Vol. 10, No. 1, June 2020, pp. 65-70
ISSN: 2720-9830. 65
The Effect Of Working Capital On Profit In Automotive Companies Listed On The Indonesia Stock Exchange (Idx)
Dono Bonardo Pasaribu Universitas Darma Agung
Article Info ABSTRACT
Article history:
Received April 2020 Revised May 2020 Accepted June 2020
The purpose of this study was to determine the effect of working capital on profitability in manufacturing companies listed on the Indonesia stock exchange in 2018-2020. The research object used is limited to automotive companies listed on the Indonesia Stock Exchange with the population in this study as many as 12 automotive sector companies. With a sample of 9 companies so that the amount of data obtained is 27 data. The data collection technique uses documentation techniques with the collection of financial statements from each sample published on the www.idx.co.id website. The data used is quantitative data in the form of secondary data. The data collection method used is literature and field research, the analytical method used is descriptive statistics, classical assumption test, simple linear regression analysis and hypothesis testing in the form of partial significant test (t test). The simple linear regression equation is Y = 0.036 + 0.012 X. As for the results of the research that has been done, it is concluded that working capital has an effect on profit which can be seen from the t value > t table 1.706.). The correlation coefficient (R) is 0.485 which states that the correlation between working capital and profit is low. The results of R square with a value of 0.205 or 20.5% of the variables of profit are explained by the independent variable (working capital) while the remaining 79.5% is explained by other variables not examined by the author. As for suggestions to automotive companies listed on the Indonesia Stock Exchange in this study, it has been proven that working capital is very influential on profits, so working capital should be used effectively so that profits increase, if profits increase then in the following year working capital will also increase and vice versa.
Keywords:
profit
Working Capital
This is an open access article under the CC BY-SA license.
Corresponding Author:
Dono Bonardo Pasaribu Universitas Darma Agung
Email: [email protected]
INTRODUCTION
Globalization is an era where the business world is required to be more effective in running its business. This is because there are no more boundaries that arise between countries. Including in business and business competition. Every company is required to be able to manage its company well in order to compete with other companies, both for domestic companies and foreign companies. One indicator that can be used to assess a well-managed company is how these companies manage their working capital. Working capital is a very important issue for every company. Working capital is needed to finance the company's daily operating
Jurnal Ilmiah Socio Secretum, Vol. 10, No. 1, June 2020: 65-70
responsibility of the financial manager to manage or manage the potential sources of funds to be converted into sustainable added value (sustainable).
The availability of sufficient working capital can be used immediately in operations depending on the type or nature of the current assets owned by the company such as cash (securities), receivables, and inventories. The faster the level of each element of working capital, the working capital can be said to be efficient, but if the turnover is slower then the use of working capital in the company is less efficient. But working capital is sufficient in number in the sense that it must be able to finance the company's daily expenses or operations, because with sufficient working capital it will be profitable for the company, especially in obtaining profits, in addition to allowing the company to operate economically or efficiently and the company does not experience difficulties. finance, will also provide several other advantages. The company's ability to generate profits during a certain period is called profitability. The profitability ratio is a ratio to assess the company's ability to seek profit. Profitability can be used as a benchmark to assess the success of a company in running its business and can also be used as a benchmark in assessing the prospects for the return of capital invested by investors. As for the company's profitability can be used to assess the company's ability to use working capital effectively to generate a certain level of profit that is expected.
Imports have soared because there are still many automotive components that cannot be produced domestically, this condition shows the company is still not able to manage its business properly, plus the national automotive industry is still very dependent on imports. With this, the use of working capital will be even greater.
Scope of problem
In optimizing the research to be carried out, the author will limit the problem, namely working capital to company profits for the 2018-2020 period in the Automotive Sub-Sector Manufacturing Company and its Components listed on the Indonesia Stock Exchange.
Formulation of the problem
Based on the above background, the formulation of the problem can be made, namely: Does Working Capital Affect Profits in Automotive Sub-Sector Manufacturing Companies listed on the Indonesia Stock Exchange.
Research purposes
The objectives of this research are:
To find out empirically the effect of working capital on the net in the Automotive Component Sub-Sector Manufacturing Companies listed on the Indonesia Stock Exchange
Benefits of research
This research is expected to be used as a comparison between the theory that has been obtained during college with practice or the reality that occurs in the company.
METHOD
Research Time and Location
The research was conducted on the Indonesia Stock Exchange using www.idx.co.id. The author chose to conduct research in this place due to the availability of open data sources and easier data collection processes, this research was conducted from April 2021 to August 2021.
Sample and population
The population in this study are automotive companies listed on the Indonesia Stock Exchange (IDX) for the 2018-2020 period which were obtained through www.idx.co.id, totaling 12 companies.
The research sample that has been carried out is 9 automotive companies listed on the Indonesia Stock Exchange during 2018-2020 from 12 manufacturing companies listed on the Indonesia Stock Exchange.
Operational Definition and Measurement of Variables Dependent Variable
The dependent variable in this study is profit, which is the result of a series of policies and decisions. A summary of operational definitions and measurement of variables in this study can be seen in the table below, as follows:
Table 1 Operational Definitions and Measurement of Variables
Processed: Author (2021).
Independent Variable
According to Sugiyono (2015:38) Independent variables are variables that are often referred to as stimulus, predictor, and antecedent variables. In Indonesian it is often referred to as the independent variable. The independent variable is a variable that affects or is the cause of its change or the emergence of a dependent variable (bound).
Data Types and Data Sources
The data used in this research is secondary data. Secondary data is data that has gone through a processing process first obtained from relevant data sources and can be trusted for its truth. The secondary data in this study was taken from the Indonesia Stock Exchange through the International network using the www.idx.co.id page
Method of collecting data
Data collection method is a method used to research and collect relevant data or information in the preparation of the thesis, in this study the author uses the following methods:
Research (Library Research)
Library research is research that aims to collect data from information and various materials contained in the library room, such as books related to the problem under study, lecture notes, documents, diktat or articles related to the title of this thesis.
Field Research (Field Research)
Research conducted directly on the object of research in the field by means of observation and observation techniques.
Methods of Data Analysis and Hypothesis Testing Descriptive statistics
Descriptive analysis aims to provide an explanation of the variables to be observed. Analysis of the ratios to find the values / numbers from the variable x (working capital), and the variable y (company profit) which is used to determine and describe the minimum value, maximum value, mean (average) and standard deviation (spread of data) of each variable.
Classic assumption test
The regression model will produce an unusual estimator if it meets the classical assumptions, namely free of multicollinearity, autocorrelation, and heteroscedasticity. If the regression model obtained deviates from one of the classical assumptions tested, then the regression equation obtained is inefficient to generalize the research results in the form of samples to the population because there will be a bias, which means that the research results are not only the influence of the variables studied but there are other confounding factors that influence it.
Heteroscedasticity Test
To test whether in a regression model there is an inequality of variance from the residual of one observation to another observation. The test is carried out to see whether there is a certain pattern on the scatter plot graph. If the scatter plot shows a pattern. Heteroscedasticity testing is carried out with a specific purpose, then there is heteroscedasticity. If the points spread above and below zero on the Y axis, then there is no heteroscedasticity.
Multicollinearity Test
A regression model contains multicollinearity if there is a perfect relationship between the independent variables or there is a linear correlation. The consequence is that the standard error of estimation will tend to increase as the independent variable increases, the level of significance used to reject the null hypothesis will
Jurnal Ilmiah Socio Secretum, Vol. 10, No. 1, June 2020: 65-70
will range from 0 to 1, if the value of the coefficient of determination = 1 indicates 100% of the total variation is explained by the variance of the regression equation, or the independent variable is able to explain the Y variable by 100%. On the other hand, if the coefficient of determination = 0 indicates that there is no total variance explained by the independent variance.
RESULTS AND DISCUSSION Descriptive Research Object
History of Indonesia Stock Exchange Company
The Indonesia Stock Exchange or IDX is one of the stock exchanges that can provide investment opportunities and sources of financing in an effort to support national economic development. The Indonesia Stock Exchange also plays a role in efforts to develop large and solid local investors to achieve a stable Indonesian capital market. The Indonesia Stock Exchange is a place for stock trading transactions of various types of companies in Indonesia. There are two types of companies listed on the Indonesia Stock Exchange, namely manufacturing and service companies.
The history of the Indonesia Stock Exchange began with the opening of a stock exchange by the Dutch East Indies government in 1912 in Batavia. The Jakarta Stock Exchange was briefly closed during the First World War period and then reopened in 1952. Apart from the Jakarta Stock Exchange, the colonial government also operated Parel Exchanges in Surabaya and Semarang. After being closed several times due to wars, the Batavia Stock Exchange was re-opened in 1977 under the supervision of the Capital Market Agency, a new institution under the Ministry of Finance.
Descriptive Statistics of Research Variables
Descriptive statistics are used to show the amount of data (N) used in this study and can show the maximum, minimum, average value (mean) and deviation of each variable.
Table 2. Descriptive Statistics of Research Variables
The following is an explanation of table 2
The working capital variable (X) has a minimum value of 0.03 and a maximum value of 8.87 with an average of 2.5048 and a standard deviation of 2.20637. The amount of data studied 27.
Profit variable (Y) has a minimum value of 0.00 and a maximum of 0.21 with an average of 0.0652 and a standard deviation of 0.05272 The number of data studied 27.
Classic assumption test Normality test
Normality test aims to test whether the regression model found a correlation between the independent variable and the dependent variable. If a variable is not normally distributed, then the results of statistical tests will decrease. The normality test of the data can be done using the One Sample Kolmogrov Smirnov test, with the condition that if the significant value is above 5% or 0.05, the data has a normal distribution.
Source: SPSS 2021 Output
From the results of the data processing table above, it is obtained that the Test Statistic value is 0.136> 0.05 and based on the Asymp value is obtained 0.200> 0.05. So it can be concluded that the data is normally distributed. Based on the picture below as a whole it can be concluded that the data observation values have been normally distributed and can be continued with other classical assumptions. For clarity, the following can be attached a histogram graph and a plot of normally distributed data.
Source: SPSS 2021 Output Figure 1 Histogram of Normality Test
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. The results of the normality test using histogram graphs show that the data distribution follows a bell-shaped curve.
Multicollinearity Test
Multicollinearity test was conducted to determine the magnitude of the intercorrelation between the variables in the study. If there is a correlation, it is called a multicollinearity problem to detect the presence or absence of multicollinearity at the tolerance and VIF values. If the tolerance value is above 0.1 and the VIF value is below 10, there will be collinearity. The results of the multicollinearity test for the regression model in this study are presented in the table below.
Table 3 Multicollinearity Test Results
Source: SPSS 2021 Output
Table 4.4 above shows that all working capital variables have tolerance above 0.1 and VIF value below 10, so it can be concluded that the regression model in this study does not occur multicollinearity.
Interpretation of Research Results Effect of Working Capital on Profit
The results of the Kolmogorov-Smirnov test were obtained by Asymp. Sig. (2-tayled) of 0.200 where the value of Asymp. Sig. (2-tayled) > significant value (0.005) so that the data is normally distributed.
The results of the analysis of determination (R-square) with a value of 0.205 which means that 20.5% of the
Jurnal Ilmiah Socio Secretum, Vol. 10, No. 1, June 2020: 65-70
thesis "Effect of working capital on net income at PT Mayora Indah Tbk for the period 2007-2016". which states that working capital has a significant effect on net income, where the tcount value is 6,283 which is greater than the ttable value of 4.424, or with a significance value of less than 0.05 (sig value .000 <0.05).
CONCLUSION
From the results of research on the effect of working capital on profits in automotive companies listed on the Indonesia Stock Exchange (IDX), it can be concluded that: Working capital partially affects the profits of automotive companies listed on the Indonesia Stock Exchange for the 2018-2020 period. This is because the results of the t-test calculation obtained t-count of 2.774 with a sig value of 0.001 <0.05. The value of t count
> t table 1.706. The simple linear regression equation obtained from the research is: Y = 0.036 + 0.012 X + e The constant value of 0.036 indicates that if the value of the Working Capital variable is considered zero, then the profit (Y) is 0.036 The regression coefficient of the Working Capital (X) variable is 0.012: it means that if every increase in Working Capital (X) the profit will increase by 0.012. The value of R shows the relationship between the working capital ratio variable to profit. From the results obtained, it shows a relationship of 0.205, which means that the relationship between the working capital variable (X) and the profit variable (Y) is weak at 20.5%.
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