The Effect of Current Ratio (CR), Firm Size (FS), Return on Equity (ROE), and Earning Per Share (EPS) on the Stock Prices of Manufacturing Companies listed in Indonesia Stock Exchange in the 2014-2018 Period

Competition in the industrial world in the current era of globalization is increasing rapidly. The number of competitive industrial companies of a country are competing to get raw materials or natural resources into finished materials. One of them is manufacturing company. Wherein manufacturing companies compete for the international market and form the competitive advantage of their products which aim to attract consumers to make purchases and attract investors to invest in these companies such as buying company shares. Investors make an investment to earn a profit per share or Earning Per Share through a closing price. Closing price is the closing stock price when the market is closed. Therefore, investors also see companies that have an increase in total equity. Each increase must always be followed by an increase in the total assets of the company and companies Abstract


I. Introduction
Competition in the industrial world in the current era of globalization is increasing rapidly. The number of competitive industrial companies of a country are competing to get raw materials or natural resources into finished materials. One of them is manufacturing company. Wherein manufacturing companies compete for the international market and form the competitive advantage of their products which aim to attract consumers to make purchases and attract investors to invest in these companies such as buying company shares.
Investors make an investment to earn a profit per share or Earning Per Share through a closing price. Closing price is the closing stock price when the market is closed. Therefore, investors also see companies that have an increase in total equity. Each increase must always be followed by an increase in the total assets of the company and companies Keywords current ratio; firm size; return on equity; earning per share; stock prices; manufacturing companies that have total current assets which always increase every year can have an effect on the increase in the company's stock price. So the stakeholders assess a company before buying shares of a company by calculating the size of the company. The table above shows that the total current assets of the company PT. Tempo Scan Pacifik Tbk has increased, but share prices have decreased. Where the increase in total current assets is not always followed by an increase in share prices or otherwise.
The total Asset of PT. Indocement Tunggal Prakasa Tbk Company has increased but the share price has decreased. Where an increase in total assets is not always followed by an increase in share prices or otherwise.
Total equity of PT. Indocement Tunggal Prakasa Company has increased but the share price has decreased. Where an increase in Total Equity is not always followed by an increase in Shares or otherwise.
Based on the above phenomena, it can be seen that the movement of stock prices in manufacturing companies has changed which is not always followed by total current assets, total assets, sales and net income. So in that case, to conduct further research, the researcher set the title for this research: "The Effect of Current Ratio (CR), Firm Size (FS), Return On Equity (ROE), and Earning Per Share (EPS) on the Stock Prices of Manufacturing Companies listed in Indonesia Stock Exchange in the 2014-2018 period".

The Effect of CR on Stock Prices Theory
Accoding to Kasmir (2013:134) Current Ratio is ability of a company to pay off shortterm liabilities by using short-term assets that are owned at maturity. Research conducted by Firtianingsih, Dwi and Yogi Budiansyah (2018) has a significant effect on stock prices. This research has the support of previous research, where the results of Indra Setiyawan (2014), Ragila Amanah (2014) and Reynad Valentino (2013) found that the Current Ratio has a positive and significant effect on stock prices.

The Effect of FS on Stock Prices Theory
Firm Size is the average of the total annual assets concerned for the next upcoming years (Brigham and Houston, 2011:119). Research conducted by Suryana and Helma (2016) has a positive and significant effect on stock prices, where high total assets will indicate a good company image. This research has the support of previous research, where the results of Achmad Syaiful Susanto (2012) and Ruttanti Indah Mentari (2015) found that the Firm Size affects stock prices.

The Effect of ROE on Stock Prices Theory
According to Kasmir (2015: 204), Return on Equity is a ratio used to measure the return on equity or its own capital profitability. The higher the ratio the better it is. In a study conducted by Cathelia, et al. (2016), it has a positive and significant impact on stock prices. This study has the support from previous researchers, where the results of Putra et al. (2013) and Ratih et al. (2013) found that Return On Equity has an influence on stock prices.

The Effect of EPS on Stock Prices Theory
According to Gitman and Zutter (2014) Profit per share is the profit received on each common share outstanding in a period which is calculated by distributing total profit for the year. Research conducted by Ayu, Gusti Mahanavami (2014) has a positive and significant effect on stock prices. This study has the support from previous researchers, where Novi Indriani (2009) found that Earning Per Share has an effect on stock prices.

Previous Researches
Partially, ROE (X1) has positive and significant impact on stock prices; DER (X2) has negative and significant impact on stock prices; TATO (X3) has negative and insignificant impact on stock prices; CAPEX (X4) and NCCR (X5) has positive and insignificant impact; and ROE, DER, TATO, CAPEX, and NCCR simultaneously has a significant effect on stock prices. Where ROE has dominant effect on stock. (Nadia Cathelia & R. Djoko Sampurno, 2016).
Partially the company growth (X1) and TATO (X2) have no and insignificant effect on stock prices; ROI (X3) has a positive and insignificant effect on stock prices; EPS (X4) has a positive and significant effect on stock prices; and Company Growth, TATO, ROI, and EPS have a significant effect on stock prices. Where EPS has a dominant effect on stock prices. (Firmansyah & Masril, 2017).
Partially CR (X1) and DER (X2) have a positive and significant effect on stock prices. CR and DER simultaneously have a significant influence on stock prices. Where CR has a dominant effect on stock prices. (Dwi Fitrianingsih & Yogi Budiansyah, 2018).
Partially firm size (X1) has a positive and significant effect on stock prices; Profitability (X2) has no and insignificant effect on share prices; and firm size and profitability simultaneously have an effect on stock prices. (Ni Wayan Ade Rosita, et al, 2018).

Conceptual Framework
Based on the literature reviews above, the conceptual framework can be illustrated as below:

Hypothesis
Based on the conseptual framework presented in figure I, the hypothesis can be formulated as follows: H1: Current Ratio partially affects stock prices in manufacturing companies listed on the IDX. H2: Firm Size partially affects stock prices in manufacturing companies listed on the IDX. H3: Return On Equity partially affects stock prices in manufacturing companies listed on the IDX. H4: Earning Per Share partially affects stock prices in manufacturing companies listed on the IDX. H5: Current Ratio, Firm Size, Return On Equity, and Earning Per Share simultaneously affects the stock prices of manufacturing companies listed on the IDX.

Time and Place of Research
This research had been conducted since December 2018 and the place of research was carried out on the official website of the Indonesia Stock Exchange at a manufacturing company and with the website address being www.idnfinancials.com.

Research Approach
This research uses a quantitative approach or the data is measured numerically. A quantitative approach is a type of research where the findings are not based on statistical procedures or quantification methods such as those in quantitative research (Azuar & Irfan 2013 : 12).

Type of Research
This research uses descriptive statistical research. Descriptive statistics are a type of research that is used to describe the data obtained without making general meaning or generality. (Sugiyono, 2016:147).

Population and Sample
Population is the entire data to be studied in the specified scope and time, (Kasmadi and Nia, 2018: 65). The population of this research is manufacturing companies listed on the Indonesia Stock Exchange (BEI) and the financial reports used are sourced from www.idx.co.id. The population in this study amounted to 150 manufacturing companies.
Sample is the result from a population selection that is adjusted to predetermined characteristics. According to Sugiyono (2016: 81) this research uses purposive sampling technique. This technique is a technique of samples selection from a population based on certain considerations (expert and scientific) with sufficiently strict requirements to match the desired characteristics.
The sampling criteria used in this study are:  In the sampling criteria, 49 Manufacturing Companies with a period of 5 years are listed on the Indonesia Stock Exchange as the research sample.

Data Collection Method
Data collection methods are a strategic stage in research, because research is to obtain data (Sugiyono, 2016: 224). In this study, the documentation method was used in data collection. The data used are journals from previous research and financial reports of manufacturing companies listed on the IDX.

Types and Sources of Data
The type of data used in this research is quantitative data and the data source used in this study is secondary data. Secondary data is a data that is received indirectly. This data source is obtained from the financial statements of manufacturing companies listed on the IDX.

Identification and Definition of Operational Variables
The operational definitions of each variable are as follows:

Research Data Analysis Test
The data analysis method aims to facilitate data processing into a form that is easier to understand. Regression analysis is used to measure the strength of the relationship between one or more variables by showing the direction of the relationship between the independent variable and the dependent variable. (Ghozali, 2016: 94

Coefficient of Determination (R2)
According to Ghozali (2016: 95) the coefficient of determination is carried out with the aim of measuring how much the model's ability can explain variations in the dependent variable. The ability of the independent variable (X) is strong against the dependent variable (Y) if the coefficient of determination (R) is getting closer to 1 and otherwise that the ability of the independent variable (X) is weak against the dependent variable (Y) if the coefficient of determination (R) is getting closer to 0.

Simultaneous Hypothesis Testing (F Test)
The F statistical test will show that all the independent variables included in the model together have an influence on the dependent variable, (Ghozali, 2016:96). The F test tests the hypothesized relationship that b1, b2, b3, and b4 are equal to zero or: H0: b1 = b2=….. = bk = 0 or HA: b1 ≠ b2 ≠….. ≠ bk ≠ 0

Partial Hypothesis Testing (t Test)
The t statistical test will show how much influence each independent variable has on the dependent variable (Ghozali,2016:99). The null hypotesis (H0) to be tested is a parameter (bi) equal to zero, or (H0 : bi = 0) and alternative hypothesis (HA) is a parameter of a variable is not equal to zero, or (HA : bi ≠ 0).

Result a. Descriptive Statistics
Descriptive statistical analysis describes the essence of a data by showing the average value (mean), maximum value, minimum value, and standard deviation of a data. This study uses SPSS 19 and Microsoft Office Excel 2016 in data processing. The results of descriptive statistical data processing in this study are as follows.

Stock Prices
From the table 4 above, it can be concluded that the number of samples (N) in manufacturing companies is 245, the average value of the stock price is Rp. 7465.44, the maximum value of the stock price is Rp.390000, and the minimum value of the share price is Rp. 50 and for the standard deviation of the Share Price of Rp. 28213.42.

Current Ratio (CR)
From the table 4 above, it can be concluded that the number of samples (N) in manufacturing companies is 245, the CR average value is 2.5552, the CR maximum value is 12.995, and the CR minimum value is 0.450 and the CR standard deviation is 1.8593..

Firm Size (FS)
From the table 4 above, it can be concluded that the number of samples (N) in Manufacturing companies is 245, the average FS value is 28.8144, the maximum FS value is 32.503, and the minimum FS value is 25.719 and the FS standard deviation is 1.6208.Pada tabel 4 diatas dapat disimpulkan memiliki jumlah sampel (N) pada perusahaan

Return On Equity (ROE)
From the table 4 above, it can be concluded that the number of samples (N) in Manufacturing companies is 245, an average ROE value of 0.1587, a maximum ROE value of 1.435, and a minimum ROE value of 0.001 and a standard deviation of ROE of 0.2345.

Earning Per Share (EPS)
From the

b. Classic Assumption Test
The classical assumption test is used to show and test whether the regression model in the study is feasible or not. In this study, multiple linear regression analysis model is used. The requirements for using multiple linear regression equations by passing the classical assumption test.

Figure 2. Histogram Normality Test
Based on Figure 2 the histogram graph above shows a symmetrical (U) curved line, therefore it can be interpreted that the data in this study is normally distributed because the histogram graph distribution pattern is not tilted to the left or right.

Figure 3. P-P Plot of Normality Test
In Figure 3 the P-P plot normality graph shows the points that are spread out close to the diagonal line, this shows that the research data is normally distributed. In addition, to find out the normally distributed data in this study using the Kolmogorov Smirnov nonparametric statistical test.  Table 5 shows the results of the Kolmogorov Smirnov non-parametric statistical test which can be explained that the variables CR, FS, ROE, EPS, and stock prices have met the requirements with normally distributed data because the significant value of 0.839 is greater than 0.05 (0.839 > 0.05).

Multicollinearity Test
Multicollinearity test is used to show a condition whether there is a linear relationship or high correlation between each independent variable in the regression model of this study. To determine whether multicollinearity occurs or multicollinearity does not occur, the criteria are: 1. VIF is smaller than 10 and tolerance is greater than 0.10 (multicollinearity does not occur) 2. VIF is greater than 10 and tolerance is smaller than 0.10 (multicollinearity occurs) The multicoliearity test results can be seen in the following table: .839 a. Test distribution is Normal. b. Calculated from data. 0.10. Thus, it can be concluded that the results of the study are free from correlation or the study passes the multicollinearity test.

Heteroscedasticity Test
Heteroscedasticity test is used to test whether or not in a regression model of this study, there is an inequality of variance from residuals and from one observation to another. In this study the chart method is used, namely: If the dots form a certain regular pattern such as wavy and widened then narrowing, it can be said that Heteroscedasticity has occurred and if there are no points spreading or in the form of a pattern above and below the zero on the Y axis it can be said that heteroscedasticity does not occur. Figure 4 shows that the Scatterplot image has randomly scattered and shapeless points. So that, it can be concluded that there is no heteroscedasticity in the regression model of this study.

Autocorrelation Test
The 3 provisions in autocorrelation testing are as follows: 1. If d is less than dL or greater than (4-dL) then autocorrelation occurs. 2. If d is greater than dU and less than (4-dU), then there is no autocorrelation. 3. If d lies between dL and dU it cannot be concluded.  In table 7 above, it can be concluded that the Durbin-Watson value is 1.882 and the dU value is 1.8094 which is obtained from n; k4 (dU) and Durbin-Watson located between dU and (4-dU). Then the dW value is 1.882 and the dU value is 1.8094 which can be interpreted as the dW valuegreater than the dU value and the value less than (4-dU), namely dU (1.8094) < dW (1.882) < 4-dU (2.1906) it can be concluded that the data in the study did not occur autocorrelation. Y= a +b 1 X 1 + b 2 X 2 +b 3 X 3 +b 4 X 4 +e Y= -15,145 + (-0,124) X 1 + 5,441 X 2 + (-0,089) X 3 + 0,877 X 4 + e

Multiple Linear Regression Analysis Test
The above equation is stated as follows: 1. The constant value is -15,145, which means that if CR (X1), FS (X2), ROE (X3), and EPS (X4) have a value of 0, it means that the Stock Price (Y) is IDR -15,145. 2. The regression coefficient on the CR variable (X1) has a regression coefficient of -0.124, which means that other independent variables are fixed and there is an addition of 1 value on CR will make the stock price (Y) decrease by IDR 0,124 as the assumption that other independent variables are constant. 3. The regression coefficient on the FS variable (X2) has a regression coefficient of 5.441, meaning that other independent variables are of fixed value and an addition of 1 value on FS will make the stock price (Y) increase by IDR 5,441 as the assumption that other independent variables are constant. 4. The regression coefficient on the ROE variable (X3) has a regression coefficient of -0.089, which means that other independent variables are fixed and there is an addition of 1 value or ROE will make the stock price (Y) decrease by IDR 0,089 as the assumption that other independent variables are constant. 5. The regression coefficient on the EPS variable (X4) has a regression coefficient of 0.877, which means that other independent variables are of fixed value and there is an addition of 1 value or EPS will make the stock price (Y) increase by IDR 0.877 as the assumption that other independent variables are constant. Based on significant value (Sig.) and the comparison of t count with t table in the formula (α/4; n-k-1) is as follows: 1.

Discussion a. The Effect of CR on Stock Prices
In partial testing, the results of statistical testing show 0.140> 0.05, besides that, it can also be seen from the t count of -1.482 greater than the t table, which is -2.345. It can be seen that it does not accept H1 which states that the independent variable partially affects the dependent variable. This study shows that increasing the current ratio will not increase stock prices. The results of this study are inconsistent with previous research conducted by Dwi Fitrianingsih & Yogi B. (2018) for the CR variable which has a significant effect on stock prices. However, the results of this study are consistent with Rondonuwu E. Faleria, et al. (2017) proving that the CR variable has no effect on stock prices..

b. The Effect of FS on the Stock Price
In partial testing, the results of statistical testing show 0.000 <0.05, besides that, it can also be seen from the t count of 5.199 smaller than the t table, namely 2.345. It can be seen that accepting H2 which states that the independent variable partially affects the dependent variable. The results of this study indicate that an increase in the company's total assets will have an effect on increasing share prices. The results of this study are consistent with previous research conducted by Ni Wayan Ade Rosita, et al (2018), Ashari Dwi Putranto & Ari Darmawan (2018), and Suryana & Helma Aditia (2016), proving that the FS variable has a positive and significant effect on stock prices.

c. The Effect of ROE on Stock Prices
In partial testing, the statistical test results show 0.075 <0.05, besides that, it can also be seen from the t count of -1.787 is greater than the t table, which is -2.345. It can be seen that H3 rejects which states that the independent variable partially affects the dependent variable. The results of this study indicate that each increase in ROE has no effect on the increase in stock prices. This study is not consistent with previous research conducted by Nadia C. & R. Dojoko S. (2016) for the ROE variable which has a positive and significant effect on stock prices. However, the results of this study are consistent with Bayu Wulandari, et al (2020) for the ROE variable has no effect on stock prices..

d. The Effect of EPS on Stock Prices
In partial testing, the statistical test results show 0.000 <0.05, besides that, it can also be seen from the t count of 20.650 which is greater than the t table which is 2.345. It can be seen that accepting H4 which states that the independent variable partially affects the dependent variable. The results of this study indicate an increase in earnings per share has an effect on increasing stock prices and vice versa. This research is consistent with previous research conducted by Mikha Q.H.M. Mantik, et al (2019), Firmansyah & Masril (2017), and Gusti A.M. (2014) for the EPS variable has a positive and significant effect on stock prices.

V. Conclusion
The conclusions obtained from the results of this study are: 1. FS (X2) and EPS (X4) partially have a positive and significant effect on the stock prices of manufacturing companies listed on the IDX, so it can be interpreted that the second hypothesis (H2) and the fourth hypothesis (H4) in this study are accepted. CR (X1) and ROE (X3) partially have no and insignificant effect on the stock prices of manufacturing companies listed on the IDX, so it can be concluded that the first hypothesis (H1) and the third hypothesis (H3) in this study are rejected. 2. CR (X1), FS (X2), ROE (X3), and EPS (X4) simultaneously have a significant effect on the stock price (Y) of manufacturing companies listed on the IDX, so it can be concluded that the fifth hypothesis (H5) in this study is accepted. 3. The multiple regression equation to analyze the effect of CR, FS, ROE, and EPS on the stock price of manufacturing companies listed on the IDX is: Y= -15,145 + (-0,124) X1 + 5,441 X2 + (-0,089) X3 + 0,877 X4 + e. 4. In the calculation of the coefficient of determination (R2), the value is 0.796. This shows that the variables CR, FS, ROE, and EPS can describe stock prices as the dependent variable of 79.6%.