DER AND TATO WITH THE AFFECTING ON THE

DER AND TATO WITH THE AFFECTING ON THE

DER AND TATO WITH THE AFFECTING ON THE PERFORMANCE OF THE ROA Paul Eduard Sudjiman1 and Lorina Siregar Sudjiman2 Faculty of Economic, Universitas Advent Indonesia, Bandung, Indonesia; [email protected] 2 Faculty of Economic, Universitas Advent Indonesia, Bandung, Indonesia 1 ABSTRACT This research is conducted to know the influence of Debt to Equity Ratio (DER), Total Asset Turnover (TATO) on company performance simultaneously to performance of manufacturing company listed on BEI 2010-2015. The company's performance in this research is described through Return On Assets (ROA). This research is an associative research with quantitative approach. Data analysis technique used is panel data regression with fixed effect model. The data used are secondary data in the form of annual financial ratios. The data collection is taken with documentation technique sourced from report of manufacturing company publication. Sampling was done purposively by side with 24 companies from total population 136 companies. The results showed that the regression coefficient of Debt to Equity Ratio (DER) was negative with 0,045311. Each increase of the average Debt to Equity Ratio of 1

percent, it will reduce the performance of the company (Return On Assets) manufacturing companies listed on the BEI of 0.045311. The regression coefficient of Total Assets Turnover (TATO) is positive sign of 0.043552. Each increase in average Total Assets Turnover by 1 percent, it will increase the performance of the company (Return On Assets) manufacturing companies listed on the BEI of 0.043552. INTRODUCTION The source of corporate funds is reflected by foreign capital and own capital as measured by debt to equity ratio (DER). According to Robert Ang (1997) this ratio shows the composition of total debt to total equity. The higher the DER shows the composition of total debt is greater than the total capital itself, so that the greater the burden on the company's outsider (creditor). ROA is one indicator to measure the company's financial performance and is the profitability ratios used to measure the effectiveness of the company in generating profits by utilizing the total assets they have. The greater return on asset's shows the better the company's performance, because the greater the return (limpaphayom and ngamwutikul, 2004). IDENTIFICATION OF THE PROBLEM What is the effect of Debt to Equity Ratio on the performance of manufacturing companies listed on the Indonesia Stock Exchange period 2010-2015? How does Total Assets Turn Over Ratio affect the performance (ROA) of manufacturing companies listed

on the Indonesia Stock Exchange 2010-2015 period? How does the Debt to Equity Ratio and Total Assets Turnover affect the performance (ROA) of manufacturing companies listed on the Indonesia Stock Exchange 2010-2015 period? RESEARCH PURPOSES The purpose of this research is as follows: 1. To analyze the effect of Debt to Equity Ratio on the performance of manufacturing companies listed in Indonesia Stock Exchange 2010-2015 period. 2. To analyze the effect of Total Assets Turn Over Ratio on the performance (ROA) of manufacturing companies listed in Indonesia Stock Exchange 2010-2015 period. 3. To analyze the effect of Debt to Equity Ratio and Total Assets Turnover on the performance (ROA) of manufacturing companies listed on Indonesia Stock Exchange 2010-2015 period. CONCEPTUAL FRAMEWORK Companies whose source of funds tend to derive more from their own capital

than from debt capital would have a small interest expense due to the number of loans from external parties small. This has an impact on net income due to the amount of operating profit used to pay the small interest expense. Capital structure is illustrated through Debt to Equity Ratio (DER) which negatively affects ROA. According to Kashmir (2015: 172), Total Assets Turnover is the ratio used to measure the turnover of all assets owned by the company and measure how much sales earned from each rupiah assets. Total Asset Turnover (TATO) is a ratio that divides sales by total assets. When the sales conditions gained rise, the net profit received by the company is likely to rise. These conditions will cause the ratio of TATO and ROA tends to rise. Vice versa, if sales decline, the possibility of net income received by the company decreased and resulted in the ratio of TATO and ROA participate decline So it can be concluded that TATO has a positive effect on ROA. Based on literature review, the dependent variable in this research is return on asset (ROA) while DER and TATO are used as independent variable. THEORETICL BASICS Financial Performance A company can be said to be able to maintain its existence when the company is able to keep the company's performance remains good and stable. Information and or company performance can be obtained by making interpretation of financial statements, that is connecting elements in financial statements such as

elements of various assets with each other, elements of liabilities one with the other, the elements of assets with liabilities, the elements of the balance sheet with elements of profit and loss, will be obtained a lot of picture about the financial condition or performance of a company. THEORETICAL BASIC ROA (Return on Assets) The right ratio currently used is Return On Assets (ROA), because this ratio is able to provide a benchmark for assessing the company's operations. This ratio also sees how well the management empowers the company's assets in generating operating profits so as to give an idea of the overall operating efficiency of the company (Mulyono, 2008). Return On Assets (ROA) shows the ability of a company by using all of its assets to generate profit after tax". . Debt to Equity Ratio can be formulated as follows: Total Amount of debt DER = ----------------------------------The amount of capital alone Debt to Equity Ratio research has been done previously by Barus and Leliani (2013) found that the leverage proxies by DER has a positive and significant effect on the profitability of the company. Total asset turnover(TATO) Total asset turnover is the ratio used to measure the efficient use of all assets to increase sales volume by dividing sales by total assets.

According to Lukman Syamsuddin (2000, p.62), Total asset turnover shows the level of efficiency in the use of all the assets of a company in generating a certain sales volume. Higher Total asset turnover means more efficient use of overall assets in generating sales. Total Asset Turnover Total asset = ---------------------- x 100% Sales RESEARCH PARADIGM DER ROA TATO RESEARCH HYPOTHESES The hypothesis proposed by the author is the development of the theoretical base and the frame of mind associated with the analysis of factors that affect the performance of the company. The hypothesis presented is as follows: Current Ratio has a positive and significant effect on the performance of manufacturing companies listed in the Indonesia Stock Exchange period 2010-2015 Ha1: Debt to Equity Ratio has a negative and significant effect on the performance of manufacturing companies listed on Indonesia Stock Exchange 2010-2015 period.

Ha2: Total Assets Turn Over has a positive and significant impact on the performance of manufacturing companies listed in Indonesia Stock Exchange 2010-2015 period. Ha3: Debt to Equity Ratio and Total Assets Turnover simultaneously affect the performance of manufacturing companies listed on Indonesia Stock Exchange 2010-2015 period. OPERATIONAL VARIABLES DEFINITION Here is an explanation regarding the measurement of variables, among others: 1. Company Performance (ROA) Company performance is the result of many individual decisions made continuously by management. Company performance viewed from the financial condition one of them seen from the profitability of the company. Profitability ratios used are Return On Assets (ROA). ROA is a percentage of the company's net income to total assets. The formula used to look for ROA is, Net profit ROA = --------------- x 100% Total Assets 2. Debt to Equity Ratio This ratio is a ratio that measures the rate of use of debt (leverage) against own capital / equity owned by the company. The formula used to find Debt to Equity Ratio is, Total Amoun of debt Debt to Equity Ratio = --------------------------- x 100% Total Equity 3. Total Assets Turn Over This ratio measures the turnover of all company assets, and is calculated by dividing sales by total assets. The formula

used to find Total Assets Turn Over is, Sales Total Assets Turn Over = ---------------- x 100% Total Assets POPULATION AND SAMPLES Population The population in this research as many as 136 manufacturing companies listed on the Indonesia Stock Exchange from various sectors. Sample In this research using one technique is purposive sampling technique. Based on the sample criteria there are manufacturing companies to be used for research. These companies include: 24 companies Criteria of the company to be sampled in the research are as follows: a. Manufacturing companies that have and are still listed on the Stock Exchange during the study period. b. A manufacturing company that publishes annual financial statements during the study period. c. Manufacturing companies that have a positive profit. d. Manufacturing companies that have positive sales. e. Manufacturing company that has a positive asset value. DATA ANALYSIS TECHNIQUE Panel Data Regression Analysis 1. Model Specification Test with Chow Test To know the model of Pooled Least Square (PLS) or Fixed Effect Model (FEM) to

be selected for data estimation can be done by F-test or Chow Test. PLS is a restricted model which implements the same intercept for all individuals. The hypothesis in this test is as follows: H0: Pooled Least Square (PLS) H1: Fixed Effect Model (FEM) Table 1 Uji Chow atau Likelihood ratio test Redundant Fixed Effects Tests Equation: EQ01 Test cross-section fixed effects Effects Test Statistic Cross-section F Cross-section Chi-square 23.339151 246.765015 d.f. Prob. (23,118) 23

0.0000 0.0000 Source: Output E-views 9 (processed results) the model does not follow Pool Effect.Because the fixed effect is accepted, the next estimation, Hausman-test, needs to be done to select fixed effect or random effect. 2. Model Specification Test with Hausman Test To determine the appropriate method in accordance with the characteristics of panel data used, is fixed (fixed) or random (random), then tested by Hausman Test. Tabel 2 Uji Hausman Test Correlated Random Effects - Hausman Test Equation: EQ01 Test cross-section random effects Test Summary Cross-section random Chi-Sq. Statistic

Chi-Sq. d.f. 8.186608 2 Prob. 0.0167 Source: Output E-views 9 (processed results) Explanation : 2stat > Chi-Sq tabel = Random Effects Model 2stat < Chi-Sq tabel = Fixed Effect Model Based on Hausman test results obtained Chi-Sq value. The statistic (8.186608) is greater than the value of 2table (0.05; df = 2) (5.9915) and can also be seen from significant (p-value) = 0.0167 less than 5%, H0 so that the model follows Fixed Effect. 3. Classic Assumption Test a. Normality test Normality test on the model was done using Jarque-Bera test. The goal is to test the normality of the residual data of the regression model with the following hypotheses: H0: Normally distributed data

H1: Data is not normally distributed The result of normality test of regression model obtained using Jarque-Bera test shows that the result of the regression model obtained is not normally distributed as shown by p-value for Jarque-Bera test statistic (0,0000) less than 0.05 ( = 5%).). b. Heteroscedasticity Test The problem of heteroscedasticity in the regression model occurs because the variance of each error term is not constant which makes the appraisal no longer efficient because of the non-minimum variance. To see whether or not the problem of heteroscedasticities in regression model in this research used White test, that is by regressing the square of the residual (error) to all possible multiplication on the independent variable. White heteroscedasticity test follows the following hypothesis: Ho: There is no heteroscedasticity Ha: There is heteroscedasticity By criteria: If Chi squares count (2) Chi squared table (df2) then Ho is accepted Table 4 White Study Model Test Results Heteroskedasticity Test: White F-statistic Obs*R-squared Scaled explained SS 52.90835

94.63369 115.2322 Prob. F(5,138) Prob. Chi-Square(5) Prob. Chi-Square(5) 0.0000 0.0000 0.0000 Obtained heteroscedasticity test results show that the variance of residuals is not homogeneous (there is heteroscedasticity). c. Test Autocorrelation Autocorrelation in this study was detected by using Durbin Watson test that is by comparing the value of Durbin Watson count (d) with the Durbin Watson value of the table with higher limit (upper bond or du) and lower limit (lower bond or d1). The D-W values derived from the model are compared to the Durbin-Watson values. in the model Regression of 1, is obtained from the Durbin-Watson (D-W) table of the DL lower limit value of 1.758 and the upper limit of the DU of 1.778 Table 5 Durbin-Watson Test Results Model X -Y Durbin-Watson test D-W

1.263979 dL 1,706 dU 1,760 There is decision autocorrelation Source: E-VIEWS Output Appendix 9 4. Hypothesis testing Based on the estimation with the Fix Effect approach obtained multiple linear regression results as follows: Tabel 6 Hasil Estimasi Model Regresi Dependent Variable: ROA Method: Panel Least Squares Sample: 2010 2015 Periods included: 6 Cross-sections included: 24 Total panel (balanced) observations: 144 Variable Coefficien

t Std. Error t-Statistic Prob. C DER TATO 10.84228 -0.045311 0.043552 2.266569 0.011587 0.013924 4.783564 -3.910468 3.127913 0.0000 0.0002

0.0022 Effects Specification Cross-section fixed (dummy variables) R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.892777 0.870060 3.513735 1456.868 -370.9518 39.30044 0.000000 Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter. Durbin-Watson stat

12.56799 9.747612 5.513219 6.049435 5.731107 1.263979 Source: E-VIEWS Output Appendix 9 From the table above can be written the results of the regression equation is as follows: ROA =10,84228 0,045311DER + 0,043552 TATO Referring to the result of regeneration estimate obtained then can be explained as follows: The value of the constant (intercept) of 10.84228 means that if the Debt to Equity Ratio and Total Assets Turnover constant or equal to 0 then the value of the performance of manufacturing companies listed on the BI (Return On Assets) of 10.84228. The regression coefficient of Debt to Equity Ratio (DER) is negatively marked as - 0,045311. Each increase of the average Debt to Equity Ratio of 1 percent, it will reduce the performance of the company (Return On Assets) manufacturing companies listed on the ISE of 0.045311. Regression Coefficient of Total Assets Turnover (TATO) with positive sign of 0.043552. Each increase in average Total Assets Turnover by 1 percent, it will increase the performance of the company (Return On Assets) manufacturing companies listed on the ISE of 0.043552. To further conclude the estimation result of the following regression model, there will be a statistical analysis to prove the significance of the influence of each independent variable by using T-statistic test. Then the F-statistic test will be done to see the effect of

independent variables together and test the coefficient of determination to see how big the independent variable able to explain the dependent variable T-statistics test Variabel DER TATO Table 7 Hasil Pengujian T-statistik Signif. T-statistik H0 Description Level (p) -3.910468 0.0002 Rejected Significant on = 0,05 3.127913 0.0022 Rejected Significant on = 0,05 Source: E-VIEWS Output Appendix 9 1. It is concluded that Debt to Equity Ratio has a negative and significant effect on the

performance of manufacturing companies listed in Indonesia Stock Exchange 20102015 period. 2. The value of prob (significance) of T-statistical test of TATO variable equal to 0,0022 less than level = 0,05 so that conclusion of test significance at 5%). significance level. It is concluded that Total Assets Turnover has a positive and significant effect on the performance of manufacturing companies listed in Indonesia Stock Exchange 20102015 period. F-statistics test After a T-statistic test, an F-statistic test is performed to measure the goodness of fit of the regression equation or to find out if all independent variables contained in the equation simultaneously affect the dependent variable. P-value test of regression equation obtained by 0.000479 smaller than level = 0.05 so that the conclusion of significant test thus HA accepted. So it is concluded that Debt to Equity Ratio and Total Assets Turnover simultaneously affect the performance of manufacturing companies listed on ISE. 3. Coefficient of determination (R2) . To show the accuracy of regression model use coefficient of determination. Debt to Equity Ratio and Total Assets Turnover simultaneously affect the performance of manufacturing

companies listed on the BEI of 89.2777%). and the rest of 10.7223%). explained by other variables outside the model. A. Conclusion The result of calculation of Chow Test obtained by Fstat value (23,339151 is bigger than F-table value (0,05,23; 118) = 1,621 Because fixed effect is accepted, then the next estimation, Hausman-test, it is necessary to choose fixed effect or random effect. Debt to Equity Ratio has a negative and significant effect on the performance of manufacturing companies. The value of the constant (intercept) of 10.84228 means that if the Debt to Equity Ratio and Total Assets Turnover constant or equal to 0 then the value of the performance of manufacturing companies listed on the BI (Return On Assets) of 10.84228. The regression coefficient of Debt to Equity Ratio (DER) is negatively marked as - 0,045311. Each increase of the average Debt to Equity Ratio of 1 percent, it will reduce the performance of the company (Return On Assets) manufacturing companies listed on the BEI of 0.045311. The regression coefficient of Total Assets Turnover (TATO) is marked positive by 0.043552. Each increase in Average Total Assets Turnover of 1 percent, it will increase the performance of the company (Return On Assets) manufacturing companies listed on the BI since the regression model has been calculated obtained value of coefficient of determination (R2) of 0.892777 or 89.2777%). Which means the independent variable in this model is able to explain the dependent variable of 89.2777%)..

RECOMMENDATION Based on the above conclusions, suggestions that can be given to companies, investors, and researchers related to the factors that affect the performance of companies listed on the Indonesia Stock Exchange are: For the Company If the DER value is higher then it can be assumed that the company has a higher risk on the ability to pay off its short term debt. However, the resulting Debt to Equity Ratio can be minimized, then can improve company performance as measured by Return On Assets ratio. On the one hand, the company is also expected to increase sales in each period with offset total assets owned. For investors I n taking the decision to choose stock should consider the TATO ratios that have a positive influence and DER that has a negative influence to indicate the company's performance. A good company is capable of generating huge profits, with a low debt to equity ratio, meaning the company is able to cover all capital needs with its own capital. For academics and researchers For further research, it is expected to conduct further development of this research by using more number of samples. In addition it should add another independent variable that allegedly affects the company's performance. Limitations of Research

This study certainly still has limitations that can be taken into consideration for the next researchers to get better results such as: In this study only test some factors that affect the company's performance is only seen from the financial ratios, among others, Debt to Equity Ratio, and Total Assumption Turnover. Have not seen from other financial ratios, human resources, and so forth. In this study only use two independent variables. The study period is relatively minimal, only 6 years. The type of company in this study is limited to manufacturing companies only so that the sample selection becomes less.

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