THE EFFECT OF NON PERFORMING FINANCING, FINANCING TO DEPOSIT RATIO AND OPERATING EXPENSE TO OPERATING INCOME RATIO (BOPO) TO PROFITABILITY (CASE STUDY IN BANK OF SHARIA LISTED IN INDONESIA STOCK EXCHANGE PERIOD 2014-2016) 69 THE EFFECT OF NON PERFORMING FINANCING, FINANCING TO DEPOSIT RATIO AND OPERATING EXPENSE TO OPERATING INCOME RATIO (BOPO) TO PROFITABILITY (CASE STUDY IN BANK OF SHARIA LISTED IN INDONESIA STOCK EXCHANGE PERIOD 2014-2016) Sri Suartini61*, Hari Sulistiyo2, and Wahyuni Indrianti3 1,2 Universitas Singaperbangsa, Indonesia Abstract The issues raised in this study are: to determine, explain and analyze profitability, Non Perfroming Loan, Financing to Deposit Ratio and Operating Expense to Operating Income in Bank of sharia and the partial effect and simultaneous of NPF, FDR and Operating Expense to Operating Income ratio to Profitability Bank of sharia Period 2014 -2016. The number of samples taken 12 Bank of sharia in the study period with saturated sampling technique. This research expected to contribute and to the development of the field of accounting, especially financial accounting. The research methods used by the author in this study, using descriptive and verification, the results showed conclusions are: NPF has no effect on profitability because of the results of calculations performed tcount smaller than ttabel. FDR has not effect on profitability because of the results of calculations performed tcount smaller than ttabel. Partially Operating Expense to Operating Income has significant negative effect on profitability. Operating Expense to Operating Income is the most influential variable among other variables on profitability. The effect of simultaneous NPF, FDR and Operating Expense to Operating Income on profitability of 75.8% while the remaining 24.2% is the influence of other factors not examined. We can conclude that NPF, FDR and ROA simultaneously positive and significant impact on profitability Bank of sharia in the study period. JEL Classification: G10, G12, G21 Keywords: FDR, NPF, Profitability, ROA 1. INTRODUCTION The world of banking is one of the indicators supporting world economic growth, including in Indonesia. Banking is one of the financial institutions that are necessary in a country's economy, particularly in the area of financing. Banking sector to perform its functions based on the precautionary principle. This is because banks have primary business and channel funds back to the community in the form of credit in order to improve the standard of living of the people. One of the indicators used to determine the profitability is Return on Assets (ROA). ROA is important for banks because of ROA is used to measure the effectiveness of the company in generating profits by exploiting its assets. ROA is the ratio between profit after tax to total assets. The greater the ROA shows the better performance of the company, since the level of return (return) increases. The greater Return on Assets (ROA) of a bank, the greater the level of profit that the bank achieved, and the better the position of the bank in terms of asset utilization. (Mawadah, 2014). In this below figure 1 presented empirical data on the development of Return on Assets (ROA) Bank of sharia from 2014 to 2016: * Corresponding author. Email address: srisuartini_daw@yahoo.com AFEBI Economic and Finance Review (AEFR) Vol.03 No.02, December 2018 70 2014 2015 2016 ROA 0.41 0.49 0.63 Growth of ROA Non Perfoming Financing 4.95 4.84 4.42 2014 2015 2016 Figure 1 Return on Assets (ROA) Source: Statistics Indonesia Bank of sharia (processed 2018) According to Niode (2016) in his study stated that NPF significant negative effect on ROA Bank of sharia, in line with research conducted by Pratama (2012) stated that the NPF and significant negative effect on ROA Bank of sharia. In contrast to the results of research conducted by Sari (2013) which states that the NPF positive and significant impact on ROA Bank of sharia. In figure 2 show an empirical data Non- perfoming financing at Bank of Syaria year of 2014-2016 are presented below: Figure 2 Non Performing Financing (NPF) Source: Statistics Indonesia Bank of sharia (processed 2018) Low profitability is also suspected due to fluctuation Financing to Deposit Ratio (FDR). In the research by Pratama (2012), argued that FDR positive and significant impact on the return on assets, this is supported by research Sari (2013) FDR positive and significant impact on ROA Bank of sharia. Then Riyadi and Yulianto (2014) in they research claimed that the positive effect on ROA Bank of sharia. In contrast with the results of Harianto (2018) stated that FDR had no effect on ROA Bank of sharia. This is supported research by Wardana (2015) stated that FDR had no effect on ROA Bank of sharia. In figure 3 show an Empirical data Financing to Deposit Ratio (FDR) at Bank Syaria years 2014 to 2016 are presented below: THE EFFECT OF NON PERFORMING FINANCING, FINANCING TO DEPOSIT RATIO AND OPERATING EXPENSE TO OPERATING INCOME RATIO (BOPO) TO PROFITABILITY (CASE STUDY IN BANK OF SHARIA LISTED IN INDONESIA STOCK EXCHANGE PERIOD 2014-2016) 71 Finacing To Deposit Ratio 86.66 88.03 85.99 2014 2015 2016 Biaya Operasional Terhadap Pendapatan Operasional (BOPO) 96.97 97.01 96.23 2016 2015 2014 Figure 3 Graph Financing to Deposit Ratio (FDR) Source: Statistics Indonesia Bank of sharia (processed 2018) Another factors which resulted in lower profitability Bank of sharia in the study period, allegedly because of the high Operating Expenses to Operating Income of the bank of sharia. Niode, (2016) The research suggests that Operating Expenses to Operating Income significant negative effect on ROA Bank of sharia. Then amplified research by Wardana (2015) states that Operating Expenses to Operating Income has significant negative effect on ROA, then the results of research by Hakim and Rafsanjani (2016) suggested that partial Operating Expenses to Operating Income has significant negative effect on ROA. In line with research conducted by Wibowo and Syaichu (2013) states that Operating Expenses to Operating Income has significant negative effect on ROA. In fugure 4 show the empirical data Operating Expenses to Operating Income (ROA) at Bank of Syaria years 2014 to 2016 are presented below: Figure 4 Operating Expenses Operating Income Source: Statistics Indonesia Bank of sharia (processed 2018) Based on the description of the background as mentioned above and see the phenomenon ratios Return on Assets (ROA), Non-perfoming Financing (NPF), Financing to Deposit Ratio (FDR), and Operating Expenses to Operating Income were erratic during the period 2014 until 2016, it is necessary to put forward the research to analyze whether there is an effect of the Non perfoming Financing (NPF), Financing to Deposit Ratio (FDR) and Operational Expenses to Operating Income to Profitability proxied by Return on Assets (ROA), the data obtained will be processed and analyzed, and then will be made in the form of research statement. This research will be the theme AFEBI Economic and Finance Review (AEFR) Vol.03 No.02, December 2018 72 or reserach titled "The Effects of Non-Performing Financing, Financing to Deposit Ratio and Operational Expenses to Operating Income (BOPO) to Profitability Bank of Sharia period 2014-2016” 2. LITERATURE STUDY/HYPOTHESES DEVELOPMENT Profitability According to Prawironegoro (2009: 55), profitability management is the ability to earn a return. From the second opinion of experts concluded that the profitability is the ability of management companies obtain profits through the sale of assets and equity. Profitability or commonly called an aspect that reflects the profitability of each company's ability to generate profits Hasibuan, (2008: 104). According Harahap (2011: 304) describes the profitability of the company's ability to profit through all existing capabilities and resources such as sales activities, cash , capital, number of employees, number of branches and so on. According to Dendawijaya (2009: 118) states that "ROA is used to measure the bank's ability to obtain an overall profit of the total assets owned. The formula can be used in calculating the ratio of return on assets (ROA) as follows: While the predicate of the bank based on ROA is presented in the table 1 below: Table 1 Predicate Bank by ROA No. ratios predbundle 1 2% 120% Not good Source: SE. BI No. 13/24 / DPNP / 2011 Operational Expenses to Operating Income (BOPO) According Dendawijaya (2009: 123) ROA "is the ratio of operating expenses are used to measure the efficiency and ability of banks to carry out operations". According Taswan (2010: 167) "ROA indicates the operational efficiency of the bank". The efficiency of the banking industry may be viewed from the standpoint of both micro and macro. According to Bank Indonesia Letter Financial Services Authority Circular No. 11 / Seojk.03 / 2015 Operating Expenses to Operating Income is the operating expense to operating income from the numbers calculated per position (not annualized). The formula can be used to calculate ROA ratios are as follows: equation…… (3) FDR = total Financing Third-party funds ROA = Total Operating Expenses Total Operating Income AFEBI Economic and Finance Review (AEFR) Vol.03 No.02, December 2018 74 while predicate bank soundness based BOPO are presented in the table below: Table 4 Predicate BOPO ratios Ranked BOPO ≤ 94% Very healthy 94% 97% Not healthy Source: Circular Letter No. 6/23 / DPNP 2004 Research Hypothesis Based on the description of the theoretical basis of research results and the framework above, then the hypothesis are: There is the influence of Non Performing Financing to Profitability, There is Influence of Financing to Deposit Ratio of Profitability, There is influence of Operating Expense to Operating Income to Profitability, There are the influence of Non Performing Financing, Financing to Deposit Ratio and Operating Expense to Operating Income to Profitability. 3. RESEARCH METHODOLOGY According Sugiyono (2011: 2), the research method is defined as: "a scientific way to obtain data for the purpose and usefulness. How meaningful scientific research activities are based on traits of science, that is, rational, empirical and systematic". In this research using descriptive method and verification. Descriptive method used to describe the formulation of the problem to one, two, three and so on. The required data is data corresponding to the existing problems and in accordance with the purpose of research, so that the data will be collected, analyzed and processed further in accordance with the theories that have been studied, so the data will be concluded. Meanwhile, according Mashuri (2009: 45) definition of verification method is as follows: "Method of verification is to check whether if it is described to test a way with or without improvements that have been implemented in other places with similar problems with life". The study was meant to test the hypothesis by using statistical calculations. This research was used to test the influence of variable X₁, X2 and X ₃ against Y researched. Verification means test the theory with testing a hypothesis of what is accepted or rejected. Therefore, this method is used to answer the problems regarding profitability as measured through the NPF, BOPO and FDR. Population According to Sugiyono (2011:80), population is a generalization of the object or the subject has certain qualities and characteristics set by the researchers to learn and then drawn the conclusion. The population in this study used is the entire banks of sharia listed on the Indonesia stock exchange publishes its report in full to the Indonesia stock exchange and the financial services authority. Total public bank of syaria in the research period as many as thirteen (13) but which meet the criteria as much as twelve (12) banks. Sample This study uses secondary data. data that has been collected by the collecting agency data and published to the public user data. Secondary data in the form of annual financial reports (annual report) published the bank. Sampling method using saturated from ten banks with the largest asset, because populations are examined less than 30. Then the entire population can be as a sample (Riduan 2010:21). So in this study the samples are twelve (12) banks. For more details can be seen in table 5 below. THE EFFECT OF NON PERFORMING FINANCING, FINANCING TO DEPOSIT RATIO AND OPERATING EXPENSE TO OPERATING INCOME RATIO (BOPO) TO PROFITABILITY (CASE STUDY IN BANK OF SHARIA LISTED IN INDONESIA STOCK EXCHANGE PERIOD 2014-2016) 75 Table 5 List Of Sample Research No Name of Bank 1 PT. Bank Muamalat Indonesia 2 PT. Bank Victoria Syariah 3 PT. Bank BRI Syariah 4 PT. Bank Jabar Banten Syariah 5 PT. Bank BNI Syariah 6 PT. Bank Syariah Mandiri 7 PT. Bank Mega Syariah 8 PT. Maybank Syariah Indonesia 9 PT. Bank Tabungan Pensiunan Nasional Syariah 10 PT. Bank Panin Syariah 11 PT. Bank Syariah Bukopin 12 PT. BCA Syariah Source: Statistics Of Sharia Banking. www.ojk.go.id. (processed 2018) Figure 5 Multiple Linear Regression Analysis Equations : Y = α+b₁X₁+b₂X₂+b₃X₃+ ἐ Descriptions: Y = Profitability (ROA) α = Konstanta X₁ = Non Performing Financing (NPF) X₂ = Financing to Deposit Ratio (FDR) X₃ = BOPO b₁ - b3 = Coefficient Of Determination ἐ = Standard Error Of The Estimate 4. RESULTS Test Validity Of Data Normality Test Normality tests are used to determine whether a data follow a normal distribution or not. Testing is already done using methods of Kolmogorov-Smirnov. With the provisions when the variable has a value of α calculate these variables then 0.05 > distributed normally. b4x4 Non Performing Financing (NPF) X₁ Profitabilitas (ROA) Y b₂x2 Financing to Deposit Ratio (FDR)X₂ BOPO X₃ b₃x3 ɛ b₁x1 AFEBI Economic and Finance Review (AEFR) Vol.03 No.02, December 2018 76 Table 6 Result of Normality Test Source: SPSS 24 (processed 2018) From the table above it can be known that value of significance is 0,182 greater than 0.05, so it can be concluded that the tested data distributed normally. Multicollinearity Test Test For Multicollinearity A good correlation model shouldn't happen correlation between independent variables. If the independent variables are correlated each other then this variable is not ontogonal. The variable ontogonal is the value of the independent variable correlation between fellow independent variable is equal to zero. To detect the presence of multikolonieritas by making a hypothesis: a. Tolerance value < 0,10 atau VIF > 10 : going multicollinearity b. Tolerance value > 0,10 atau VIF < 10 : not happening multicollinearity Table 7 Multikolinearity Test Collinearity Statistics Tolerance VIF ,772 1,296 ,904 1,106 ,750 1,333 Source: SPSS 24 (processed 2018) Based on the table above can be drawn the conclusion that the value of Tolerance and the VIF be seen that there is no Tolerance value below 0.10 and the value of the VIF is not in the top 10, this is the fourth independent variable means that there is no relationship multikolinearity so it can be used to predict the profitability of the proxied with the Return On Asset (ROA) during the research period i.e. 2014 up to 2016. Heteroscedasticity Test Heteroscedasticity is the State where a variant of residual inequalities occur for all observations in regression models. The regression models in the pre-requisite is the absence of Heteroscedasticity problems. Heteroscedasticity test aimed at testing One-Sample Kolmogorov-Smirnov Test Unstand ardized Residual N 36 Normal Parametersa,b Mean ,000000 0 Std. Deviation 2,26034 652 Most Extreme Differences Absolut e ,182 Positive ,182 Negativ e -,159 Test Statistic ,182 Asymp. Sig. (2-tailed) ,004c THE EFFECT OF NON PERFORMING FINANCING, FINANCING TO DEPOSIT RATIO AND OPERATING EXPENSE TO OPERATING INCOME RATIO (BOPO) TO PROFITABILITY (CASE STUDY IN BANK OF SHARIA LISTED IN INDONESIA STOCK EXCHANGE PERIOD 2014-2016) 77 whether in regression models of the residual variance inequality occurs one observation to observation of the other testing on this research using a scatterplot Graph between the value of the dependent variable prediction that is ZPRED with residue SRESID. Heteroscedasticity does not occur when there is no clear pattern, as well as the points spread above and below the 0 on the Y axis. Figure 4 Result of Heteroscedasticity Test Source: SPSS 24 (processed 2018) Based on figure 4 above it’s known that the data can be shown through the dots do not gather in one place and do not form a specific pattern, but evenly spread above and below the zero line so it can be inferred This regression test that there are no problems Heteroscedasticity. Autocorrelation Test a. Autocorrelation is the State in which the occurrence of residual correlation between observations at one with other observations in the regression model. Method of testing uses test Durbin-Watson (test DW) with the following conditions: a. If d is smaller than dl or greater than 4-dl, then the zero hypothesis was rejected, which means there is autocorrelation. b. If d lies between du and 4-du, then the zero hypothesis is accepted which means no autocorrelation. c. If d is located between dl and du or du-4 and 4-dl, then it does not produce definitive conclusions. Table 8 Autocorrelation Test Results Model Summaryb Change Statistics Sig. F Change Durbin-Watson , 000 2.245 Source: SPSS 24 (processed 2018) Based on the output data above can be seen that the value of DW of 2.245, Then this value is compared with the value of the table (table Durbin Watson) the significance of 5%, where the amount of sample (N = 36) and the number of independent variables (K = 3) the obtained value du 1,654. DW value 2.245 is greater than the upper limit du namely 1,654 and less than (4-du) 4-1.654 = 2.346. It can be concluded that there is no autocorrelation. AFEBI Economic and Finance Review (AEFR) Vol.03 No.02, December 2018 78 5. DISCUSSION Multiple Linear Regression Analysis Based on the results of data processing by multiple linear regression using SPSS 24, coefficient for each variable Non Performing Financing (X1), Financing to Deposit Ratio (X2), and operating expenses to operating income (X₃) to Profitability (Y). The results of the analysis can be seen in the table 9 below: Table 9 The results of multiple linear regression test Coefficients Model Coefficients unstandardized standardized Coefficients t Sig. B Std. Error beta 1 (Constant) 16.113 2,853 5.648 , 000 NPF -, 386 , 280 -, 137 -1.381 , 177 FDR -, 001 , 029 -, 002 -, 020 , 985 BOPO -, 150 .019 -, 798 -7.952 , 000 Source: SPSS 24 (data processed 2018) Analysis multiple linear regression was used to test the effect of two or more independent variables on the dependent variable. The regression equation can be seen from the test results table coefficients. In the table of coefficients that is read is the value in column B, the first line shows the constant (a) and the next row shows the independent variables constant. According to the table above, the regression model used is as follows: Y = 16,113-0,386X₁ - 0,001X₂ - 0,150X₃ + Ԑ Based on the regression model and the table above, the results of multiple regression can be explained as follows: A linear regression Equation compounds known to have constants of 16.113 with positive direction. So the magnitude of constants indicate that if the independent variables (NPF, FDR, and BOPO) is assumed to be constant, then the dependent variable is Profitability (ROA) going up by 16.113%. the variable Coefficients NPF = 0.386 with negative direction, means any increase in NPF 1% will cause a decline in Profitability (ROA) of 0.386%. Coefficient of FDR = 0.001 with the direction of the negative meaning if FDR suffered a rise of 1% then the profitability (ROA) will decrease of 0.001%. the variable coefficients BOPO = 0.150 negative directions meaning if BOPO increase by 1%, then the profitability (ROA) declined by 0.150%. Coefficient Of Determination In the correlation analysis there is a number called the coefficient of determination or who is often called the coefficient determinant, because magnitude is the square of the correlation coefficient (r²), so that the coefficient is useful to determine the influence of variable X to variable Y. Table 10 coefficient of Determination Model Summaryb Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change 1 , 871a , 758 , 735 2.36393 , 758 33.428 Source: SPSS 24 (data processed 2018) a. Predictors: (Constant), NPF, FDR, BOPO b. Dependent Variable: ROA THE EFFECT OF NON PERFORMING FINANCING, FINANCING TO DEPOSIT RATIO AND OPERATING EXPENSE TO OPERATING INCOME RATIO (BOPO) TO PROFITABILITY (CASE STUDY IN BANK OF SHARIA LISTED IN INDONESIA STOCK EXCHANGE PERIOD 2014-2016) 79 According to the table 10 above, shows that the coefficient of determination (R2) of 0.758 or 75.8%, then the variable profitability is proxied by the ROA (Y) can be explained by the variable NPF (X₁), FDR (X₂) and ROA (X₃) or can NPF means (X₁), FDR (X₂), and ROA (X₃) effect on profitability is proxied by the ROA (Y) amounted to 75.8% while the remaining 24.2% is the influence of other factors not examined. NPF influence on Profitability NPF influence on profitability can be determined via statistical hypothesis testing as follows: H0: NPF no effect on Profitability Ha: NPF effect on Profitability Based on t test Tcount -1.381 values obtained further the value will be compared with the value Ttable . Ttable with a significance level (0.05) and degree of freedom (Df) = (n-2) = 36-2 = 34 obtained table = 1.691, Becauset (1,381) α (0.05), then Ho is accepted. It can be concluded that the partial Non Performing Financing does not affect the profitability. FDR influence on Profitability FDR influence on profitability can be determined via statistical hypothesis testing as follows: H0: FDR had no effect on Profitability Ha: FDR effect on Profitability Based on t test Tcount -0020 values obtained further the value will be compared with the value Ttable . Ttable with a significance level (0.05) anddegree of freedom (Df) = (n-2) = 36-2 = 34, Becauset (0,020) α (0.05), then Ho is accepted. It can be concluded that the partial financing to deposit ratio does not affect the profitability. BOPO influence on Profitability BOPO influence on profitability can be determined via statistical hypothesis testing as follows: H0: BOPO no effect on Profitability Ha: BOPO effect on Profitability Based on t test tcount -7.952 values obtained further the value will be compared with the value Ttable . Ttable with a significance level (0.05) anddegree of freedom (Df) = (n-2) = 36-2 = 34, Becauset (7.952)> T table (1,691) With sig. (0,000) <α (0.05), then Ho is rejected. It can be concluded that the partial BOPO significant negative effect on profitability Variables Test (Test F) F test (F-test) is aimed to determine the effect of independent variables (Credit Risk, Liquidity Risk, Operational Risk and Market Risk) simultaneously (together) to profitability (ROA) of banks listed on the Indonesia Stock Exchange period 2014- 2016. Statistical hypothesis: H0: NPF, FDR, and ROA simultaneously has no effect on Profitability Ha: NPF, FDR, and ROA simultaneously affect the profitability With the test criteria as follows: H0 rejected if sig or with a significance level of 5%, the test is not significant or no real effect on the individualαFhitung < Ftabel x1and x2x3 the dependent variable Y. The test results simultaneously with SPSS 24 presented in the table 11 below: AFEBI Economic and Finance Review (AEFR) Vol.03 No.02, December 2018 80 Table 11 F Test Results ANOVAa Model Sum of Squares Df mean Square F Sig. 1 Regression 560.402 3 186.801 33.428 , 000b residual 178.821 32 5.588 Total 739.223 35 Source: SPSS 24 (data Processed 2018) Based on Table 12 above, shows that F count =33.428 sig. 0,000. Effect of X₁, X₂ and X₃ simultaneously to Y are shown in the table below 4:11 this: Table 12 Influence Together NPF (X1), FDR (X2) and BOPO ((X3) to Profitability (Y) structural Sig. Α Fhitung Ftabel Conclusion ɓx1, x2, X3 0,000 0.05 33.428 2,641 Ho rejected Source: SPSS 24 (Data Processed 2018) Test Table F shows that sig (0.000) <α (0.05)="" and="" fhitung="" (33.428)="">Ftabel (2.641) then the Ho is rejected. Thus it can be concluded that Non- performing Financing, Financing to Deposit Ratio and BOPO simultaneously positive and significant effect against the Profitability (ROA) banking on the research period. 6. CONCLUSION Based on the results of the analysis and discussion that had been featured in previous chapter, then the conclusion can be drawn as follows: The NPF did not affect to profitability because of the results of the calculations are the value of Tcount is less than Ttable. This means that the higher the risk of Credit then it will not affect profitability (ROA) of the bank. FDR did not affect to profitability because of the results of calculations performed tcount(t hitung) smaller than Ttable . It means that the higher the liquidity of the banking then it will not affect profitability (ROA) of the bank. BOPO influence on profitability is 7.952% with a negative direction. That is partially BOPO significant negative effect on profitability (ROA). This means that the greater the risk of a loan the bank profitability would be lower. ROA is the most influential variable among other variables on profitability. The simultaneous effect NPF, FDR and BOPO on profitability (ROA) of 75.8% while the remaining 24.2% is the influence of other factors not examined. Thus we can conclude that NPF, FDR and BOPO simultaneously positive and significant impact on profitability (ROA) Banking in the study period. 7. SUGGESTION Based on the results of the above conclusions, it could be suggestions that are beneficial to the company, among others: It is expected that Bank of sharias continue to maintain its NPF not to be too high by means of the principle of prudence in lending to customers, even though the results do not affect the bank's profitability but this NPF is one indicator of the rating of the bank. It is expected that Bank of sharias continued to keep FDR because by keeping the liquidity level of the bank will be able to cover its obligations in both the short term and long term so that the bank's operations can run smoothly as well as risks relating to liquidity can be anticipated by the banks. 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