The Effect of Liquidity, Leverage and Profitability, on Dividend Policy in IDX High Dividend 20 Index Companies Listed on the Indonesia Stock Exchange

This study aims to determine the effect of liquidity, leverage and profitability, on dividend policy in IDX High Dividend 20 index companies listed on the Indonesia Stock Exchange. The location of this research is on the Indonesia Stock Exchange (IDX) by accessing the official IDX website, www.idx.co.id. The population in this study were 20 IDX High Dividend 20 index companies listed on the Indonesia Stock Exchange in 2015-2017. The sample analysis technique used is purposive sampling technique, namely 20 companies with a total of 60 observations. The data analysis technique used is multiple linear regression analysis, multiple correlation analysis, determination analysis and ujit. The test results show that liquidity has a positive and significant effect on dividend policy in IDX High Dividend 20 index companies; leverage has a negative and significant effect on dividend policy in IDX High Dividend 20 index companies; profitability has a positive and significant effect on dividend policy in IDX High Dividend 20 index cmpanies.

shows that the independent variables that can affect dividend policy can be identified as follows, liquidity (X1), leverage (X2), and profitability (X3). While the dividend payout ratio (DPR) as the dependent variable (Y) which is the percentage of dividends as the expected goal of shareholders. Liquidity shows the company's ability to meet short-term financial obligations on time (Sartono, 2010: 114). Liquidity ratio is a ratio that describes the company's ability to meet short-term obligations (debt), meaning that if the company is billed, it will be able to fulfill the debt (pay), especially maturing debt (Kasmir, 2013: 110). The company's liquidity level can be measured by several ratios, namely current ratio, acid test ratio, cash ratio, net working capital to sales and current assets to sales (Wiagustini, 2010: 78). In this study, liquidity is proxied by current ratio (CR) because CR is one of the most commonly used liquidity ratios (Horne and Wachowicz, 2005: 206).Leverage shows the company's capacity to fulfill both short-term and long-term obligations (Sartono, 2010: 114). The level of company leverage can be measured by several ratios, namely debt to total assets, debt to equity ratio, times interest earned and fixed charged coverage (Wiagustini, 2010: 114). In this study, leverage is proxied by DER (debt to equity ratio) because DER is the right ratio used to show the company's ability to pay all its long-term and short-term obligations. DER reflects the company's ability to meet all its obligations as indicated by some part of its own capital used to pay debts. The greater this ratio indicates the greater the obligation and the lower the ratio will indicate the higher the company's ability to fulfill its obligations (Sumantri and Candranignrat, 2014). Profitability is the company's ability to earn profits in relation to sales, total assets and own capital (Sartono, 2010: 122). According to Hanafi (2010: 42), the profitability ratio measures the company's ability to generate profits at a certain level of sales, assets, and share capital. There are three ratios that are often used, namely profit margin, return on assets (ROA), and return on equity (ROE). In this study, profitability is proxied by return on equity (ROE). According to Sartono (2012: 124), the definition of ROE is a ratio to measure the company's ability to earn profits available to shareholders. Several previous researchers have conducted research on dividend policy. However, the results of the research conducted by these researchers are still not consistent between one researcher and several other researchers. Each of them has differences from the results of their research. The liquidity variable is stated to have a positive and significant effect on dividend policy (dividend payout ratio) in research conducted by Wicaksana (2012) and Andriyani (2008), but this contradicts the results of research conducted by Novatiani and Oktaviani (2012)

Literature Review: Dividend
Dividends are the distribution of company profits to shareholders in proportion to the number of shares owned (Baridwan, 2008). Dividends are cash flows paid to shareholders (Van Horne, 2009). So it can be concluded that dividends are profits distributed to shareholders for the profits distributed to the shares for the profits earned by the company. Usually dividends are distributed at fixed intervals, but sometimes additional dividends are distributed at unusual times. Several definitions of dividend policy according to experts. According to Sartono (2009), "Dividend policy is a decision whether the profit earned by the company will be distributed to shareholders as dividends or will be retained in the form of retained earnings to finance future investments". According to Riyanto (2011): The policy is concerned with determining the division of income (earnings) between the use of income to be paid to shareholders as dividends or to be used in the company, which means that the income must be invested in the company. The dividend policy carried out by the company can take various forms. Dividend policy is an integral part of the company's funding decisions, the dividend payout ratio (dividend patyout ratio) determines the amount of profit that can be retained as a source of funding. The greater the retained earnings the less the amount of earnings allocated for dividend payments. The dividend payout ratio is the percentage of earnings paid in the form of dividends to the total earnings available to shareholders (Van Horne, 2009). This ratio can be found using the following formula: DPR=DividendPerShare/EarningsPerShare×100%

Liquidity
The size of the liquidity ratio is a problem related to the problem of a company's ability to meet its financial obligations that must be met immediately (Riyanto, 2011). Liquidity ratio is an indicator of the company's ability to pay all shortterm financial obligations at maturity using available current assets. The liquidity of the company will greatly affect the size of the dividends paid, so the stronger the company's liquidity position against the prospect of future funding needs, the higher the cash dividends paid. This means that the stronger the company's liquidity position, the greater its ability to pay dividends. In this study, liquidity is proxied in the current ratio. Current ratio is a ratio that measures how far the company's current assets can be used to meet its current liabilities (Kasmir, 2016). Current ratio can be calculated by the formula: Current Ratio = Current Assets/Current Debt

Leverage
Leverage can be measured using the debt to equity ratio (DER). Debt to equity ratio (DER) reflects the company's ability to fulfill all its obligations as indicated by the part of its own capital used to pay debts (Kasmir, 2012). If the company determines that the repayment of its debt will be taken from retained earnings, it means that the company must retain most of its income for these purposes and only a small portion of the income can be paid as dividends (Riyanto, 2011). An increase in debt will affect the size of the net income available to shareholders including dividends to be received. If the debt burden is higher, the company's ability to pay dividends will be lower. Debt to equity ratio S can be calculated using the formula: Debt to equity ratio = (Total debt) / (Total equity)

Profitability
Return on equity (ROE) is one of the calculations included in the profitability ratio. ROE is a ratio calculation that shows the company's ability to generate net income using its own capital and generate net income available to owners or investors. ROE (Return on Equity) compares net income after tax with the equity that the company's shareholders have invested (Van Horne and Wachowicz, 2005: 225). The higher the ROE ratio, the higher the value of the company, this is certainly an attraction for investors to invest in the company. The formula for calculating ROE is as follows: Return on equity = Net Profit/Equity

Framework and Hypothesis:
in accordance with expectations when investing. The hypothesis formulation regarding the relationship between liquidity and dividend policy is as follows: H1: Liquidity has a positive and significant effect on dividend policy in IDX High Dividend 20 Index companies on the Indonesia Stock Exchange.

Leverage Effect on Dividend Policy
The leverage ratio is a ratio that describes the company's ability to pay its long-term obligations. Debt to equity ratio (DER) is one of the variables that can measure the leverage ratio. This ratio shows the amount of debt used by the company in order to carry out its operational activities. The increasing debt ratio has an impact on the profitability obtained by the company, because part of it is used to pay loan interest. Lower debt levels follow higher corporate dividend payments. Thus the debt to equity ratio has a negative relationship with dividends. The hypothesis formulation regarding the relationship between leverage and dividend policy is as follows: H2: Leverage has a negative and significant effect on dividend policy in IDX High Dividend 20 Index companies on the Indonesia Stock Exchange.

Effect of Profitability on Dividend Policy
Profitability (return on equity) describes the company's ability to generate profits using its own capital (Kasmir: 2016). If the level of profit is high, then the amount of dividends paid tends to be high, and vice versa if the level of profit is low, then the amount of dividends paid also tends to be low. The theory is that the greater the return on equity (ROE), the greater the amount of dividends distributed. The hypothesis formulation regarding the relationship between profitability and dividend policy is as follows: H3: Profitability has a positive and significant effect on dividend policy in IDX High Dividend 20 Index companies on the Indonesia Stock Exchange.

Hypothesis Formulation Effect of Liquidity on Dividend Policy
Liquidity shows the company's ability to meet short-term obligations. Liquidity ratio can be measured by current ratio. Companies in paying dividends require cash outflows, so there must be sufficient liquidity available. The higher the liquidity, the more able the company is to pay dividends. Current Ratio (CR) is a variable to measure liquidity ratio. If the CR ratio is high, the company has a high ability to meet short-term obligations in the form of cash dividends. If the CR ratio is high, investors can get cash dividends

Research Method:
Research variables are basically anything in the form of anything that is determined by the researcher to study so that information is obtained about it and then conclusions are drawn. Theoretically, variables can be defined as attributes of a person or object that have variations between one person and another or one object and another object (Sugiyono, 2018: 60). Variables can also be attributes of certain scientific fields or activities. The variables to be analyzed in this study can be grouped as follows: 1) Independent Variables This variable is often called the stimulus variable, predictor, antecedent. In Indonesian it is often referred to as an independent variable. Independent variables are variables that affect or cause changes or the emergence of dependent variables (bound). In this study, the independent variables are profitability (ROE), liquidity (CR) and leverage (DER) .2) Dependent Variable This variable is often referred to as the output variable, criterion, consequent. In Indonesian, it is often referred to as the dependent variable. The dependent variable is the variable that is influenced or that becomes the result, because of the independent variable. In this study, the dependent variable is the dividend policy represented by the dividend payout ratio (DPR).

Variable Operational Definition:
1) CR (X1) is a ratio calculation that shows the company's ability to pay its short-term liabilities with current assets owned. CR can be calculated with the following formula: CR= (Current assets)/(Current debt) x 100% 2) DER (X2) is a ratio calculation that reflects the company's ability to fulfill all its obligations as indicated by the part of its own capital used to pay debt DER can be calculated using the following formula: is a ratio calculation that shows the company's ability to generate net income using its own capital and generate net income available to owners or investors. ROE can be calculated with the following formula: ROE= (net income)/(own capital) x 100% 4) DPR (Y) is the percentage of earnings paid in the form of dividends to the total earnings available to shareholders (Van Horne, 2009). ROE can be calculated with the following formula: DPR=Dividend Per Share Earnings Per Share × 100% Types and Sources of Data According to Sugiyono (2018: 16) there are several types of data, namely qualitative data and quantitative data. The types of data used in this study is quantitative data. Quantitative data is data in the form of numbers or quantitative data that is summarized. Quantitative data in this study are the financial statements of companies included in the IDX High Dividend 20 Index on the Indonesia Stock Exchange from 2015 to 2017.

Data Source
The data used in this study used is secondary data. According to Sugiyono (2018: 195), secondary data is data obtained through data that has been researched and collected by other parties related to research problems such as literature studies and financial reports of companies included in the IDX High Dividend 20 Index on the Indonesia Stock Exchange in 2015 to 2017 by accessing the website www.idx.co.id.

Population and Sample:
According to Sugiyono (2018: 117) population is a generalization area consisting of objects / subjects that have certain qualities and characteristics set by researchers to study and then draw conclusions. The population of this study are all companies included in the IDX High Dividend 20 Index on the Indonesia Stock Exchange. According to Sugiyono (2018: 118) the sample is part of the characteristics possessed by the population. If the population is large, and it is impossible for researchers to study everything in the population, for example due to limited funds, energy and time, then researchers can use samples taken from that population.In this study, the authors conducted sampling based on the purposive sampling method, which is a sampling technique with certain considerations (Sugiyono 2018: 124). The criteria for selecting samples are as follows: 1) Companies included in the IDX High Dividend 20 Index on the Indonesia Stock Exchange that distribute dividends from 2020 to 2022. 2) Companies included in the IDX High Dividend 20 Index whose financial statement data from 2020 to 2022 are available on the website www.idx.co.id For more details, the sample selection criteria can be seen in the following table:

Data Collection Method
According to Sugiyono (2018: 193) data collection techniques are the most strategic step in research, because the main purpose of research is to get data. The methods used to collect data in this study are: 1) Observation According to Sugiyono (2018: 78) observation is an operational technique for collecting data through a careful and systematic recording process of symptoms or phenomena that exist in the object of research. In this study, non-participant observation was carried out, namely by collecting, reading, recording data -data, information and information needed through financial reports obtained from the website www.idx.co.id.
2) Documentation Study Documentation study is a way of collecting data obtained from company documents with the object of research or it can also be referred to as a literature study, namely looking for theoretical study material from some literature related to esearch (Arikunto 2006: 158). In this study, the documentation study was carried out with financial research (Arikunto 2006: 158). In this study, the documentation study was carried out with financial statement data and other data obtained from the website www.idx.co.id which was then processed in accordance with the research conducted.

Classical Assumption Test
Before the classical regression model is carried out to test the hypothesis, of course, the model is free from the classical assumption test. The classic assumption test is used to determine whether the regression model passes the classic assumption test. The classic assumption tests according to Ghozali (2016: 99)  the residuals (confounding errors) are not free from one observation to another. if there is a correlation, it is called an autocorrelation problem. Autocorrelation arises because successive observations over time are related to each other (time series data), while in crossection data (crosstime) autocorrelation problems rarely occur. In a regression test, it is said to be good when it is free from autocorrelation elements. Autocorrelation testing can be done with the Runs Test. Ghozali (2016: 140) explains that the runs test as part of non-parametric statistics can also be used to test whether there is a high correlation between residuals. The Runs Test is used with a significance level of 0.05. The runs test formulates that H0 = the line is random (random) and H1 = the line is non-random (non-random). H0 is rejected if the significance level is <0.05 and conversely H0 fails to be rejected if the significance level is >0.05.  (Ghozali, 2016: 101). A good regression model is free from multicollinear symptoms. To detect the presence or absence of correlation between fellow independent variables, it can be seen from the tolerance value not less than 0.10 or the VIF (variance inflation factor) value smaller than 10, so it is said that there is no multicollinearity or even if there is, this can be ignored because the value is very low.

3)
Heteroscedasticity Test The heteroscedasticity test aims to test whether in the regression model there is an inequality of variance from the residuals of one observation to another. If the variance of the residuals from one observation to another is constant, it is called homoscedasticity and if it is different it is called heteroscedasticity (Ghozali, 2016: 104). A good regression model is one with homoscedasticity or no heteroscedasticity. To detect the presence or absence of heteroscedasticity, the Glejser test is used. This method is done by regressing the absolute value of the residual with the independent variables. If the significance value is greater than 0.05, it is said that the model is free from heteroscedasticity.

4)
Autocorrelation Test The autocorrelation test aims to identify whether in a linear regression model there is a correlation between confounding errors that occur in period t and confounding errors that occur in period t-1 (previous). A good test model is free of autocorrelation (Ghozali, 2016: 120). If time is related to each other, this problem arises because Social Science and Humanities Journal, Vol. 07, Issue. 08, Page no: 3143-3154 β1, β2, β3 = Slope or direction of the regression line which states the change in Y value due to a change of 1 unit of X.

2) Multiple Correlation Analysis
In multiple correlation analysis aims to determine how the degree of relationship between several independent variables (variables X1, X2, ......., Xk) with the dependent variable (variable Y) together Based on multiple correlation, which is given the notation RY.12.....n is calculated through the path of the relationship between several independent variables (X1, X2, ......., Xn) with one dependent variable (Y), which is in the form of multiple linear regression Y' = a + b1.X1 + b2.X2 + ...... + bn.Xn. Based on the multiple regression, the multiple linear correlation coefficient is calculated using the following formula: Table 2 Guidelines for Interpreting the Correlation Coefficient

3) Determination Analysis
Determination analysis (R2) is an important measure in regression because it can inform whether the estimated regression model is good or not. The coefficient of determination (R2) reflects how much variation in the dependent variable (Y) can be explained by the independent variable (X). If R2 is close to 1 (100%), then the calculation results show that the better or more precise the regression line obtained. Conversely, if the R2 value is close to 0, it shows that the more inappropriate the regression line is to measure the observation data. The fundamental weakness of using the coefficient of determination is bias towards the number of independent variables included in the model. For every additional independent variable, R2 must increase regardless of whether the variable has a significant effect on the dependent variable. Therefore, it is recommended to use the Adjusted R2 value when evaluating the best regression model. Unlike R2, the adjusted R2 value can increase or decrease if one independent variable is added to the model (Ghozali, 2006: 152).

4) t test
The t test basically shows how far the influence of independent variables individually in explaining the variation in the dependent variable, with a significant level of 0.05. Ha has a significant effect, if sig. t ≤ ɑ = 0.05 and Ha has no effect if sig. t > ɑ = 0.05.

Research Results and Discussion Descriptive Statistical Test
Descriptive statistical tests in this study are presented to provide information about the characteristics of the research variables, including the minimum value, maximum value, average value and standard deviation. Based on the results of the descriptive statistical test, it is found that

Classical Assumption Test Result
Before testing the hypothesis, it is necessary to test the classical assumptions first, which include: normality test, multicollinearity test, heteroscedasticity test, and autocorrelation test.

1)
Normality Test Result Based on the results of the normality test, it is found that the Kolmogorov_Smirnov Z value is 0.124 and the Asymp.Sig. (2-tailed) significance value of 0.416 is greater than alpha 0.05, so the residual value is normally distributed.

2)
Multicollinearity Test Result Based on the results of the multicollinearity test, it is found that the tolerance value of the three independent variables is above 0.10 (0.817; 0.729; 0.933 respectively), which means that there is no correlation between the independent variables. Meanwhile, the calculation of the VIF value shows that all independent variables have a VIF value of less than 10 (1.532; 1.376; 1.821 respectively), which means that there are no symptoms of multicollinearity between the independent variables in the regression model. So it can be concluded that the regression model does not have a multicollinearity problem, which means that the existing regression model is suitable for use.

3) Heteroscedasticity Test Result
Based on the results of the heteroscedasticity test, it can be explained that the significance value for each independent variable in this study is greater than alpha 0.05, namely CR = 0216; DER = 0.138; ROE = 0.275 so it can be concluded that the regression model used in this study has no symptoms of heteroscedasticity.

4) Autocorrelation Test
Based on the results of the autocorrelation test, it is found that the DW value is 1.914. The dU value for the number of independent variables is 3 and the number of samples is 60, the amount of DWtable: dl (lower limit) = 1.4581; du (upper limit) = 1.6830; 4 -du = 2.317. So from the calculation it can be concluded that the DW-test lies between the upper limit (du) and (4-du), so the autocorrelation test results are du < DW < 4-du, namely 1.683 < 1.914 < 2.317. So it can be concluded that there is no autocorrelation in the regression model.

Data Analysis Result: 1) Multiple Linear Regression Analysis Result
Based on the results of multiple linear regression analysis, a multiple linear regression equation can be compiled which can be explained as follows: Based on the multiple linear regression equation above, the multiple linear regression results can be explained as follows: a) In the multiple linear regression equation above, it is known to have a constant of 0.332. The constant amount shows that if the independent variables (ROE, CR, and DER) are assumed to be constant (zero), then the value of the dependent variable (DPR) is 0.332. b) The variable coefficient of CR = 0.117 means that every 1% increase in CR will cause an increase in DPR by 11.7% with the assumption that the other independent variables are constant or fixed. Thus CR has an effect on DPR. c) The coefficient of the DER variable = 0.145 means that every 1% increase in ROE will cause a decrease in DPR by 14 d) The coefficient of the ROE variable = 0.236 means that every 1% increase in ROE will cause an increase in DPR by 23.6%, assuming other independent variables are constant or fixed. Thus ROE has an effect on DPR.

2) Multiple Correlation Analysis Result
Based on the results of multiple correlation analysis, the R value in the table above is 0.630 which is located between 0.600 -0.799, which means that the level of relationship between the independent variables, namely ROE, CR and DER on the dependent variable, namely DPR, shows a strong relationship.

3)
Determination Analysis Result Based on the results of the determination analysis, the Adjusted R-Square number of 0.141 shows that the independent variables, namely ROE, CR, and DER, can explain the dependent variable, namely DPR, by 14.1%, while the remaining 85.9% is explained by other variables not involved in this study.

4)t-test
Based on the results of the t test, it is found that: a) For the variable CR (X1) gives a significance value of 0.002 smaller than ∝ = 0.05. So it can be concluded that the CR (X1) variable has a significant effect on the value of the DPR (Y) variable. b) The DER (X2) variable gives a significance value of 0.000 smaller than ∝ = 0.05. So it can be concluded that the DER variable (X3) has a significant effect on the value of the DPR variable (Y). c) The ROE variable (X1) gives a significance value of 0.003 smaller than ∝ = 0.05. So it can be concluded that the ROE variable (X1) has a significant effect on the value of the DPR variable (Y).

Discussion of Research Results: 1) Liquidity Effect on Dividend Policy (X1)
After partial testing through the t test, it was found that liquidity (CR) has a significant positive effect on dividend policy (DPR). This can be seen from the regression coefficient value of 0.117 showing a positive direction and the t test results which state that the significance value of 0.02 is smaller than ∝ = 0.05. Thus it can be concluded that the CR variable has a positive and significant effect on dividend policy (DPR). This shows that the second hypothesis which states that liquidity has a positive and significant effect on dividend policy is accepted. The results of this study are consistent with research conducted by Wicaksana (2012) and Andriyani (2008) which states that liquidity has a positive and significant effect on dividend policy.

2)
Leverage Effect on Dividend Policy (X2) After partial testing through the t test, it was found that leverage (DER) has a negative and significant effect on dividend policy (DPR). This can be seen from the regression coefficient value of -0.145 indicating a negative direction and the t test results which state that the significance value of 0.000 is smaller than ∝ = 0.05. Thus it can be concluded that the DER variable has a negative and significant effect on dividend policy. This shows that the third hypothesis which states that leverage has a negative and significant effect on dividend policy can be accepted. The results of this study are consistent with research conducted by Putra (2016), Sumantri (2014), and Damayanti (2016) who get similar results, namely leverage has a negative and significant effect on dividend policy.

3)
Effect of Profitability on Dividend Policy (X3) After partial testing through the t test, it was found that Return on Equity (ROE) has a positive and significant effect on dividend policy (DPR). This can be seen from the regression coefficient value of 0.249 showing a positive direction and the t test results which state that the significance value of 0.00 is greater than ∝ = 0.05. Thus it can be concluded that the ROE variable has a positive and significant effect on dividend policy (DPR). This shows that the first hypothesis which states that profitability has a positive and significant effect on

Conclusion:
Based on the results of the research that has been carried out, the following conclusions can be drawn: 1) Liquidity has a positive and significant effect on dividend policy in IDX High Dividend 20 Index companies on the Indonesia Stock Exchange. The higher the liquidity of the company, the more the dividend distribution of IDX High Dividend 20 Index companies on the Indonesia Stock Exchange will increase. 2) Leverage has a negative and significant effect on dividend policy in IDX High Dividend 20 Index companies on the Indonesia Stock Exchange. The higher the company's leverage, the lower the dividend distribution of IDX High Dividend 20 Index companies on the Indonesia Stock Exchange.
3) Profitability has a positive and significant effect on dividend policy in IDX High Dividend 20 Index companies on the Indonesia Stock Exchange. The higher the profitability of the company, the more the dividend distribution of IDX High Dividend 20 Index companies on the Indonesia Stock Exchange increases.

Suggestion
This research is inseparable from limitations, from these various limitations it is hoped that it can be refined in further research. Therefore, some things that the authors can suggest are as follows: 1) The company should increase the proportion of dividends to the level of the company's ability, because the addition of dividends can increase the fulfillment of company funding. The use of dividends can also add investors.

2)
For companies that will pay dividends, they must pay attention to the net profit that the company can generate, and be able to manage its assets effectively and efficiently.