17
The Effect of Non Performing Loan, Loan to Deposit Ratio, Receivable Turnover on Return on Assets in Banking Subsector Companies Listed on The Idx 2016-
2018
M Fahrul Rohman
Departement of Management, Narotama University Surabaya Jl. Arief Rachman Hakim No. 51 Surabaya, Indonesia
Abstract
This study aims to analyze the effect of Non Performing Loan (NPL), Loan to Deposit Ratio (LDR), and Receivable TurnOver (RTO) on Return On Assets (ROA) in banking companies listed on the Indonesia Stock Exchange 2016-2018. The population of this research is banking companies listed on the Indonesia Stock Exchange during 2016-2018. The sample used was 42 banking companies using purposive sampling method and 10 companies were selected. Data learning techniques with documentation in the form of secondary data and library research. Analysis of the data of this study using Multiple Linear Regression. The results of this study are partially Non Performing Loan (NPL) and Loan to Deposit Ratio (LDR) have a negative and insignificant effect on Return On Assets (ROA), and Receivable TurnOver (RTO) has a significant positive effect on Return On Assets (ROA). Then simultaneously Non Performing Loan (NPL), Loan to Deposit Ratio (LDR), Receivable TurnOver (NPL) have a significant positive effect on Return On Assets (ROA).
Keywords :
Loan to Deposit Ratio (LDR), Non Performing Loan (NPL), Receivable TurnOver (RTO), Return on Assets (ROA)
1. Introduction
In Indonesia, the development of the banking sector is very interesting to observe, because the strength of the banking system is an important requirement to ensure economic stability and growth. Banking which has a very vital role in the area of national objectives related to increasing and equalizing the level of society. Banks are an industry that in their business activities rely on public trust so that the soundness of the bank should be maintained. To maintain this function, banks must maintain the continuity of their operational activities by generating profit as possible so that their profitability continues to increase. Profitability is the most appropriate indicator to measure the performance of a bank. Profitability in the banking world can be calculated by means of ROA (Return on Assets). ROA is important for banks because ROA is used to measure the effectiveness of a company in generating profits by utilizing the assets it owns.
Return on Assets (ROA) is used to measure bank profitability, because Bank Indonesia as a supervisor and bank supervisor prioritizes the profitability value of a bank as measured by assets whose funds are mostly from public deposits. The greater the ROA of a bank, the greater the level of profit achieved by the bank, and the better the position of the bank in terms of asset use.
Figure 2. The Development of Return on Assets (ROA) on The Indonesia Stock Exchange in 2016 - 2018 Resource : www.idx.co.id, processed data
18
Based on the information above, it can be seen that the average Return on Assets of banking companies listed on the Indonesia Stock Exchange in 2016 - 2018 is in good condition. This is also supported by the average increase in the 2016 - 2018 period. One of the important information in finance is information regarding profitability. This information is very important because profitability explains how the company has performed in one period in the past period. A bank's financial performance can be assessed from the bank's financial ratios, such as the ratio of Net Performing Loan (NPL), Loan to Deposit Ratio (LDR), and Receivable Turnover (RTO).
Based on the description above, the authors are interested in conducting research in the title: "The Effect of Non Performing Loan, Loan To Deposit Ratio, Receivable Turnover on Return on Assets in Banking Subsector Companies Registered in Bei 2016-2018".
2. Literature Review 2.1. Return on Assets (ROA)
Return on Assets (ROA) is a profitability ratio that measures the company's ability to generate profits from the assets used. ROA is able to measure the company's ability to generate profits in the past to then be projected in the future. Assets or assets in question are all company assets obtained from own capital or fro m foreign capital that the company has converted into company assets which are used for the survival of the company. Return On Assets is used to evaluate whether management has received an adequate return from the assets it controls. This ratio is a useful measure if one wants to evaluate how well the company has used its assets. Therefore ROA is often used by top management to evaluate business units within a multinational company (Simamora, 2000). According to Kasmir (2014) Return on Assets is a ratio that shows the results of the total assets used in the company.
ROA is calculated by comparing net income available to common stockholders with total assets.
Formulated as follows:
𝑅𝑒𝑡𝑢𝑟𝑛 𝑜𝑛 𝐴𝑠𝑠𝑒𝑡𝑠 =𝑁𝑒𝑡 𝑃𝑟𝑜𝑓𝑖𝑡 𝐴𝑓𝑡𝑒𝑟 𝑇𝑎𝑥 𝑇𝑜𝑡𝑎𝑙 𝐴𝑠𝑠𝑒𝑡𝑠 2.2. Non Performing Loan (NPL)
Kuncoro and Suhardjono (2002) Non-Performing Loan (NPL) or bad credit is a condition in which the customer is unable to pay part or or all of his obligations to the bank as promised. Meanwhile, according to Dendawijaya (2009) Non Performing Loans (NPL) is a ratio to measure the ability of bank management to overcome problem loans provided by banks. The credit risk of a bank is one of the risks received from a banking business or activity that results from non-repayment of loans given by banks to debtors. Thus, it can be concluded that the Non-Performing Loan (NPL) is a ratio to measure the ability of bank management to overcome non-performing loans because customers are unable to pay part or all of their obligations.
According to Riyadi (2006) Non Performing Loans (NPL) can be calculated using the following formula:
𝑁𝑃𝐿 =𝑇𝑜𝑡𝑎𝑙 𝑁𝑜𝑛 𝑃𝑒𝑟𝑓𝑜𝑟𝑚𝑖𝑛𝑔 𝐿𝑜𝑎𝑛𝑠 𝑇𝑜𝑡𝑎𝑙 𝐶𝑟𝑒𝑑𝑖𝑡𝑠 𝐺𝑟𝑎𝑚𝑡𝑒𝑑
Loan to Deposit Ratio (LDR) is an indicator of measuring liquidity. Basically, the Loan to Deposit Ratio (LDR) is a traditional measurement that shows time deposits, current accounts, savings, etc. used to fulfill borrowers' requests (loan requests). This ratio is used to measure liquidity. A high ratio indicates that a bank has lent all its funds (loan-up) or is relatively illiquid. On the other hand, a low ratio indicates a liquid bank with excess funding capacity that is ready to be lent. According to Kasmir (2008), the Loan to Deposit Ratio (LDR) is a ratio between the total loans granted to the total third party funds (DPK) that can be collected by the bank. The LDR will show the bank's ability to channel third party funds collected by the bank concerned.
According to Bambang (2001) regarding the liquidity problem states that liquidity problems are related to the problem of a company's ability to meet its financial obligations which are immediately fulfilled, the number of payment instruments owned by a company at a certain time is the power to pay the company concerned. a company that has the power to pay is not necessarily able to meet all its financial obligations that must be fulfilled immediately, or in other words, it is not necessarily in the ability to pay.
The formula for finding a Loan to Deposit Ratio (LDR) is as follows:
Loan to Deposit Ratio = Total Credits granted Total third party funds
19
Return on Assets Receivable Tturnover
Non Performing Loan
Loan to Deposit Ratio 2.3. Receivable Turn Over (RTO)
According to Kasmir (2012) accounts receivable turnover is a ratio used to measure how long it takes to collect accounts receivable during a period or how many times the funds embedded in these receivables rotate in one period. The largest bank activities in channeling funds to other parties are in the form of credit (receivables).
In a bank balance sheet on the assets side, credit is the largest productivity asset and provides the largest income compared to other asset products. According to Law No. 10 of 1998 concerning banking, the credit provided is the provision of money or an equivalent bill, based on a loan agreement or agreement between the bank and another party which requires the borrower to pay off his debt after a certain period of time with interest (Ismail, 2009).
Receivable turnover is a measure of the effectiveness of accounts receivable management. The faster the accounts receivable turnover, the more effective the company is in managing its receivables. Accounts receivable relates to credit sales, so the formula for calculating accounts receivable turnover is:
Receivable Turn Over = Net Credit Distribution Average Accounts Receivable
3. Theoretical Framework
3.1. The Impact of Non Performing Loan Towards Return on Assets
Non Performing Loans (NPL) show the ability of bank management in non-performing loans provided by banks. A high NPL ratio means bad credit quality and causes the number of non-performing loans to increase so that the possibility of a bank in a problematic condition is getting bigger (Hesti, 2002). The higher the NPL, the higher the credit arrears which reduce the income and the interest to decrease the profit (Muljono, 1999).
The decrease in profit will decrease the bank's ROA
3.2. The Impact of Loan to Deposit Ratio Towards Return on Assets
The LDR ratio is used to measure the ability of the bank to pay its debts and repay the depositors, as well as to fulfill the credit demand submitted. Or in other words, to what extent the provision of credit to customers, creditworthiness can offset the bank's obligation to immediately fulfill depositors' requests who want to withdraw the money that has been used by the bank to provide credit (Dendawijaya, 2003). The higher the credit channeled by the bank, the higher the bank's income and profit (assuming the bank is able to channel its credit effectively). By increasing bank profits, the ROA ratio will also increase. Thus, LDR has a positive effect on ROA.
3.3. The Impact of Receivable Turn Over Towards Return on Assets
Receivable Turnover (receivables turnover) shows the receivables rotating until they can be collected and entered into the company's cash. The higher the proportion of receivables from credit purchases that have been distributed, the impact on increasing profits and increasing profitability (ROA) (Wild, 2010).
Figure 3. Theoretical Framework Explanation:
Explanation :
: Partial Test
: Simultaneous Test
4. Hypotheses
H1 : Non Performing Loans (NPL) have a significant effect on the Return on Assets (ROA) of banks listed on the Indonesia Stock Exchange 2016-2018.
20
H2 : Loan to Deposit Ratio (LDR) has a significant effect on the Return on Assets (ROA) of banks listed on the Indonesia Stock Exchange 2016-2018.
H3 : Receivable Turover has a significant effect on the Return On Assets (ROA) of banks listed on the Indonesia Stock Exchange 2016-2018.
H4 : Non Performing Loans (NPL), Loan to Deposit Ratio (LDR), and Receivable Turover simultaneously have a significant effect on the Return on Assets (ROA) of banks listed on the Indonesia Stock Exchange 2016-2018
5. Research Methods 5.1. Types of Research
In this study, researchers used a quantitative approach. Quantitative research is a form of numbers to test a hypothesis. By using this approach, the significance of the relationship between the variables studied will be obtained.
5.2. Research Object
The object of this research is the financial ratios of banking companies listed on the Indonesia Stock Exchange which include the ratio of Non-Performing Loans, Loan to Deposit Ratio, Receivable Turnover, and Return on Assets. The data period used in this study is 3 years from 2016 to 2018.
5.3. Population and Sample
In this study, the population used is banking companies listed on the Indonesia Stock Exchange for the period 2016 to 2018. The sampling technique used in this study is purposive sampling, the sampling technique is the technique used to take samples. The selection of purposive sampling method aims to obtain the required data, while the sampling criteria are:
1. Banks that have gone public on the Indonesia Stock Exchange during the research period (2016-2018 period)
2. There are financial reports that relate to the data studied during the study period (2016-2018 period) 3. The ten banks that generated the largest ROA during the 2016-2018 period
Based on the sampling results, it was obtained that there were 44 banking companies and 10 companies that met the sampling criteria. The analysis will be carried out for 3 periods, namely the 2016-2018 period so that the data from the sample amounts to 10 x 3 = 30
5.4. Data Type
The type of data used in this research is quantitative. The type of data required is the financial statements of banking companies for 2016-2018 obtained from the official website of the Indonesia Stock Exchange https://www.idx.co.id/company-noted/report-finance-and-tahunan/ (downloaded, 02- 05-2020 12.30 WIB).
5.5. Data Analysis Technique
In this study the data analysis technique uses multiple linear regression, which is an analysis technique to determine the effect of the independent variable with the dependent variable that shows a one-way relationship.
The models in this study are:
Y = 𝛼 + 𝛽1𝑋1 + 𝛽2𝑋2 + 𝛽3𝑋3 + 𝑒 Keterangan :
Y = Return on Assets (ROA) 𝛼 = Constanta
𝛽1- 𝛽4 = Coefisien Regression X1= Non Performing Loan X2= Loan to Deposit Ratio X3= Receivable TurnOver e = Standart error
6. Result and Discussion
The classic assumption test is a requirement that must be fulfilled in multiple linear regression analysis.
This test aims to provide certainty that the regression equation obtained has accuracy in estimation, unbiased, and consistent.
6.1 Normality Test
This test is used to determine the data contained in each variable is normally distributed or not.
Normality Test Results can be seen in Table 1.
21
Table 1.Kolmogorov Smirnov Test One-Sample Kolmogorov-Smirnov-Test
Unstandardized Residual Explanation
Asymp. Sig. (2-tailed) ,727 Normal
Based on the Kolmogorov Smirnov test it can be seen that the data in this study are normally distributed.
Seen on Asymp. Sig (2 tailed) of 0.727 indicates a significant value greater than 0.05 which means the data is normally distributed.
6.2 Multicollinearity Test
Multicollinearity test is used to find out whether in the regression model there is a variance in variance from the residuals of one observation to another . Multicollinearity Test Results can be seen in Table 2.
Table 2. Multicollinearity test
Variabel Collinearity Statistics
Tolerance VIF
NPL ,839 1,192
LDR ,898 1,114
Receivable Turnover ,889 1,125
In table 2, it can be seen that the data meet the multicollinearity test requirements because the tolerance value of each variable is ≤ 0.10 and the VIF value of each variable is ≥10 which means that the variable does not occur multicollinearity.
6.3 Autocorrelation Test
Autocorrelation aims to test whether in a linear regression model there is a correlation between confounding errors in period t with errors in period t-1 (previous). If there is a correlation, it is called an autocorrelation problem. A good regression model is free from autocorrelation. One way to identify it is to look at the Durbin Watson (D-W) value:
1. If the D-W value is below -2 it means that there is positive autocorrelation 2. If the D-W value is between -2 to 2.5 it means that there is no autocorrelation 3. If the D-W value is above 2.5, it means that there is negative autocorrelation
Table 3. Autocorrelation Test Durbin-
Watson
Description
1.218 There is no
autocorrelation 6.4 Heterokedasticity Test
Heterokedasticity test used to find out whether the regression model occurred inequality variants of residuals of the observations to other observations . Heteroscedasticity test can be seen in Figure 3.
22
Figure 4. Heterokedasticity Test
In Figure 3, it can be seen that the points spread randomly and spread both above and below 0 on the Y axis, and there are no specific patterns, this concludes that there is no heterokedasticity.
6.5 Multiple Linear Regression Test
The results of multiple linear regression analysis in this study can be seen in Table 5.
Table 4. Multiple Linear Regression Test
Model Unstandardized Coefficients
B
(Constant) 1,771
NPL -,034
LDR -,014
Receivable Turnover ,275
Based on the analysis results in table 5, the linear regression equation is obtained as follows: Y = 1,771 – 0,034𝑋1 – 0,014𝑋2 + 0,275𝑋3 + 𝑒
The coefficient of determination test aims to find out how much the model's ability to explain the variation of the dependent variable. Test results in this study can be seen in table 6.
Table 5. Coefficient of Determination Test 𝑹𝟐 Adjusted R
Square
R R
Square
Adjusted R Square
Std. Error of the Estimate
,784 ,898 ,806 ,784 1,17913
The result of the coefficient of determination (R ^ 2) shows that the value of Adjusted R Square is 0.784 or 78.4%. This means that the Return on Assets (ROA) which is able to present the independent variables (NPL, LDR, and Receivable Turnover) is 78.4% while the remaining 21.6% is based on other variables not examined.
6.6 F Test (Simultaneous)
Simultaneous hypothesis testing aims to determine the effect of NPL, LDR, and RTO independent variables simultaneously (together) on the dependent variable which is profit change. The f test results in this study can be seen in table 7.
Table 6. F Test
F Sig Explanation
36,022 ,000 Significant
F test results show that F count (36,022) and sig. (,000), when compared to F table (2,98), then F count >
F table and sig. < α 0.05, thus it can be concluded that the model is significant.
23 6.7 T Test (Partial)
Partial hypothesis test aims to determine the effect of NPL, LDR, and RTO independent variables partially (individually) on the dependent variable which is profit changes. T test results in this study can be seen in Table 8.
Table 7. T Test
Model B t Sig. Explanation
(Constant) 1,772 1,188 ,246 Insignificant
NPL -,034 -,155 ,878 Insignificant
LDR -,014 -,982 ,335 Insignificant
Receivable Turnover
,275 9,896 ,000 Significant
The results of the t test on the NPL variable (X1), the regression coefficient of -0.034 (negative) with t- count (-0.155) and sig (0.878), if with t-table (-2.055), then -t-count> -t -table and sig> 𝛼 (0.05), assuming other variables are considered constant, so it can be concluded that Net Performing Loan (NPL) has a negative and insignificant effect on Return on Assets (ROA). Based on this analysis, it can be concluded that the first hypothesis which states that the Net Performing Loan (NPL) has a significant effect on Return on Assets (ROA) is rejected.
The results of the t test on the LDR variable (X2), the regression coefficient of -0.014 (negative) with t- count (-0.982) and sig (0.335), if with t-table (-2.055), then -t-count> -t -table and sig> 𝛼 (0.05), assuming other variables are considered constant, so it can be concluded that the Loan to Deposit Ratio (LDR) has a negative and insignificant effect on Return on Assets (ROA). Based on this analysis, it can be concluded that the second hypothesis which states that the Loan to Deposit Ratio (LDR) has a significant effect on Return on Assets (ROA) is rejected.
The results of the t test on the variable Receivable Turnover (X3), the regression coefficient of 0.275 (positive) with t-count (9.896) and sig (0.000), if with t-table (2.055), then t-table> t-table and sig <𝛼 (0.05), assuming other variables are considered constant, so it can be concluded that Receivable Turnover has a significant positive effect on Return on Assets (ROA). Based on this analysis, it can be concluded that the third hypothesis which states that Receivable Turnover has a significant effect on Return on Assets (ROA) is accepted.
7. Conclusion and Suggestion 7.1. Conclusion
This study aims to test and prove the effect of Non Performing Loans, Loan to Deposit Ratio, and Receivable Turnover on Return on Assets of banking companies on the IDX in 2016-2018, based on the results of multiple linear regression tests, the following conclusions can be drawn,
The partial test results show that the Non Performing Loan (X1) has a negative and insignificant effect on Return on Assets (Y). This means that the size of the NPL value does not affect the ROA value of banking companies.
The partial test results show that the Loan to Deposit Ratio (X2) has a negative and insignificant effect on Return on Assets (Y). This means that the size of the LDR value does not affect the ROA value in banking companies.
The partial test results show that Receivable TurnOver (X3) has a significant positive effect on Return on Assets (Y). This means that the greater the RTO value, the greater the ROA value in banking companies
The simultaneous test results of Non Performing Loan, Loan to Deposit Ratio, Receivable Turnover have a significant effect on Return On Assets, this means that ROA can be explained by the three independent variables consisting of NPL, LDR, and RTO.
7.2. Suggestion
For the company, it is expected to improve its performance through bank profitability (ROA). Banks should be able to reduce unnecessary operational costs, for example reducing banking products and services that require high costs. Bank management should be more courageous in channeling financing when the interest rate of the Indonesian bank is relatively stable, so that the profit earned is increased, but still carry out good control and supervision so that bad credit can be anticipated.
For future researchers, this researcher can be used as a reference for further research. It is hoped that in future studies it can add other ratios and also can add a study period of more than 3 years.
References
Bambang, R. (2001). Dasar-Dasar Pembelajaran Perusahaan. BPFE. Dendawijaya, L. (2003). Manajemen Perbankan. Ghalia Indonesia. Dendawijaya, L. (2009). Manajemen Perbankan (2nd ed.). Ghalia Indonesia.
24
Hesti, W. (2002). Faktor Yang Mempengaruhi Profitabilitas Bank Take Over Pramerger di Indonesia. 1(2).
Ismail. (2009). Akutansi Bank Teori dan Aplikasi dalam Rupiah. Kencana Prenada Media Group.
Kasmir. (2008). Bank dan Lembaga Keuangan Lainnya. PT. Rajagrafindo Persada. Kasmir. (2012). Analisis Laporan Keuangan. PT. Rajagrafindo Persada.
Kasmir. (2014). Dasar-Dasar Perbankan. PT. Rajagrafindo Persada.
Kuncoro, M., & Suhardjono. (2002). Manajemen Perbankan : Teori dan Aplikasi. BPFE. Muljono, T. P. (1999).
Analisa Laporan Keuangan Untuk Perbankan. Djambatan.
Riyadi, S. (2006). Banking Assets and Liability Management. Lembaga Penerbit Fakultas Ekonomi Universitas Indonesia.
Simamora, H. (2000). Akuntansi : Basis Pengambilan Keputusan Bisnis. Salemba Empat. Wild, J. J. (2010).
Financial Statment Analysis (10th ed.). Salemba Empat.
