The Influences of Return on Asset, Return on Equity, Net Profit Margin, Debt Equity Ratio and Current Ratio Toward Stock Price

This research aims to determine the influences of Return on Asset, Return on Equity, Net Profit Margin, Debt Equity Ratio and Current Ratio toward stock price. The population in this research are all manufacturing companies listed in Indonesia Stock Exchange (IDX). The technique of determining the sample using purposive sampling method and sample acquired three companies from 35 companies from 2016 to 2018. This research contains six variables which are one dependent variable and five independent variables.


1.INTRODUCTION
The Indonesia Stock Exchange (IDX) increases the number and value of shares traded. The process is managed and supported by the government, which investors launch and invest in Indonesia. The role of government is significant in attracting investors to invest domestically as well as abroad in Indonesia. Investment is usually made to commit to various funds or other tools to obtain several future benefits. An individual usually purchases several shares in the hope of taking advantage of rising prices or potential dividends. An investor purchases several shares now to make a profit over time and risk from increasing share prices or a variety of dividends in the future.
Indonesia's stock market is expected and fast-growing. The growth of the capital market will make it possible for more companies to be publicly available and listed on the stock market to raise money through public ownership rather than by banks. Industries may obtain their required financial benefits by selling their ownership to the public, without paying fixed interest to banks that loan money. Stocks market as a mechanism and an ideal place for people interested in investing without spending much money.
Indonesia's stock exchange's presence is promoting rising industrial growth. This matter, shown by the Indonesia Stock Exchange (IDX), makes it easier to acquire additional money to develop the business. However, additional funds from the Indonesia Stock Exchange (IDX) is not easy for businesses. The amount of funding the company receives is determined by the number of funds spent by creditors.
Investors socialize the stock price by expecting revenue, cash flow, and the degree of profit. Macroeconomic conditions and global economic conditions also influence stock prices. The price of a share reflects a company's value that will affect company shareholders who generate good value. Stock price adjustments and improvements are decided by stock (secondary) demand to value the share that constitutes the assets. The higher the stock price the more investors that want to purchase shares. Conversely, the lower the stock value, more buyers want to sell or transfer their shares. The financial statements are released by management to demonstrate the situation of the company. The company shall issue financial statements for a particular time. Financial statements are critical for investors to return investments, like sales, acquisitions and equity. In achieving the goals, management needs the ability to choose the practical action that will reflect the result of the financial statement, since the better financial output is a prerequisite for businesses to attract investment.
The financial reports are using for measurement to assess if the company performance. Good management and operating quality businesses can generate higher net income and stock prices. Accounting and finance analysis is primarily concerned with the data on financial reports and their impact on stock market behaviour. Several investigators have been drawn to investigate how financial information is affected by security prices and influences investment decisions.

II. METHODS
Regarding the existing literature and hypothesis development above, the researcher constructed the following graph Figure 1, to figure out the relation between return on Asset, Return on Equity, net profit margin, debt-equity ratio, and current ratio as an independent variable, and stock price as the dependent variable.  Hypothesis testing in this analysis uses a regression model consisting of more than one independent variable, represented as multiple regression. The data processing in this research is assisted with computer program SPSS 25.
Descriptive Statistical Analysis Descriptive statistics provide a summary or explanation of the data shown by mean, standard deviation, median, mode, peak, minimum, total, distance, kurtosis and skewness (Ghozali, 2011

Multicollinearity Test
The multicollinearity test is used to check a correlation between independent variables (independent) or not by the regression model. A good regression model there is no correlation between independent variables. Multicollinearity can be seen by Variance inflation factor (VIF) if the VIF value <10 and tolerance value >0.10, then there is no multicollinearity (Ghozali, 2011).

Autocorrelation
The autocorrelation test tests a correlation between the error in the period t with the error in the period t-1. To test autocorrelation can use the Durbin Watson test (DW test), where the test results are determined based on the Durbin-Watson (DW) value. The basis for decision making is the existence of autocorrelation using Durbin Watson. A good correlation model is one that does not contain autocorrelation. The hypothesis to be tested: H0: There is no auto correlation (r = 0) Ha: There is an autocorrelation (r ≠ 0) Decision making for autocorrelation through Durbin Watson table criteria with a significance level of 5% is as follows: 0<d <dL = There is an autocorrelation -dL <d <4 = There is an autocorrelation du <d <4 -du = There is no autocorrelation Heteroscedasticity This test is used to determine the confounding variables in the regression equation having the same variance, meaning there is no heteroscedasticity, whereas if there are unequal variances, there is heteroscedasticity (Susanto, 2015). In this study, the heteroscedasticity test used the geyser test.

Hypothesis Test
The two methods used in the hypotheses test are T-test and R-square (Determination Coefficients).
T-tests shall find the significance of the independent variable's influence individually to the dependent variable provided that the other independent variables are constant. T-test uses hypothesis: H0: βi = 0 H1: βi ≠ 0 The determination coefficient is a method for statistical analysis of the observations that measures how well a model has represented and predicted the future. The predictions show the level of variation in the data set-the coefficient of ISSN:2722-4015 http://ijstm.inarah.co.id determination line between 0 and 1 (0 ≤ R2 ≤ 1). R2 is better if the value is closer to 1 in the regression line rather than close to zero.

Descriptive Statistic
Descriptive statistics help to explain the variable in general and to simplify the data to be more understandable. It nevertheless does not allow to infer any hypothesis that we have made. The variables in this research are listed in the following table DescriptiveStatisticsTables The

Classical Assumption Test Normality Test
Test for Normality means ensuring the normal distribution of data used in the investigation. A good model of regression will typically be distributed. Kolmogorov Smirnov Method and Normal Probability Plot will be used in this research in normality testing. The Kolmogorov-Smirnov test results are usually indicated when the significance level is >0.05 (above 0.05). The result of the normality test by using the standard probability plot is shown in Figure 2.

Formal Probability Test
The graph shows that the data distribution fits the diagonal line that usually distributes the data used in this analysis. However, the expected probability plot results need to be supported by statistical tests such as Kolmogorov Smirnov. The result of the normality test by using Kolmogorov Smirnov is shown in Table .

One sample Kolmogorov-Smirnov Test
The table shows that data are typically distributed as a result of non-parametric Kolmogorov Smirnov.

Multicollinearity Test
Multicollinearity should be free of a regression model. This test is done to assess if one independent variable is associated with another. The tolerance or variance inflation factor of multicollinearity can be tested. If the tolerance's VIF value is less than 0.10 or more than 10, the variable has multicollinearity. Then the result of tolerance a VIF is shown in the following:

TableCoefficient Correlation of Multicollinearity Test
The and VIF less than 10, which means the data used for the research is free from multicollinearity.
Heteroscedasticity Test Heteroscedasticity tests are conducted to assess if there is some discrepancy between residuals in one study time and another in a regression model. We may determine heteroscedasticity from the scatterplot graph by observing its pattern. It means that work has a heteroscedasticity problem when a specific pattern is formed.
The heteroscedasticity test results are described below.

Figure3. Scatterplot Graph of Heteroscedasticity Test
From the graph results shows us that the dots are not forming any particular pattern. Therefore, it can be concluded that this research has no heteroscedasticity problem.

Autocorrelation Test
The autocorrelation test is used to know the correlation at different times between process values. SPSS is used to test for the autocorrelation by this research using the Durbin Watson method. Durbin Watson's criterion concludes that the residual is not associated with other studies, which means that it has to be higher dU and less than 4dU for the Durbin Watson value. dU value from the Durbin Watson table is calculated. obtained from the test will fulfil the of 0 < d < dL, which is 0 < 1.681 > 1.1601. It means that there is a positive correlation.

Hypothesis Testing Coefficient Determination (R2)
In this analysis, the coefficient determination is used to calculate the independent variables' effect on the dependent variable. The results of this research are as follows coefficient, multiple regression model: The result shown by the table that the Return on Asset significance value is 0.925. It means that has no significant effects, since the significant value is 0.462 after divided by two and it is still higher than 0.05.
Return on Equity has a significant value of 0. It means that towards stock price Return on Equity has significant effects since the significant value is small than 0.05.
Net Profit Margin has a significant value of 0.137, as shown in the table. It means that Net Profit Margin has no significant effect since the significant value will be 0.0685 after divided by two still bigger than 0.05.
Debt Equity Ratio has a significant value of 0. It means that the Debt Equity Ratio has significant effects since the significant value is less than 0.05.
The result of T-Test, table 4.8, shows that Current Ratio has a significant value of 0.077. The Current Ratio significantly affects since the significant value will be 0.038 after divided by two, which is lower than 0.05.

IV. CONCLUSION
From the T-test result, Net Profit Margin has insignificant influences toward stock price since the significant value is 0,137. Which is half the significant value from the table, and it is still higher than 0.05. The coefficient of Net Profit Margin -10.342,173, as shown in table T-test. This research indicates that towards stock price, Net Profit Margin has a negative influence. Therefore, H0 is accepted.
From the T-test result, Debt Equity Ratio is having significant influences toward stock price since the significant value is 0. The coefficient of DER 5.884,357, as shown in table T-test. This research indicates that towards Debt Equity Ratio has positive and significant influence. Therefore, H0 is accepted.
From the T-test result, the Current Ratio has significant influences on stock price since the significant value is 0,038 after divided by two.