Company Internal Factors and Their Influences on Financial Performance: Panel Data Analysis

This research aims to systematically, actual, and accurately explain the facts and characteristics of the company and their effect on financial performance. Data in the form of time-series data from 2015-2019 and cross-section data collected from the financial statements of automotive companies listed on the Indonesia Stock Exchange then obtained nine companies that meet the criteria. The independent variables are Firm Size, Leverage, Liquidity, and the dependent variable is financial performance as proxied by Return On Equity (ROA). The research used panel data techniques; Common Effect Model, Fixed Effect Model, and Random Effect Model. The results show that Firm Size partially has a negative and significant effect, meaning that the greater the assets owned by the company, the more complex the agency problems faced. The partial leverage variable has a negative and significant effect, means that the use of relatively high debt will cause fixed costs in the form of interest expenses and loan principal installments to be paid, the greater the fixed costs. The liquidity variable partially has a positive and insignificant effect. This means that changes that occur in both the number of current assets or current liabilities affect increasing profits so that the increase in Liquidity (CR) or the level of liquidity affects changes in increasing company performance (ROA).

business expansion through acquisitions or mergers, profit growth, product development, diversification, and an increase in the number of company employees (Kouser, 2012). Company performance can be measured in different ways and by applying various methods. The method generally used is the profitability ratio (Nires, 2014).
The company's financial performance is influenced by several factors, including the ratio leverage, Liquidity, and Firm Size. Leverage is an essential tool in measuring the effectiveness of the use of corporate debt. Leverage is the company's ability to meet both short-term and long-term financial obligations. Leverage arises because the company uses assets and sources of funds that cause a fixed burden for the company. According to , the higher the value, the greater the leverage debt owed by the company than the capital, so the costs that must be borne by the company to fulfill obligations will be greater and has an impact on the decline in the company's profitability. Putra (2015) results stated that leverage has a negative and significant effect on financial performance. The results of this study are supported by Sukadana (2018), Wibowo (2012), Mualifah (2017), Purnamasari (2017) and Gunde (2017) which states that leverage has a significant negative effect on financial performance. Meanwhile, the additional research disclosed by Atika (2016) stated that the leverage significantly affects the financial performance.
One of the factors affecting subsequent financial performance is liquidity. Liquidity is the company's ability to pay off short-term financial obligations. There are three types of liquidity ratios often used: (1) the current ratio, the quick ratio, and the cash ratio. The higher the company's liquidity value, the smaller the risk of the company's failure to meet long-term obligations (Widystuti, 2019). The high liquidity value of the company will reduce the uncertainty of investors but indicate the existence of idle funds. The liquidity that is too high indicates an excess of cash or current assets than needed. The results of research by Asandimitra (2014) state that the liquidity variable has a positive and significant effect on financial performance. The research was supported by the results of research Durrah (2016) Utami (2016) and Odalo (2016) states that liquidity has a significant positive effect on financial performance. While the research results Sari et al. (2017) showed that liquidity does not affect the financial performance.
In addition to leverage and liquidity, another factor that affects a company's financial performance is firm size. Firm size describes a company indicated by total assets, total sales, average sales, and average total assets. Firm size can affect when the company makes a loan. Large companies will have ample assets to be used as collateral for funding sources to obtain loans. Companies with large sizes will have easy access to sources of funds, either the capital market or banking, to obtain investment to increase profits. The results of Sulastri's research (2016) show that firm size has no significant effect on financial performance. The results of this study are supported by , Fachrudin (2011), Epi (2017 and Tambunan (2018) which states that firm size has no significant effect on financial performance. In contrast to Lusiyati and Salsiyah (2013), firm size significantly affects the company's financial performance. Based on the explanation on the background, there are still inconsistent research results from several previous research results on the variables of liquidity, leverage, and Firm size on the company's financial performance. From the results of previous studies, several variables affect the company's financial performance, which still shows different results and even contradict the results of one study with another. This is what will be appointed as a research gap in this study.

B. Literature Review 1. The Effect of Leverage on the Company's Financial Performance
Companies that use sources of funds from debt need to consider the company's ability to pay its fixed obligations. Therefore, companies need todetermine the optimal debt burden of the company. The selection of less than optimal leverage will cause a decrease in the profitability or productivity of the company, which will result in a decrease inthe value of the company, which is characterized by significant corporate losses.
As for the research conducted by Sukadana and Triaryati (2018), leverage has a significant negative effect on profitability (company performance). The results of research conducted by Putra and Badjra (2015), Mualifah et al. (2017), and Purnamasari (2017) also state that leverage has a significant negative effect on profitability. Meanwhile, different results were obtained by Ashari and Smapurno (2017), where leverage has a significant positive effect on the profitability or financial performance of the company. This research is supported by Atika's research (2016). So the first hypothesis the author formulates is as follows.
H1: Leverage has a significant negative effect on financial performance.

Influence of Liquidity on Company Financial Performance
Liquidity plays an essential role in the success of a company's business because the company must ensure that the company does not experience a shortage or excess liquidityto meet its short-term obligations (Mariah, 2015). Companies with high liquidity ratios are at-risk of low but strong profitability. Companies with large amounts of working capital will have an impactnegative, namely because cash is an inactive fund, the company's profitability is lost, Which means cash that does not generate income because it is only stored. Ardiansyah (2014) research states that the liquidity variable has a positive and significant effect on financial performance. The results of this study are supported by the results of research conducted by Durrah (2016), Utami (2016), and Odalo (2016), which state that liquidity has a significant positive effect on financial performance. While the results of research by Sari et al. (2017) show that liquidity does not affect financial performance. This research is supported by the results of Lusiyati and Salsiyah (2013). So that the second hypothesis the author formulates as follows.
H2: Liquidity has a significant positive effect on performance

Firm size influences the company's financial performance.
Every company must prepare to report positive profit growth in the hope ofattracting investors to invest their capital. Big companies are negatively given less riskbecause they have more access or opportunities to enter the marketcapital to raise funds and increase profitability. The company's size is one of the factors that affect profitability, which can be seen from the company's total assets. Firm Size increase can show the size of the company's profitability. Likewise, assetscompany is used to support the company's operations, to create company profits.
This means that Firm size determines the profitability of the company. Research conducted by Sulastri (2016) concluded that Firm size has a positive and insignificant effect on financial performance. The results of this study are supported by , Fachrudin (2011), Epi (2017, and Tambunan (2018), which state that firm size has no significant effect on financial performance. In contrast to Lusiyati and Salsiyah (2013), firm size significantly affects the company's financial performance. So that the third hypothesis the author formulates is as follows.
H3: Firm size has no significant positive effect on financial performance.

C. Research Methodology
The purpose of this study is to systematically, actual, and accurately explain the facts and characteristics of a company and their effect on financial performance, which is done by identifying existing problems and solving problems faced by the company. The type of research used is descriptive quantitative research. The data used are time series from 2015-2019 and cross-sections collected from automotive companies' financial statements listed on the Indonesia Stock Exchange. Then determine the number of samples that meet the criteria for use in this study as many as nine companies.
The dependent variable in this study is financial performance proxied by Return On Equity (ROA) because ROA can show the company's ability to generate profits based on certain shares. Variable data in the form of ratios that can be obtained from financial statements or can be calculated by net income divided by capital.
While the independent variable is Firm Size (shown by total assets, total sales, total profit, tax expense, and others). Leverage (in this study used Debt to Equity Ratio (DER) DER is a ratio that compares the amount of debt with equity), liquidity (in this study used Current Ratio (CR) Current ratio (current ratio) is the company's ability to meet its obligations when it matures.
The data analysis method used is the quantitative analysis method using panel data. Panel data is a combination of time-series data and data cross-section. They use three estimation methods, namely the estimation of the Common Effect Model, Fixed Effect Model, and Random Effect Model. The selection of this method is adjusted to the research data and estimation test results. Before performing regression analysis, the first step is to test the classical assumptions and then continue to test the model specifications to get the best model to be used in the study (Gujarati, 2013). After selecting the model, the next step is to test the hypothesis. In this study, the data analysis process was carried out with the help of the Eviews ten program. The following model was used.

D. Results And Discussion
After the Jakarta Stock Exchange was separated from the Bapepam Institution in 1992 and privatized, the capital market began to experience very rapid growth. The capital market proliferated in the period 1992 -1997. The crisis in Southeast Asia in 1977 caused the capital market to fall. Composite Stock Price Index (JCI SG) drops to the lowest position. However, the capital market issue cannot be separated from the flow of investment that will determine the economic growth of a region; Indonesia and other countries in Southeast Asia are no exception. Based on the predetermined criteria, nine automotive companies were obtained that met the criteria and became the samples in this study during the 2015 -2019 period.

Descriptive Statistics
Statistical analysis was used to determine a description of data seen from the maximum value, minimum value, average value (mean), and standard deviation value. The variables of this study consist of firm size, leverage, and liquidity as independent variables and the company's financial performance as the dependent variable. Descriptive statistical test results can be seen in the following table:

Classical Assumption a. Multicollinearity Test
The test is used to test whether there is a correlation between independent variables in a regression model. If the correlation coefficient between independent variables is more than 0.8, it can be concluded that the model has multicollinearity problems. On the other hand, if the correlation coefficient is less than 0.8, the model is free from multicollinearity problems.

Source: Data Processed
Multicollinearity of test results using reviews in Table 3 can explain that all the variables used in the study avoided multicollinearity. The results of all multicollinearity tests for all variables have a correlation coefficient value of 0.8.

b. Autocorrelation Test
According to Ghozali (2016: 107), autocorrelation test aims to test whether in a linear regression model there is a correlation between the confounding error in period t and the error in period t 1 (previous). A good regression model is a regression that is free from autocorrelation. The autocorrelation test in this study used the LM test. The following are the results based on the LM test. The results of Table 4 shows, the hypothesis in the autocorrelation test is (1) H0: there is no autocorrelation, and (2) H1: there is autocorrelation. To find out the LM test results, what is seen is the result of the value Chi-Square Prob (2), which is the p-value of the test Breusch-Godfrey Serial Correlation LM. If the value is more than 0.05, then there is no autocorrelation. The results of the autocorrelation test show the Prob Chi-Square(2) value of 0.9852 which means more than 0.05, so it can be concluded that there is no autocorrelation.

c. Heteroscedasticity Test
The test is used to see whether the residuals of the formed model have a constant variance or not. In order to test the presence of heteroscedasticity in this study, the White Test straightforward method was used. The following are the results of the White Test that has been carried out.

d. Normality Test
The test aims to determine whether the regression model of the confounding variable or residual usually is distributed or not. In this study, the normality test was carried out using the Jarque-Bera Test; if the probability value of Jarque-Bera> 0.05, the residuals were normally distributed. Following are the results of the normality test using the Jarque-Bera Test.

e. Model Selection Test Results
Before setting the estimation of the research model, the first step is to choose a panel data regression model.In the estimation of the panel data

f. The Chow
The test was conducted to select the model to be used, whether the Fixed Effect Model (FEM ) or the Common Effect Model (CEM ). By making decisions using the hypothesis on the Chow test, if the F test shows a probability of less than 0.05, then H 0 is accepted, and H 1 is rejected, which means that the best regression model to use is FEM . M eanwhile, if the F test shows a probability of more than 0.05, then H 0 is rejected, and H 1 is accepted, indicating that the model used is the CEM model. The results of the Chow test calculation with a significant level of 0.05 are as follows:

g. Hausman Test
The test is conducted to select the Random Effect Model (REM) or the Fixed Effect Model (FEM). If the chi-square probability value is less than 0.05, it means that the best model used is REM. Meanwhile, if the probability value is more than 0.05 chi-square, then H0 and H1 are accepted, meaning the best model is FEM. The following are the Hausman test results.  Simultaneous or simultaneous hypothesis testing produces F-statistics = 34.87101 with probability of 0.000000 the test results indicate the probability is less than 0.05, so reject H0 and accept H1. that is, Collaborative variable firm size, leverage, and liquidity significantly influence the company's financial performance automotive companies listed on the Stock Exchange.

Partial Hypothesis Test
The hypothesis test is used to see whether the independent variable has an individual effect on the dependent variable. The simultaneous test can be seen using t count. The test criteria if the t-count probability is less than 0.05, then H0 is rejected, and H1 is accepted. This means that the independent variable has a significant effect on the dependent variable individually.The results of the partial hypothesis test are: ah as follows:  Table 10 can be explained that based on the results of the partial test, it is shown that the influence of Firm size on the financial performance of automotive companies listed on the IDX with a regression coefficient of -3.444526 with a t value of -9.537186 and a probability value of 0.0000. The test results show that the coefficient is negative, and the probability is less than 0.05. This means rejecting H0 and accepting H1. It is concluded that there is a partially significant negative effect of the variable Firm size on the financial performance of automotive companies listed on the IDX.
Partial hypothesis testing by leverage on the financial performance of automotive companies listed on the IDX produces a regression coefficient of -0.191253 and an at-count value of -4.162511 with a probability value of 0.0002. The test results show a negative coefficient, and the probability is less than 0.05. This means that H0 is rejected and H1 is accepted. So that there is a partially significant negative effect of the variable Firm size on the financial performance of automotive companies listed on the IDX.
The partial test results on the effect of liquidity on the financial performance of listed automotive companies show a coefficient of 0.701808, an at-count value of 1.383561, and a probability value of 0.1758. The test results show a positive coefficient and a probability of more than 0.05. So that there is a partially insignificant positive effect of the liquidity variable on the financial performance of automotive companies listed on the IDX.

Empirical Model of Panel Data Regression
The regression equation from the regression estimation results is as follows: ROE = -10.56432 -3.444526SIZE -0.191253LEV + 0.701808CR The regression estimation above can be explained as follows: 1) SIZE coefficient of -3,444526 indicates that firm size hurts the company's financial performance. If there is an increase in Firm size by 1%, it will reduce the company's financial performance by 3.444526%. 2) The coefficient leverage of -0.191253 indicates that leverage hurts the company's financial performance. If there is an increase in leverage of 1%, it will reduce the company's financial performance by 0.191253%. 3) The liquidity coefficient of 0.701808 indicates that liquidity positively affects the company's financial performance. If there is an increase in liquidity by 1%, it will increase the company's financial performance by 0.191253%.

Analysis of the Results of the Coefficient of Determination
The results of the coefficient of determination from the panel data regression model are as follows: The magnitude of the contribution of variables Firm size, leverage, and liquidity to the company's financial performance is known through the coefficient of determination (adjusted R-Squared) equal to 0.894378 or 89.4378%. These results indicate that the company's financial performance diversity can be explained by firm size, leverage, and liquidity of 89.4378%. While the remaining 10.5612% is explained by other variables not discussed in this study. Based on the value R-Squared 0.920784, it can be seen that the relationship between the independent variable and the dependent variable has a strong correlation pattern because the value of 0.920784 is close to 1.
This study confirms the suitability of theories, opinions, and previous research that have been stated previously and behavioral patterns that must be done to overcome this. There are 3 (three) main sections that will be discussed in the analysis of the findings of this study, namely as follows: 1.
Effect of Firm Size on Company's Financial Performance Based on the results of multiple regression analysis of panel data with Fixed Effect Model (FEM), Firm size (Size) has a negative and significant effect on the financial performance of automotive companies listed on the IDX. These results do not align with the proposed hypothesis; namely, the variable Firm size has a significant positive effect. This is supported by research by Lusiyati and Salsiyah (2013), which states that Firm size has a significant effect on the company's financial performance. Based on the analysis results that obtained negative and significant results, this could happen because the greater the assets owned by a company, the more complex the agency problems faced. Thus it will increase the expenses incurred for the company's operations to reduce the net profit generated by the company, and the resulting rate of return on investment will also decrease. In addition, with the larger the size of a company, the company will require higher costs to carry out operational activities such as labor costs, general and administrative costs, as well as building maintenance costs, machinery, vehicles, and equipment so that it will be able to reduce the company's profitability (Sari and Budiasih, 2014).

2.
Effect of Leverage on Company Financial Performance Based on the multiple regression analysis of panel data with the Fixed Effect Model (FEM), leverage has a negative and significant effect on the financial performance of automotive companies listed on the IDX. These results align with the proposed hypothesis, namely that the variable leverage has a negative and significant effect. The results of this study are supported by Sukadana and Triaryati (2018), which show that the variable leverage has a significant negative effect on profitability (company performance). The results of research conducted by Putra and Badjra (2015), Mualifah et al. (2017), and Purnamasari (2017) also state that leverage has a significant negative effect on profitability. Brigham and Houston (2010) state that companies with very high returns on investment use relatively small amounts of debt. The high rate of return allows the company to do most of its funding through internally generated funds (Brigham, 2006). This follows the pecking order theory, which states that profitable companies prefer internal to external funding. The results of this study follow the Pecking Order Theory, which states that the greater the use of debt, indicating that the greater the costs that must be borne by the company to fulfill its obligations so that it can reduce the profitability of the company. This is because high debt can lead to fixed costs in the form of interest expenses and principal installments that must be paid, and the greater the fixed costs can result in a decrease in company profits (Halim, 2015).

3.
Effect of Liquidity on Company Financial Performance Based on the multiple regression analysis of panel data with the Fixed Effect Model (FEM), liquidity has a positive and insignificant effect on the financial performance of automotive companies listed on the IDX. These results are not in line with the proposed hypothesis, namely the liquidity variable has a positive and significant effect. The results of this study are supported by the results of Sari et al. (2017), which shows that liquidity has no significant effect on financial performance. This research is supported by the results of research by Lusiyati and Salsiyah (2013), which states that the liquidity variable has no significant effect on financial performance. Referring to the research results, which states that the liquidity variable has a positive effect but is not significant, it can be explained that company managers must maintain the company's liquidity level because if the level of liquidity is good, the company is generating profits very effective. After all, investors believe in investing in the company because changes in the Current Ratio positively affect changes in Return On Assets ( ROA). The results of this study indicate that any changes that occur either in the number of current assets or current liabilities effect on increasing profits, so that an increase in Liquidity (CR) or high and low liquidity values affect changes in increasing company performance (ROA).

E. Conclusion
This study aims to examine how the influence of firm size, leverage, and liquidity on the company's financial performance. Based on the results of multiple regression analysis with Fixed Effect Model (FEM), it can be concluded as follows: variable Firm size partially has a negative and significant effect. This is evidenced by the calculated t value of -9.537186 with a probability value of 0.0000. This shows that the greater the assets owned by a company, the more complex the agency problems faced.
The variable leverage partially has a negative and significant effect. This is evidenced by the t-count value of -4.162511 with a probability value of 0.0002. This proves that high debt can cause fixed costs in the form of interest rates and principal loan installments that must be paid. The greater the fixed costs in a company can result in a decline in the company's finances. The liquidity variable partially has a positive and insignificant effect. This is evidenced by the t-count value of 1.383561 with a probability value of 0.1758. This shows that changes in the number of current assets or current liabilities affect increasing profits. Increasing Liquidity (CR) or high and low liquidity values affect changes in increasing company performance (ROA).