so that banking profitability would be disrupted (Almunawwaroh & Marliana, 2018). According to Yulianto and Solikhah (2016), if the NPF ratio in a bank decreases, there will be a decrease in the number of deposits collected from customers. People’s desire to save or put their funds in Islamic banks would decrease because the bank cannot return the funds saved or will only get a small profit share (Yulianto & Solikhah, 2016).
Based on Figure 3, it could be seen that Non-Performing Financing (NPF) in Islamic commercial banks continued to decline. It indicated that Islamic banks were always careful when carrying out their functions in distributing funds to minimize the occurrence of jams, non-currents, and so on in the financing. The graph showed that the highest value was in May 2016, with an NPF value of 6.17%. Meanwhile, the lowest NPF value was in December 2019 at 3.23%. The average NPF ratio during 2015–2019 was 4.59%.
Figure 3: Graph of the Development of Non-Performing Financing (NPF) Source: OJK Sharia Banking Statistics
4.4. The Development of Exchange Rate IDR – USD
According to Karim (2013), the exchange rate compares the value/ price between the two currencies. The exchange rate was a record (quotation) of the market price of foreign currency in the price of the domestic currency or reciprocal, namely the price of domestic foreign currency against foreign currencies (Karim, 2013). According to Sukirno (2000), the exchange rate was the exchange between two different currencies, namely, comparing the value or price between the two currencies. This comparison of values was often referred to as the exchange rate. Exchange rates usually fluctuate. Changes in exchange rates can be in the form of depreciation and appreciation. The depreciation of the rupiah (IDR) against the US dollar decreased the price of the US dollar against the rupiah. Meanwhile, the rupiah’s appreciation against the US dollar was an increase in the rupiah against the US dollar (Sukirno, 2000).
In Figure 4, it was known that the Rupiah exchange rate against the US Dollar fluctuated and tended during 2015–2019. The highest exchange rate of the rupiah against the US dollar in October 2018 reached IDR 14, 869 thousand, while the lowest was in January 2015 of IDR 12, 579 thousand. The average exchange rate of the Rupiah against the US Dollar is IDR 13, 692 thousand.
Figure 4: Graph of the Development of the IDR-USD Exchange Rate Source: OJK Shariah Banking Statistics
4.5. The Development of Sharia Bank Indonesia Certificates
Based on Bank Indonesia regulation No. 10/11/2008, Bank Indonesia Sharia Certificates, commonly referred to as SBIS, were short-term securities based on Sharia Principles in rupiah currency issued by Bank Indonesia. Bank Indonesia issued SBIS as one of the instruments for open market operations in monetary control based on sharia principles. The regulation also explained that SBIS issued by Bank Indonesia used a ju’alah contract.
Based on Figure 5, it could be seen that Bank Indonesia Sharia Certificates fluctuated/ up and down during 2015–2019. It indicated that the excess funds held by Sharia banks also fluctuated. The highest SBIS value in the 2015–2019 period was IDR 8, 825 billion, while the lowest SBIS was in the month of IDR 3, 385 billion. The average Bank Indonesia Sharia Certificate during 2015–2019 was IDR 5, 670 billion.
Figure 5: Graph of Development of Valuable Bank Indonesian Sharia Certificates Source: OJK Sharia Banking Statistics
4.6. Estimation Results
To analyze the influence of the direction and amount of Third Party Funds (TPF), Non-Performing Financing (NPF), Exchange Rates, and the Bank Indonesia Sharia Certificates (SBIS) on Sharia Agriculture Sector Financing (PP) at Islamic Commercial Banks using the Regression Analysis Method of the Ordinary Least Square (OLS) and econometric models as follows:
\(\mathrm{PP}_{t}=\widehat{\beta_{0}}+\widehat{\beta_{1}} \mathrm{DPK}_{t}+\widehat{\beta_{2}} \mathrm{NPF}_{t}+\widehat{\beta_{3}} \mathrm{ER}_{t}+\widehat{\beta_{4}} \mathrm{SBIS}_{t}+\hat{\varepsilon}\)
Where:
PPt = Agricultural Sector Sharia Financing = Third-Party Funds
DPKt = Third-Party Funds
NPFt = Non-Performing Financing
ERt = Exchange rate
SBISt = Bank Indonesia Sharia Certificate
β0 = Constants
β1 β2 β3 β4 = Regression Coefficients
t = Year-level
ε = Error term
The estimation results of the econometric model above along with the complementary tests were as follows (Table 1).
Table 1: Econometric Model Estimation Results
*Significant on α = 0.01; **Significant on α = 0.05; ***Significant on α = 0.10. Numbers in brackets were empirical probabilities (p-value) t-statistics.
4.7. Classic Assumption Test
In this study, the method used to detect multicollinearity problems was to look at the Variance Inflation Factor (VIF) value. The formulation of the hypothesis was used to see the existence of a multicollinearity problem in the model is if VIF > 10, it means that there was a multicollinearity problem in the model. The results of the VIF Multicollinearity Test are presented in Table 1.
Autocorrelation will be tested by using the Breusch Godfrey test. There was no autocorrelation in the estimated model with the H0. While HA, there was autocorrelation in the estimated model. H0 can be accepted if the probability χ2 > α, and H0 was rejected if the significance of probability χ2 ≤ α. In Table 2, it was known that the value of χ2 was 0.0428 (> 0.01). It meant that H0 was accepted, then there was no autocorrelation problem in the model.
The model specification test was used to test the assumption of the linearity of the model. Thus, it was often called the linearity of the model. This study used the Ramsey RESET-test with the formulation of the hypothesis H0: linear model (correct model specification), and HA: nonlinear model (wrong model specification). The determined significance level (α) is 0.10 with the test criteria of the accepted H0 if F-count or sig. (F) > α, and H0 is rejected if F-count or sig. (F) ≤ α. The results of the Ramsey RESET- test in Table 1 showed that the significance or probability (F) was 0.9261 (> 0.10). It means that H0 was accepted, and the model used was a linear model with the correct specifications.
Residual Normality Test was tested using the Jarque-Bera test. H0 was the distribution of the estimated normal residual model, while HA was the distribution of the estimated residual model that was not normal. H0 was accepted if the probability or empirical statistical significance was JB > α, H0 was rejected if the probability or empirical statistical significance was JB ≤ α. In Table 1, it was known that the probability or statistical significance of 0.6387 (> 0.10), then H0 was accepted, the residual distribution of the model was estimated to be normal.
The heteroscedasticity test used in this study was the White test, with the formulation of the hypothesis H0: there was no heteroscedasticity problem in the model, while HA: there was a heteroscedasticity problem in the model. The test criteria H0 was accepted if the statistical significance or probability was χ2 > α, and H0 was rejected if the statistical significance was χ2 ≤ α. In Table 1, it was known that the statistical significance or probability of χ2 was 0.9261 (> 0.10), then H0 was accepted. There was no heteroscedasticity problem in the estimated model.
4.8. Model Goodness Test
The F-test was used to test the effect of all independent variables on the dependent variable simultaneously. This test was conducted to determine whether the model used exists or not, with the hypothesis formulation H0: = β1 = β2 = β3 = β4 = 0, the model used was not exist, and HA: ≠ β1 ≠ β2 ≠ β3 ≠ β4 ≠ 0, the model exists. The significance level (α) used was 0.10. The test-criteria H0 was accepted if the statistical probability F > α, and H0 was rejected if the statistical probability was F ≤ α. Table 1 showed that the statistical significance or probability value of F was 0.016 (< 0.10), so H0 was rejected. It can be concluded that the model used exists, and the independent variables affect the dependent variables simultaneously.
The coefficient of determination (R2) indicated the predictability of the estimated model. Based on Table 2, it can be seen that the magnitude of the coefficient of determination (R2) was 0.9919 or 99.91%. Thus, it can be concluded that the effect of the variables of Third Party Funds, Non-Performing Financing, Exchange Rates, and the Bank Indonesia Sharia Certificates is 99.91%. Meanwhile, the remaining 0.81% is influenced by other variables that are not included in the statistics.
The validity test of effects used in this study was the t-test, with the hypothesis formulation H0: βi ≤ 0; then, the TPF, NPF, ER, SBIS variables have no significant effect, and HA : βi > 0, then, the TPF, NPF, ER, SBIS variables have a significant effect. The test criteria H0 was accepted if the statistical significance ti > α, and H0 was rejected if the statistical significance ti ≤ α. The results of the t-test can be seen in Table 1.
4.9. Interpretation of the Effect of Independent Variables
Based on the results of the t-test in Table 1, it can be seen that the TPF and ER variables have a significant effect on PP. Meanwhile, the NPF and SBIS variables did not have a significant effect.
The TPF variable had a regression coefficient of 0.0414. The pattern formed between TPF and PP was linear. It meant that if TPF increased by one billion Rupiah, then, PP would increase by IDR 0.0414 billion. On the other hand, if TPF decreases by one billion Rupiah, then, PP will decrease by IDR 0.0414 billion.
The exchange rate (ER) variable has a regression coefficient of 1.4749. The pattern between the ER and the PP was linear-linear (lin-lin). It meant that if the exchange rate (ER) increased, it would cause PP to increase by IDR 1.4749 billion. On the other hand, if the exchange rate (ER) decreases, PP will decrease by IDR 1.4749 billion.
4.10. Economic Interpretation
During the observation period, from 2014 to 2020, the variables of Third Party Funds (TPF) and Exchange Rates affected the variable Islamic Financing for the Agricultural Sector (PP). Meanwhile, the variables of Bank Indonesia Sharia Certificates (SBIS) and Non-Performing Financing (NPF) did not affect the Agricultural Sector Islamic Finance (PP) variable.
4.11. The Effect of Third Party Funds (TPF) on Sharia Financing in the Agricultural Sector
Based on this research, Third Party Funds (TPF) had a positive effect on Sharia Financing for the Agricultural Sector. This finding is similar to Lestari (2019), who found that TPF that third-party funds have a considerable impact on agriculture funding. Third-Party Funds were one of the financial sources owned by a bank to carry out financing activities. By having a significant source of funds, banks could carry out channeling funds properly (Wardiantika & Kusumaningtias, 2014). It was the goal of Islamic banks to get profit so that the funds owned were not idle. Islamic banks tend to channel funds as much as possible to get the maximum profit (Aziz & Nurdiansyah, 2021).
4.12. The Effect of Non-Performing Financing (NPF) on Sharia Financing in the Agricultural Sector
Based on this research, Non-Performing Financing (NPF) had no effect on Sharia Financing for the Agricultural Sector. Islamic banking, with its fund distribution function in carrying out financing, always pays attention selectively and carefully to non-current financing. It was done to balance the financing carried out (Nugraha et al., 2019). A high level of NPF caused banks to experience difficulties and a decline in bank soundness to maintain a minimum NPF range of 5%. If the NPF level were above 5%, the bank would be careful and reduce the financing disbursed. This caution had reduced customer demand (Wardiantika & Kusumaningtias, 2014).
4.13. The Effect of Exchange Rates (ER) on Sharia Financing in the Agricultural Sector
Based on this research, the exchange rate positively influenced Islamic financing in the agricultural sector. Exchange rates were constantly moving and changing from time to time. In specific periods of economic turmoil, the exchange rate will move up and down, increasing the composition of financing (Fauziah, 2016). The strengthening of the Rupiah (IDR) exchange rate against the US Dollar, in this case, reflected the increasingly stable economic stability, which would reduce the risk of doing business. In the end, the business world would respond by increasing financing (Andriani, 2010). The effect of the exchange rate on the agricultural sector could also be seen from exports or imports of agricultural products (Asaleye et al., 2021).
4.14. The Effect of Bank Indonesia Sharia Certificates (SBIS) in Financing the Agricultural Sector Sharia
Based on this research, Bank Indonesia Sharia Certificates (SBIS) did not have a significant effect on Islamic financing in the agricultural sector. The higher the allocation of funds in Bank Indonesia Sharia Certificates, the higher the amount of disbursed financing will be at an insignificant level. The increase in funds from the profits of the allocated distribution to SBIS caused a decrease in the value of financing disbursed (Majid & Rusli, 2020).
5. Conclusion
Based on the research results, it can be concluded that the model used in this research met the classical assumption test that showed a normal residual distribution, there was no multicollinearity problem, there was no autocorrelation in the model, there was no heteroscedasticity problem, and the model used was linear. Partially, the research results showed that the variables of Third Party Funds (TPF) and the Exchange Rates (ER) affected the Sharia Financing for the Agricultural Sector (PP). Meanwhile, the variables of Non- Performing Financing (NPF) and Bank Indonesia Sharia Certificates (SBIS) did not affect Islamic Agriculture Sector Financing (PP). Simultaneously, the variables of Third Party Funds (TPF), Non-Performing Financing (NPF), Exchange Rates, and the Bank Indonesia Sharia Certificates (SBIS) affected the Islamic Agriculture Sector Financing (PP) in Indonesia. The value of the coefficient of determination (R2) was 0.9919, meaning that 99.91% of the variation in the variable of Sharia Financing in the Agriculture Sector can be explained by the variables of Third Party Funds, Non- Performing Financing, Exchange Rates, and Bank Indonesia Sharia Certificates. The remaining 0.18% was explained by other variables. This study provided advice to Islamic Banking in Indonesia to prioritize the use of third-party funds from the public for the agricultural sector because it was following the character of the Indonesian nation as an agrarian country. Islamic banking also needs to develop Islamic financing products that follow the characteristics of the business sector in the agricultural sector.
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