The Effect of Liquidity, Leverage, Profitability and Company Size on Stock Prices in Mining Companies Listed on the Indonesia Stock Exchange in the Period of 2013-2017

Cite this as: Shelvia Angeline, Jessy Safitri Sitorus, Mustika Indah Sari Sumbayak, Sri Devi Fitriani Purba and David. (2020). The Effect of Liquidity, Leverage, Profitability and Company Size on Stock Prices in Mining Companies Listed on the Indonesia Stock Exchange in the Period of 2013-2017. JURNAL AKSI (Akuntansi dan Sistem Informasi), 5 (2), 74-82. http://doi.org/ 10.32486/aksi.v5i2.515 JURNAL AKSI Akuntansi dan Sistem Informasi http://aksi.pnm.ac.id


INTRODUCTION
Liquidity described as a ratio that represent one company's capability to meet short-term obligations (debt) (Kasmir 2015: 129). Hanie and Saifi (2018) state that, liquidity is used to measure a company's capability to settle company's obligations when due. A company is said to be liquid if it is able to turn assets into cash without impairment. Based on Hery (2017: 284) liquidity is a ratio used to gauge how liquid the firm is.
As revealed by Fahmi (2012: 87) , solvency ratio described as a picture of a company's capability to meet and maintain the company's ability to always be able to meet its obligations in paying debts in a proper time. Hery (2015: 190) states that, solvency ratios are ratios used to gauge the standard to which one company's assets are founded with debt. Jusuf (2014: 55) states that, leverage described as a ratio that signifies the composition of one company's funding sources, especially debt.
Profitability described as a ratio that rates the capability of companies to look for benefit, namely by comparing between various components in financial statements, especially financial statements and income statements (Kasmir 2015: 196). Hery (2017: 317) states that, profitability described as a ratio used to gauge the percent of net income on sales. And according to Munawir (2010: 89) that, profitability is the magnitude of operating profit stated in percentage and net sales.
The size of a company, which is a large-scale company, is generally easier to obtain debt than from a small company because it relates to the creditor's trust in large companies (Namjudin 2013: 316). Sitanggang (2013: 76) states that, the size of companies with large market capitalization or sales shows the company's achievements, companies will more easily get access to sources of funds to obtain additional capital with debt. Ningsapati (2010: 43) also states that, company size described as a rate that represent the size from a company.
According to Hartono (2013: 392), the variable asset size is measured logarithm of the total assets. Asset size is used as a proxy for the size of the company.
As stated by Darmadji and Fakhruddin (2011: 5) that, shares can be described as a mark of ownership of a person or corps in one company or qualified company's liablity. Utari (2014: 245) states that, a company that can live all the time is a company that has a retained profit greater than its share capital, it shows that the company from time to time is able to accumulate capital through retained earnings. Meanwhile According to Wira (2011: 7) Share Prices are a reflection of company performance. In a short period, prices may fluctuate. According to Darmadji and Fakhruddin (2011: 135), supply and demand for stock prices always change every time. Brigham and Houston (2010: 150) state that, if liquidity ratios, asset management, debt management, and profitability all seem nice if these conditions run steadily then the market value ratio will also be high.
As stated by Fahmi (2014: 69) that, indeed for the manager of the company having a high current ratio is considered good, even for creditors considered the company is in a strong state. But for shareholders this is considered not good.
According to Kasmir (2015: 151), leverage is used to gauge the range of which one company's assets are cost with debt. This means what is the amount of debt burden born by the company sacked up to the company's assets. Arisona (2013: 104) states that, the bigger the debt to equity ratio depict the lower its leverage so that its capability to repay debt is low. This tells that this company's risk (financial risk) is relatively high. This means that if the debt to equity ratio is high, the value of the stock price will go down.
As stated by Sartono (2015: 257) that, the used of assets and funding sources that are used by companies that have fixed costs by an outlook to increase beneficial shareholder profits is called leverage.
According to Harahap (2015: 304), profitability shows the number of percentages of net income earned from each sale. If this ratio shows high percentage it will be better since it rates the company's capability to get high benefits. Jumingan (2014: 161) states that, the value generated from profitability gives an important picture because it shows the level of sales success and achievement of the company's profit targets.
As stated by Harmono (2014: 110) that, profitability has a causal relationship to firm value in general the dimension. While the value of the company in a basic concept can be described by the value determined by the price of shares traded in the capital market.
Pujo Gunarso (2014) states that a company is considered as developing if its company size shows the large size so that investors will give good responds and it will bring up the worth of the company. This statement also confirmed by research by Sasongko & Wulandari (2006) in which company size has an influence on stock prices.
According to Gumanti (2011: 222), there are four exogenous or independent variables that clearly affect stock prices. The four variables are: 1. Corporate tax rates 2. Changes in State expenditure or expenditure 3. Changes in nominal money and 4. Potential economic output In this research, there are some independent variables used. They are Liquidity (X1), Leverage (X2), Profitability (X3) and Company Size (X4), while the dependent variable is Stock Price (Y). Where this research purposes to specify and analyse whether the effect of these independent variables on stock prices, the conceptual framework can be described as follows.

MATERIALS AND METHODS
This research was established on mining sub-sector companies listed on the Indonesia Stock Exchange in 2013-2017 through the website www.idx.co.id. and through each company's official website. The research approach used in this research is a quantitative research method. Based on Sugiyono (2017: 7), quantitative research methods are often called traditional, positivistic, scientific and discovery methods. This method is called the traditional method because this method has been used for a long time so that it has been inherited as a method for research. The type of research that is used in this research is descriptive statistical research. As stated by Sugiyono (2017: 35), descriptive statistical research is a problem statement regarding the question of independent variables, whether only on one or more variables (independent variables). The nature of this research is a causal relationship. According to Sugiyono (2017: 37), causal relationships are causal relationships. So in this study can be found independent variables (variables that affect) and dependent (influenced).
According to Sugiyono (2017: 80), population can be described as one generality zone coinciding of subjects / objects that fulfil several qualities and characteristics specified by researchers to be analized and later conclusions given. The population taken in the study were 47 mining sub-sector companies listed on the Indonesia Stock Exchange in 2013-2017. According to Sugiyono (2017: 81), the sample described as section of the number of characteristics owned by the population. Sampling is done by purposive sampling. As stated by Sugiyono (2017: 85), purposive sampling can be described as one sampling technique that requires some considerations. Some of the criteria specified are: According to Sugiyono (2017: 137), data collection techniques are steps required in collecting data needed in a study. Collecting data technique that used in the research is documentation studies conducted through data collection from journals, books and media internet intermediaries through the website website www.idx.co.id and and through the each company's official website.
Data sourcing type that used in this research are secondary data. Sugiyono (2017: 137) states that, secondary data can be described as one source that does not immediately supply data to data collectors.
In this study several test methods were conducted, namely the classic assumption test in which there were several other tests such as normality test, multicollinearity test, autocorrelation test, heterokedasticity test, F test and t test conducted using SPSS 25 application. The research model used was to use multiple linear regression analysis.

RESULTS AND DISCUSSION
The Descriptive Statistics Table above shows the data used in this study were 130, which was obtained from a total sample of 26 companies multiplied by the study period of 5 years. The table gives the value of the minimum value, maximum value, average value (mean), and standard deviation of the variable Liquidity (X1), Leverage (X2), Profitability (X3), Company Size (X4) and Stock Price (Y) with details as follows. The aim of the normality test is to tell wether in the regression model, confounding or residual variables there is a normal distribution. When this normality test is conflicted then the statistical test becoming invalid for the smaller number of samples. Histogram Normality Test Results and P-P Plots will be shown in the figure below:

Figure 2. Histogram for Normality Test Before Transformation
The histogram graph in Figure 1 above shows the curve lines do not form bells upside down so it can be said that the data isn't normally distributed, therefore it is necessary to transform the data.

Figure 3. Histogram for Normality Test After Transformation
The histogram graph in Figure 2 above shows the tendency of the symmetry curve (U), so it can be told that the data is normally distributed. In addition to the histogram test, the normality test in this study uses the normal P-P plot graph as seen in the following figure:

Figure 4. P-P Plot Normality Test Before Transformation
P-P Normality Graph The plot in Figure 3 above, seen the points far away from the diagonal line, it can be described that the data is not normally distributed. Normality Test results above indicate the data are not normally distributed, it is important to transform data.

Figure 5. P-P Plot Normality Test After Transformation
In the P-P Normality chart the plot after the transformation above shows the points go close to the diagonal line, and keep up the way of the diagonal line so that the data is normally distributed.
In addition to using the Histogram Normality Test and the P-P Plot Normality, this research also uses the Kolmogorov-Smirnov analysis to ascertain if the regret model has actually been normally distributed with the conditions stated below: • If the significant shows a value > 0.05 then it is normally distributed. • If the value of the significant < 0.05, then the distribution is not normal.  ,084 a. Test distribution is Normal. b. Calculated from data.
The normality test results over indicate that the multiple regression model that was made was normally distributed. This can be shown from the significant level of the outcomes of the test which the value is 0.084 or 0.84%, where the value is greater than 5% (0.084> 0.05). Data in general are normally distributed. After the data is transformed, the amount of data that was originally 130 samples is reduced to 88 samples. The reduction in the data is due to the large amount of profitability that has a negative value.
To test if the regression model found any correlation between independent variables, multicollinearity test is required. To discover the present or absent of multicollinearity in the regression model can be told from the mark of tolerance and variance inflation factor. The method of decision making is tolerance value > 0.1 and VIF < 10 then multicollinearity free regression.  Autocorrelation test is a test used to see if in a linear regression model there is any correlation between the error of the intruder in period 1 and the error of the intruder in the period t-1 (the previous period). One measure in determining the present or absent of autocorrelation problems with the Durbin -Watson test (DW -test) The Heteroscedasticity test is useful for testing if we can find dissimilar variance from the residuals of one observation to another in the regression model. How to make decisions is to look at the Scatterplot graph as follows.

Figure 6. Scatter Plot Heteroscedasticity Test Before Transformation
The results of the study in Figure 5 from the scatterplot graph on top shows that the deployment of residuals is irregular and forms patterns. From this causes, it is necessary to transform data.

Figure 7. Scatter Plot of Heterokedasticity Test After Transformation
By looking at the scatterplot graph, it can be deduced that there was no heterocedasticity in the regression model, because the points were seen to spread randomly, and that they were scattered above or number 0 on Y.
The research model that has been used in the research is research model with multiple linear regression analysis methods.  units and a positive value states that each increase of 1 unit profitability variable will cause an increase in Share Price of 0.308 with the assumption that other variables are constant. 5. Regression coefficient of the company size of -2,547 units and a negative value states that every increase of 1 unit of the size of the company size will cause a decline in stock price of -2,547 with other variables constant.
The coefficient of determination (R2) is a number that indicates the degree or ability of the independent variable (X) in explaining the dependent variable (Y). The greater the coefficient of determination, the greater the independent variable influences the dependent variable. From the above data it can be explained the discussion regarding the results of the analysis that has been carried out are as follows:

Effect of Liquidity on Stock Prices
From the research results obtained tcount> t table or 3.281> 1.979 with significance 0.002 thus H1 which states that Liquidity has a positive and significant effect on stock prices. These results indicate that good liquidity can lead to high stock prices.
The results of this study are in line with research by Ummu Putriana Hanie, and Muhammad Saifi (2018) which states that the smaller the risk of liquidation experienced by the company reflects that the company is able to pay off its obligations.
Thus, if the company's liquidity is good, investors will not doubt whether the capital they invested in the company will return and provide benefits for them or not. Because if a company's liquidity is not good, it has the tendency to be shunned by investors. The results of this study are in line with research conducted by Santi Oktaviani and Dahlia Komalasarai (2017) which in their research showed that liquidity had no significant effect on stock prices.

Effect of Leverage on Stock Prices
From the research results obtained tcount> t table or -0.476> 1.979 with a significance of 0.635 thus H2 which states that leverage has a negative and not significant effect on stock prices. This research is supported by Sari Ariyanti, et al (2016) who state that leverage has a negative and not significant effect on stock prices. High leverage indicates a company's ability to carry out more operational activities derived from debt. Basically, investors will choose companies that have low leverage in investing to avoid risk.

Effect of Profitability on Stock Prices
From the research results obtained t count> t table or 3.580> 1.979 with a significance of 0.001, thus H3 which states that profitability has a positive and significant effect on stock prices. These results indicate that profitability is able to generate profits from assets used by the company.
The results of this study are in line with research by Santi Oktaviani, and Dahlia Komalasarai (2017) which states that profitability has a significant effect on stock prices. Thus, the higher the profitability of a company, the higher the value of the company's assets and can achieve a good profit or profit in each period. So that investors do not need to worry that the company will experience a loss or bankruptcy, but it opens up the possibility of new investors who want to invest their capital there and can increase the company's stock price.

Effect of Company Size on Share Prices
From the research results obtained tcount> ttable or -3.610> 1.979 with a significant value of 0.001 thus H4 which states that company size has a negative and significant effect on stock prices.
The results of this study are in line with research by Muhammad Sukarno, Riana Sitawati, and Sam'ani (2016) which states that company size has a significant effect on stock prices.
Thus, if the size of a large company, the company's share price will also be high, and vice versa if the size of a small company, the share price will also be low. This is because the greater the size of the company is an attraction for investors to invest because the size of the company has a positive effect on investors so that it will make demand for these shares go up. .

CONCLUSIONS AND SUGGESTION
The aim of this research was to specify the effect of Liquidity, Leverage, Profitability and Company Size on Stock Prices. Based on the results of research established, it can be concluded that partially, Liquidity and Profitability has a positive and significant effect on Stock Prices. Leverage has a negative and not significant effect on stock prices. While the size of the company has a negative and significant