Vol. 10, No. 1, June 2020, pp. 103-112
ISSN: 2720-9830. 103
The Effect Of Short-Term Debt And Long-Term Debt On Profitability In Manufacturing Companies Listed On The Indonesia Stock Exchange
Indah Rianti Panggabean Universitas Darma Agung
Article Info ABSTRACT
Article history:
Received April 2020 Revised May 2020 Accepted June 2020
This study aims to determine the effect of short-term debt and long-term debt on profitability. The population in this study are food and beverage companies listed on the Indonesia Stock Exchange in 2017-2019. The number of samples used as many as 16 companies taken using purposive sampling technique.
Data analysis used classical assumption test and multiple linear regression.
The indicator for short term debt is short term debt (STD), long term debt indicator is long term debt equity ratio (LTDE), and profitability indicator is return on assets (ROA). The results of the research hypothesis are known that the t-test of the Short-Term Debt variable does not significantly affect Return On Assets, this can be seen from the significant value of 0.479 > 0.05 and the value of tcount > ttable or -0.079 < 2.014. And the Long-Term Debt has no significant effect on Return On assets, this can be seen from the significant value of 0.488 > 0.05 and the value of tcount > ttable or -0.292 > 2.014.
Meanwhile, it simultaneously shows that the fcount value is 47.796 and ftable can be seen in the statistical table, it is obtained ftable = 3.20. So it can be concluded that fcount > ftable (47.796 > 3.20) and 0.368 > 0.05, meaning Ho is rejected and Ha is accepted. This means that short-term debt and long-term debt have a simultaneous effect on return on assets in the 2017-2019 period.
Keywords:
Long Term Debt Return On Assets Short Term Debt
This is an open access article under the CC BY-SA license.
Corresponding Author:
Indah Rianti Panggabean Universitas Darma Agung
Email: [email protected]
INTRODUCTION
In facing business competition, a company must really prepare a very fundamental thing, namely capital. To be productive in the face of competition, companies must pay special attention to the use of funds. Provision of funds can come from internal sources, namely retained earnings and external sources, namely long-term debt, short-term debt and capital.
In certain circumstances the company tends to be able to meet its funding needs, by prioritizing sources that come from within (internal), but the growth of the company causes the need for funds to increase, so to meet these funding needs, the company must use external sources of funds. company is debt.
The income statement is a report that examines the measure of the success of a company's operations over a certain period of time. Through the income statement, investors can find out the level of profitability generated.
Through the income statement, creditors can also consider the creditworthiness of the debtor. The level of profit measure describes the company's performance to generate profits to pay creditor interest, investor dividends, and government taxes.
The profitability ratio of a company here is of course influenced by several factors, one of which is the level of debt (debt level). Profitability is one of the factors to assess the good or bad of a company's performance.
Return On Assets (ROA) is one type of profitability ratio that can assess the company's ability to earn a profit
Jurnal Ilmiah Socio Secretum, Vol. 10, No. 1, June 2020: 103-112
from the assets used. Return on Assets is a ratio used to assess the ability of a company's management to earn a profit as a whole. The greater the ROA value of a company, the greater the level of profit that can be achieved by the company and the better the position of the company in terms of asset utilization.
Profitability ratio is also a ratio that measures the effectiveness of the overall management as indicated by the size of the level of profit earned in relation to sales and investment.
With respect to debt, it can be said that with an increase in the amount of current debt (short-term debt), this increase will increase the ratio of current debt to total assets. The effect of the increasing current debt ratio is an increase in profit, but so is the risk. The increase in profit was due to the decrease in costs associated with the use of less short-term capital compared to the amount of long-term capital. The increase in debt will affect the size of the profit or profit for the company, which reflects the company's ability to fulfill all its obligations, which is indicated by some part of its own capital used to pay all its obligations, because the greater the use of debt, the greater the obligations. In essence, if the loan or debt changes, the profitability of a company will also change. An increase in debt will also increase profits and vice versa, a decrease in debt also decreases profits.
There are several results from previous studies, including research conducted by Rafiqoh Rizki Harahap (2016) which found that short-term debt and long-term debt simultaneously had a significant effect on profitability.
Meanwhile, according to Lukman Hakim Harahap (2019), the results of the study partially show that the short- term debt variable has no effect between short-term debt and profitability, the long-term debt variable has no effect on long-term debt on profitability.
In a study conducted by Syauib (2018), he found research results showing that long-term debt and short-term debt simultaneously have a positive and significant effect on profitability. Partially short-term debt and long- term debt also have a positive and significant effect. Meanwhile, in the journal Anita and Imam (2015) found that the long-term debt variable has an effect on profitability, while the short-term debt variable has no effect on profitability.
Research conducted by Wella Mery Cristina Nainggolan (2019) found that the results of the analysis found that short-term debt had a positive effect on profitability, long-term debt had a positive effect on profitability.
Meanwhile, Winni Ariane Pertiwi's research (2019) found that partially the long-term debt variable has a negative and significant effect on profitability, and the Current Ratio variable has a positive and significant effect on profitability. Simultaneously the variables of short-term debt, long-term debt, Current Ratio and Total Debt to Total Assets Ratio affect profitability.
Source: Processed by the Author 2021
This study will use Return On Assets as a tool to measure profitability ratios. Profitability provides a measure of the effectiveness of the company's management as indicated by the size of the profit generated from the use of existing resources as well as sales and investment income. The better the management of profitability ratios, the better it will describe the ability of the company to earn high profits
The reason the researcher uses Return On Assets as the dependent variable is because Return On Assets reflects the profit generated by the company by using all its assets so that when the Return On Assets is higher, the use of assets will be more efficient to obtain large profits.
Based on the research gap table shows the inconsistency of previous research results, so that the researchers will review the variables that affect Return On Assets and will conduct research with the title "The Effect of Short-Term Debt and Long-Term Debt on Profitability in Manufacturing Companies Listed on the Stock Exchange Indonesia (IDX)".
Formulation of the problem
Given the wide scope of the object of research and the limited ability of the author, in this study there are limitations to the problems that will be discussed. This is intended so that researchers can achieve as they should. The problems discussed in this study are limited to short-term debt and long-term debt to a company's ROA (Return On Assets). Meanwhile, the sample used is food and beverage sub-sector manufacturing companies listed on the Indonesia Stock Exchange (IDX) in the period 2017 to 2019.
Formulation of the problem
Based on the background of the problem that has been described, several problems that can be formulated in this study are:
Does Short-Term Debt affect the profitability of manufacturing companies listed on the Indonesia Stock Exchange?
Does Long-Term Debt affect the profitability of manufacturing companies listed on the Indonesia Stock Exchange?
Do Short-Term Debt and Long-Term Debt affect profitability simultaneously in manufacturing companies listed on the Indonesia Stock Exchange?
Research purposes
Based on the formulation of the problem, the objectives of this study are: To determine the effect of short-term debt on profitability in manufacturing companies listed on the Indonesia Stock Exchange, To determine the effect of long-term debt on profitability in manufacturing companies listed on the Indonesia Stock Exchange, To determine the effect of short-term debt and long-term debt simultaneously on the profitability of manufacturing companies listed on the Indonesia Stock Exchange.
METHOD Research sites
This research was conducted by taking a sample of food and beverage sub-sector companies that announced audited financial statements listed on the Indonesia Stock Exchange (IDX), namely www.idx.co.id during the 2017-2019 period.
Population and Sample
In this study, the total population is all food and beverage sub-sector companies listed on the Indonesia Stock Exchange as many as 25 companies. .
The sampling technique used is purposive sampling, this technique is based on three criteria, namely; (1) listed on the IDX, (2) audit reports, (3) generate profits. From these criteria obtained 16 companies that can be used as samples.
Table 2 List of Sub-Sector Manufacturing Companies that are Sampled
Jurnal Ilmiah Socio Secretum, Vol. 10, No. 1, June 2020: 103-112 Source: Data processed by the author (2021)
Data Types and Sources
The type of data used in this study is qualitative data, which is obtained directly from the company's financial statements that have been audited and published on the Indonesia Stock Exchange (IDX) during the period 2017 to 2019.
The source of data used in this study is from the food and beverage sub-sector using data from the Indonesia Stock Exchange by accessing the www.idx.co.id site.
Method of collecting data
The data collection technique used by the researcher is documentation, namely by collecting secondary data in the form of notes, financial reports, photos, and other information related to this research. Research data obtained through internet media by downloading the reports of manufacturing companies in the food and beverage sub-sector required in this research through the website www.idx.co.id and from the Capital Market Directory (ICMD).
Descriptive statistics are statistics that function to describe or provide an overview of the object under study through sample or population data as it is, without analyzing and making conclusions that apply to the public.
Descriptive analysis is used to describe data statistics such as min, max, mean, and standard deviation.
Normality test, the regression model is used to test and find out whether the residual value generated from the regression is normally distributed or not. One way to detect whether the residuals are normally distributed or not is by statistical tests, namely the Kolmogrov-Smirnov (k-s) non-parametric statistical test. With a significant level of 0.05, the data is declared normally distributed if the significance is greater than 5% or 0.05.
Classic Assumption
The multicollinearity test aims to test whether there is a correlation between the independent variables in the regression model. to detect multicollinearity in this study is to look at the value of VIF (Variance Inflation Factor). If the value of VIF < 5 then there is no multicollinearity between the independent variables.
Meanwhile, if the VIF value > 5, it means that there is multicollinearity between the independent variables.
The heteroscedasticity test aims to test whether in the regression model there is an inequality of variance from the residuals of one observation to another observation. The method used to test heteroscedasticity is to use the scatterplots test.
Autocorrelation is one of the deviation problems in multiple linear regression. The test used to determine autocorrelation is the Durbin-Watson test through the SPSS program.
Multiple Linear Regression Analysis, is used to build an equation that connects the dependent variable (Y) with the independent variable (X) and at the same time to determine the forecast value or prediction.
Hypothesis test,
The t-test (t-Test), the t-test is used to partially test the effect of the independent variable on the dependent variable, the t-table can be seen in the statistical table at 0.05 significant with degrees of freedom df = n-k-1.
F test (simultaneous test), F-test is used to test the effect of independent variables together on the dependent variable of a regression equation.
The Coefficient of Determination Test (R2), the coefficient of determination test (R²) is the number of how far the regression equation matches the multiple-determination coefficient data that can be used to determine the contribution of the entire independent variable (X) to the dependent variable (Y).
RESULTS AND DISCUSSION Research Variable Data
Table 3 Data on Short Term Debt (STD), Long Term Debt Equity (LTDE) and Return On Assets (ROA) for Food and Beverage companies listed on the Indonesia Stock Exchange in 2018-2020 (Calculation in Millions of Rupiah).
Descriptive Statistics of Research Variables
Table 4. Descriptive Statistical Results
Source: SPSS 20 . output data processing
Based on the descriptive statistics of the research variables presented in the table above, it can be interpreted as follows:
Variable Short-Term Debt (X1) has a minimum value of 0.061 and a maximum value of 5.054 with an average of 0.581 and a standard deviation of 0.791. The amount of data studied is 48.
Variable Long-Term Debt (X2) has a minimum value of 0.02 and a maximum value of 1.02 with an average of 0.21 and a standard deviation of 0.209. The number of data studied is 48.
The Return On Asset (Y) variable has a drinking value of 0.0005 and a maximum value of 0.8121 with an average of 0.1382 and a standard deviation of 0.1581. The amount of data studied is 48.
Classic assumption test Normality test
Jurnal Ilmiah Socio Secretum, Vol. 10, No. 1, June 2020: 103-112
Table 5. Normality Test Results before transformation
Source: SPSS 20 . output data processing
After transforming the data on the normality test using SPSS Version 20.
Table 6.Normality Test Results after transformation
From the statistical analysis of the Kolmogorov-Smirnov test, it was obtained that the company's significant value was 0.3 > 0.05. From the significant value above, it shows that all the variables used are normally distributed. For clarity, the following histogram and p-plot graphs of normally distributed data can be attached.
Source: SPPS Statistical Output data processing 22 Figure 1 Probability Plot Of Regression Normality Test Results
Based on the histogram graphic above, it shows that the data is normally distributed. This can be seen from the histogram graph which shows the data distribution has followed the diagonal line.
Source: SPPS Statistical Output data processing 22 Figure 2 Probability Plot Of Regression Normality Test Results
From the Probability plot graphic above, it can be seen that the results of the normal p-p plot of regression standardized residual show that the points follow and approach the diagonal line so that it can be concluded that the regression model meets the assumption of normality.
Multicollinearity Test
Table 7. Multicollinearity Test Results
From table 4.4 above shows that the tolerance value of Short-Term Debt and Long-Term Debt is 0.738, meaning that it is above 0.1 and the VIF value of the Short-Term Debt variable is 1.356, Long-Term Debt is 1.356, meaning it is still less than 5, it can be concluded that there is no multicollinearity occurs.
Heteroscedasticity Test
Source: SPSS Statistical Output data processing 22
Based on the results of the scatterplots above, it is known that the data points spread above and below or around the number 0 (zero), the points do not only collect above or below, and the spread of the data points is
Jurnal Ilmiah Socio Secretum, Vol. 10, No. 1, June 2020: 103-112
Table 8.Autocorrelation Test Results After Transformation
The results of the autocorrelation test in the table above show that the Durbin-Watson value is 1.569, meaning -2 < 1.569 <+2. So it can be concluded that there is no autocorrelation in the regression model in this study.
Multiple Linear Regression
Table 9. Multiple regression linear results after transformation
Source: SPSS 20 Statistical Output Data Processing
Based on the table above, the following regression equation is obtained:
Y = a + b1 X1 + b2X2
Y = -0.976 + -0.079 X1 + -0.292 X2
The regression equation above can be explained as follows:
The constant (a) is -0.976: meaning that if the Short-Term Debt (X1) and Long-Term Debt (X2) are zero (0), then the Return On Asset (Y) value is -0.976.
The regression coefficient of the Short-Term Debt (X1) variable is -0.079: meaning that if the other independent variables have a fixed value and Short-Term Debt has increased, the Return On Assets will decrease by -0.079.
The regression coefficient of the Long-Term Debt (X2) variable is -0.292: it means that if the other independent variables have a fixed value and Long-Term Debt has increased, the Return On Asset (Y) will decrease by -0.292.
Hypothesis test
Partial Significance Test (t test)
Table 10 T-Test Results After Transformation
Source: data processing SPSS 22 . statistical output
At the SPSS output above tcount, when consulted in ttable (attached) for an error of 5%, it is obtained ttable
= 2.014.
The effect of Short-Term Debt has no significant effect on Return On Assets, this can be seen from the significant value of 0.479 > 0.05 and the value of tcount > ttable or -0.079 <2.014.
The effect of Long-Term Debt has no significant effect on Return On Assets, this can be seen from the significant value of 0.488 > 0.05 and the value of tcount > ttable or -0.292 > 2.014.
Simultaneous Test (F Test)
Table 11 f-test results after transformation
Based on the results of the simultaneous test in the table above, it shows that the fcount value is 47.796 and ftable can be seen in the statistical table, it is obtained ftable = 3.20. So it can be concluded that fcount >
ftable (47.796 > 3.20) and 0.368 > 0.05, meaning Ho is rejected and Ha is accepted. This means that short- term debt and long-term debt have a simultaneous effect on return on assets in the 2017-2019 period.
Coefficient of Determination Test (R2)
Table 12 Coefficient of Determination Test Results (R2)
Based on the test results in the table above, it can be seen that the resulting R2 value is 0.043, meaning that the percentage contribution of the influence of the variables of Short-Term Debt and Long-Term Debt to Return On Assets is 4.3%, while the remaining 95.7% is influenced by other variables. not included in this study or there are other factors that affect profitability, namely sales growth, debt to equity ratio, and company size.
CONCLUSION
Based on the research results, it can be concluded partially (t-test) that the Short-Term Debt Variable has no effect on Return On Assets in manufacturing companies listed on the Indonesia Stock Exchange for the 2017-2019 period. The Long-Term Debt variable has no effect on Return On Assets in manufacturing companies listed on the Indonesia Stock Exchange for the 2017-2019 period. The results of the Significant Test (f-test) according to the basis for decision making in the f-test can be concluded that Short-Term Debt and Long-Term Debt simultaneously affect manufacturing companies listed on the Indonesia Stock Exchange for the 2017-2019 period. The test value of the Determinant coefficient (R2) produced is 0.043, meaning that the presentation of the contribution of the influence of the variable Short-Term Debt and Long-Term Debt on Return On Assets has a relationship of 4.3% while the remaining 95.7% is influenced by other variables that are not included. in this research.
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