The Effect of Current Ratio, Return on Assets, Total Asset Turnover and Sales Growth on Capital Structure in Manufacturing Company

This study aimed to determine how much effect the Current Ratio, Return on Assets, Total Asset Turnover and Sales Growth have on the Capital Structure of manufacturing companies listed on the IDX from 2016 to 2018. The research method used was descriptive method and multiple linear analysis method. The population of this study was 144 companies with a sample of these companies, namely 73. The data used were financial reports published by the Indonesia Stock Exchange through the website www.idx.co.id. The variables related to this research are the Current Ratio, Return on Assets, Total Asset Turnover, and Sales Growth. The results showed that partially Current Ratio has a negative and significant effect on Capital Structure, Return on Asset did not have a significant effect on Capital Structure, and Total Asset Turn Over has no significant effect on Capital Structure, and Sales Growth has no significant effect on Capital Structure in manufacturing companies listed on the Indonesia Stock Exchange. Simultaneously Current Ratio, Return on Asset, Total Asset Turn Over and Sales Growth together have a significant effect on the capital structure of companies listed on the Indonesia Stock Exchange. Copyright © Universitas Pendidikan Ganesha. All rights reserved. A R T I C L E I N F O Article history: Received 13 July 2020 Received in revised form 10 July 2020 Accepted 28 July 2020 Available online 29 August 2020

From the data obtained through the website www.idx.co.id regarding current assets, net profits, sales, and debt to manufacturing companies on the Indonesian stock exchange for the period 2016-2018, it can be seen that a phenomenon that occurs in current assets at PT Kedawung Setia Industrial Tbk (KDSI) experienced a decline from 2017 to 2018 of 2.02%, but followed by a decrease in debt from 2017 to 2018 of 0.77%. The net profit at PT Sepatu Bata Tbk (BATA) has increased from 2016 to 2017 by 27.05% but followed by an increase in debt from 2016 to 2017 of 11.63%. For total assets at PT Kino Indonesia Tbk (KINO) has increased from 2017 to 2018 by 10.95%, but followed by an increase in debt from 2017 to 2018 of 18.85%. Sales at PT Kino Indonesia Tbk (KINO) decreased from 2016 to 2017 by 9.52%, but followed by a decrease in debt from 2016 to 2017 of 11.26%.
Based on this description, a research objective was formulated to analyze the Current Ratio, Return on Assets, Total Asset Turnover, Sales Growth to Capital Structure in manufacturing companies listed on the IDX for the period 2016 -2018"

Methods
This study was a quantitative descriptive research. The sample used in this study was the financial data of companies listed on the IDX in 2016-2018. The sampling technique used was purposive sampling method.
The population in this study was 144 companies listed on the IDX for the period 2016 -2018 with a sample size of 219 financial reports taken from 73 manufacturing companies listed on the IDX for the 2016 -2018 period.
The data collection technique used in this study was using data from official companies that published their financial reports on the Indonesia Stock Exchange website, as well as review journals, books and papers to obtain a comprehensive theoretical basis.

Normality test
This test aimed to determine whether the residual variable is functioning normally or not in a normal distribution, where the techniques used are graphic analysis or statistical analysis (Ghozali, 2018).

Multicollinearity Test
This test was used to find a correlation or intercorrelation between independent variables (Ghozali, 2018).

Autocorrelation Test
This test was carried out to test for errors or not that result in correlation to the data (Ghozali, 2018).

Heteroscedasticity Test
This test was used to test for the similarity or inequality of variants and residuals of observations to other observations (Ghozali, 2018).

Hypothesis testing
The t statistical test was used to prove whether the independent variable has an effect on the dependent variable individually (Ghozali, 2018). The t-test criteria are: a. If t-table < t-count < t-table, then Ho is accepted. b. If t-count > t-table or t-count < t-table, then Ho is rejected.
The f statistical test was used to measure whether the independent variables as a whole have an effect on the dependent variable (Ghozali, 2018). The F test criteria are: a. If F-count < F-table, then Ho is accepted. b. If F-count > F-table, then Ho is rejected.
The coefficient of determination was used to regulate how capable the model is to explain the variation of the independent variables (Ghozali, 2018).

Descriptive Statistics of Data
In this study, descriptive statistical testing was to provide a description of data that explained the maximum value, minimum value, average value, and standard deviation used in the study.   International Journal of Social Science and Business, Vol. 4, No. 3, 2020, pp.

Normality test
This test was conducted to determine the regression model and the residuals which have a normal distribution.

Figure 1. Histogram Normality Test
Based on Figure 1 above, it shows that the curve graph is an inverted bell where it is concluded that the residual data is normally distributed. Graph of Normality P -P Plot in Figure 2 below, it can be seen that the dots spread out close to the diagonal line. It can be concluded that the data are normally distributed.
Likewise, the results of the normal probability plot test are as follows

Figure 2. P -P Plot Normality Test
In addition to the analysis of histogram charts and the P -P Plot, it can be seen that the data is normally distributed or not, namely by using the Kolmogrov -Smirnov non-parametric statistical test, if the value is Asymp. Sig (2-tailed)> 0.05, then the data can be said to be normally distributed. .200 Data source: Results of SPSS 2020 data processing Based on Table 3 above, it can be seen that normality testing using the Kolmogrov -Smirnov statistic has a sig value of 0.200> 0.05 so that the data were normally distributed.

Multicollinearity Test
The multicollinearity test aimed to measure whether the regression model found a correlation between independent variables by looking at the Tolerance value or the Variance Inflation Factor (VIF) value.  Table 4 above, it is shown that the tolerance value of the current ratio variable (0.833), return on assets (0.743), total asset turnover (0.887), and sales turnover (0.934) is above 0.10 while the VIF value of the current ratio variable (1.2) ), return on assets (1,347), total asset turnover (1,128) and sales turnover (1.07) are below 10. Where the tolerance value limit is> 0.1 and VIF <10, then in this regression model there is no multicollinearity between the independent variables.

Autocorrelation Test
The autocorrelation test aimed to test whether or not there was an error that results in correlation to the data.  Table 5 above, it can be concluded that the value of Asymp. Sig. (2-tailed) of 0.195> 0.05, the data is free from autocorrelation symptoms.

Heteroscedasticity Test
Heteroscedasticity test was used to test for the similarity or inequality of variants and residuals from observations to other observations. Based on Figure 3 above shows the scatterplot, it can be seen that the dots spread randomly either above or below or around the zero (0) on the Y axis, so from the graph it can be concluded that there is no heteroscedasticity in this test and is feasible to use.
International Journal of Social Science and Business, Vol. 4, No. 3, 2020, pp. Table 6 above, it shows that the R Square value is 0.031, then the calculated c2 value is: The formula = n x the value of R Square = 173 x 0.031 = 5.363 (calculated c2 value) While the c2 table value of 7,815 is obtained from k -1 (4 -1 = 3) with a significance value of 5%, it can be concluded that the value of c2 count <c2 table (5,363 <7,815), so there are no symptoms of heteroscedasticity.

Results of Research Data Analysis Multiple Linear Regression Analysis
Multiple linear regression analysis was used to determine the relationship between variable X and Y.

Coefficient of Determination
The coefficient of determination was used to determine the effect of the model's ability to explain the variation of the independent variables. Based on Table 8 above, it shows the results of the determination coefficient test, the value of the Adjusted R Square coefficient of determination is 0.502, which means that 50.2% can be explained that the independent variable affects the capital structure while the remaining 49.8% is explained by other independent variables that are not careful in this study.

Simultaneous Hypothesis Testing (Test F)
The F test was used to prove whether the independent variable has an overall effect on the dependent variable.  From table 9 above, it can be seen that the Fcount value is 44,272 and the Ftable value is significant at 0.05 and seen the df1 and df2 with the formula df1 = k -1 = (4 + 1) -1 = 4, df2 = n -k = 173 -5 = 168 is 2.43, then Fcoun t> Ftable (44.272 > 2.43) so that the results of the study reject Ho and accept Ha and the significant value is less than 0.05 (0.000 < 0.05). Thus it can be concluded that the variables CR, ROA, TATO, and Sales Growth together have a significant effect on the Capital Structure of manufacturing companies listed on the IDX for the period 2016 -2018.

Partial Hypothesis Testing (Test -t)
The t test was used to prove whether the independent variable affected the dependent variable individually. Based on the results of data processing with the SPSS program, the results of the t test are as follows.

Discussion The Effect of Current Ratio on Capital Structure
From the partial test results, it can be seen that the CR variable has a t-count value of 12.32 with a ttable of t df = 173, and a t-table of 1.97419 is obtained. Then tcount > ttable (12.32 > 1.97419) with a significant value of 0.000 < 0.05. This shows that CR partially has a negative and significant effect on DER. The current ratio owned by the company is a factor that affects the capital structure because high liquidity is able to reduce the use of external funds due to high internal funding. According to (Hery, 2016) Current Ratio is a description of how much the amount of current assets owned by the company is compared to the amount of current liabilities that will be due. According to (Fahmi, 2015), Current Ratio is a general measure used for short-term solutions and a company's ability to meet debt when it becomes due. According to (Supardi et al., 2016) Current Ratio is the company's performance in paying off its obligations at maturity. A high current ratio makes investors more interested in buying shares so that they can increase the company's stock price (Lilie et al., 2019;Setia Rini et al., 2018). Current Ratio is useful for assessing the company's ability to fulfill its obligations so that it can attract investors to invest.
According to Herlambang & Marwoto in the journal (Tanri et al., 2020) said that if the company has the ability to pay its current debt well, the company is in a liquid condition, but on the other hand, a company that is unable to pay it will be a liquid company. According to (Juliantika & Dewi, 2016), according to the pecking order theory, companies that have high liquidity tend to use internal funds, so that the level of corporate debt will decrease due to the repayment of current debts.
The results of this study were in line with the results of research (Deviani & Sudjarni, 2018) which stated that the current ratio partially has a negative effect on capital structure. In addition, there are the results of research conducted by (Juliantika & Dewi, 2016) which stated that liquidity, which is proxied by the Current Ratio (CR), has a negative and significant effect on capital structure (DER). (Watung, 2016)  stated that there is a negative influence between liquidity (current ratio) on capital structure. In addition, (Lasut et al., 2018). From the results of the t test it is concluded that liquidity has a negative and significant effect on capital structure.

The Effect of Return on Asset on Capital Structure
From the partial test results, it can be seen that the ROA variable has a t-count of -0.314 with a ttable of t df = 173, the t table is 1.97419. Then tcount <ttable (0.314 <1.97419) with a significant value of 0.754> 0.05. This shows that ROA partially does not have a significant effect on DER in-manufacturing companies listed on the Indonesia Stock Exchange (BEI) for the period 2016 -2018.
Return on Asset is the calculation of the benefits obtained by utilizing the use of company assets (Chandra et al., 2019). According to (Wijayanto, 2010) Return on Asset is a ratio used to measure how much profitability is generated from the use of company assets. According to (Murhadi, 2015) Return on Asset is a description of how much return is obtained for each invested in assets. According to (Haryanto, 2016), if the company has a high level of profitability, it shows that the company can generate enormous profits because it utilizes its assets. According to (Watiningsih, 2018), if the profitability in the company is high enough, the company's capital structure will be low so that the company uses smaller debt because it is able to provide sufficient funds through retained earnings. According to (Akhtar et al., 2011) if the value of Return on Assets in the company is high, it indicates higher profitability. The effect of liquidity on capital structure means that if the company's liquidity increases, the company's capital structure will decrease. It can be said that changes in profitability will not affect changes in capital structure.
This study was in line with the results of research (Naibaho et al., 2015) which stated that changes in profitability will not affect the capital structure. (Premawati & Darma, 2019) also stated that there is a negative effect company size on capital structure. Research conducted (Prihasti, 2018) stated managerial ownership has no effect on capital structure.

Effect of Total Asset Turnover on Capital Structure
From the partial test results, it can be seen that the TATO variable has a t-count value of 0.787 with a t-table of t df = 173, and the t-table is 1.97419. Then tcount < ttable (0.787 < 1.97419) with a significant value of 0.433 > 0.05. This shows that partially TATO has no significant effect on DER in manufacturing companies listed on the Indonesia Stock Exchange (BEI) for the period 2016 -2018. According to (Hutabarat, 2013), if the company that produces TATO is higher, the company will show sufficient lots of business volume so that the company can increase the value of sales. According to (Suweta & Dewi, 2016), the increase in tattoos shows that the performance of management in managing its assets is effective, so that when the turnover of a company's assets increases, the higher its sales. When the level of activity of the company is high, it will reduce the use of its debt. The higher the TATO, the higher the company creates profit from sales, so a high asset turnover will reduce the use of external funds from the risks faced (Noviandini & Welas, 2017).
The results of this study were in line with the results of research conducted by (Noviandini & Welas, 2017) that the total asset turnover partially has no effect on the capital structure. This is because when creditors provide long-term loans, creditors do not only see the asset rotation side, but many aspects are considered. The research conducted (Hartiwi et al., 2019) also stated that Total Asset Turnover has no influence on the Capital Structure of the Advertising, Printing and Media sub-sector companies for the 2012-2016 period. This is because the higher the Return on Equity, the better it means that the position of the company owners is getting stronger. Vice versa. If, a company with a high level of Return on Equity will generally use little or no debt.

The Effect of Sales Growth on Capital Structure
From the partial test results, it can be seen that the Sales Growth variable has a tcount of 1.962 with a t table of t df = 173, it is obtained a t table of 1.97419. Then tcount < ttable (1.962 < 1.97419 with a significant value of 0.051> 0.05. This shows that partially TATO has no significant effect on DER inmanufacturing companies listed on the Indonesia Stock Exchange (IDX) for the period 2016-2018. Sales growth is a performance companies to gain profits after determining a sales target. According to (Yudiandari, 2018) Companies that have a higher sales growth rate so that the company's dependence on debt will be lower. When sales growth increases, the company will also need high capital to support the company's development. (Halim & Widanaputra, 2018) Increasing high sales growth in a company tends to increase the use of debt in its capital structure (Suweta & Dewi, 2016). The results of this study were also in line with the results of research (Naray & Mananeke, 2015) which stated that growth does not have a significant effect on the capital structure because companies with high sales growth will tend to generate greater cash flow so that the company will use its internal funds. Research conducted (Prihasti, 2018) stated that taxes have no effect on capital structure. (Seftianne & Handayani, 2011) also stated that the business risk variable has no effect on the company's capital structure.

Conclusion
Current Ratio partially has a negative and significant effect on the Capital Structure of manufacturing companies listed on the IDX for the period 2016 -2018, Return on Assets partially has no significant effect on the Capital Structure of manufacturing companies listed on the IDX for the period 2016 -2018, Total Asset turnover partially does not have a significant effect on the Capital Structure of manufacturing companies listed on the IDX for the 2016 -2018 period, Sales Growth partially does not significantly affect the capital structure of manufacturing companies listed on the IDX for the 2016 -2018 period. If simultaneously Current Ratio, Return on Assets, Total Asset Turnover and Sales Growth simultaneously have a significant effect on the Capital Structure of manufacturing companies listed on the IDX for the period 2016 -2018 with a determination coefficient of 50.2%,

Suggestion
Based on the results of the study above, the researcher suggests manufacturing companies listed on the Indonesia Stock Exchange to carefully optimize their funding or capital structure and see the level of risk because good and bad capital structure in the company will affect the company's finances. For further researchers, it is necessary to broaden their knowledge and language, to work in groups even more, and to add independent variables and to increase the period of observation.