The Role of Capital Structure in Mediating the Effect of Liquidity on Profitability

teknik

decrease, there were instances of growth in 2015 and 2020.The decrease was a result of several factors, including dropping prices of goods and rising short-term debts, impacting the liquidity of the companies.This occurrence goes against the Signalling Theory, which suggests that a rise in the Current Ratio should lead to higher profitability, however, the link between them seems to be adverse.
Prior research on the correlation between liquidity and profitability has demonstrated inconsistent findings.Gusrina et al. (2023), Olaleye et al. (2021), and Sulistyo & Arif, (2022) have all found evidence in their research to support the idea that liquidity ratios have a positive impact on profitability, thus aligning with the Signalling Theory.Nevertheless, differing research suggests conflicting findings, as evidenced in studies conducted by Sulistiono & Nur, (2023) and Safrani & Alwi, (2021), which indicate a negative impact of the Current Ratio on profitability.These contradictory findings indicate a need for more research.In order to tackle this discrepancy, this research will examine how capital structure affects the relationship between liquidity and profitability.The Debt to equity ratio (DER) and Debt to Asset Ratio (DAR) are seen as factors that can impact a company's profitability.A company can increase its profitability by utilizing an ideal capital structure to reduce the cost of capital and mitigate financial risks Van Horne & Wachowicz, (2007).Hence, the focus of this research is to investigate how capital structure can impact the link between liquidity and profitability, offering fresh perspectives on corporate financial operations under the title "The Role of Capital Structure in Mediating the Impact of Liquidity on Profitability."

Types of Research
This study uses a causal research design based on the type of research as per the explanatory nature of science.Causal research aims to offer explanations by identifying causeand-effect connections among different concepts, variables, or strategies that have been created This study uses a causal research design based on the type of research as per the explanatory nature of science.Causal research aims to offer explanations by identifying causeand-effect connections among different concepts, variables, or strategies that have been created (Prof. Augusty Ferdinand, 2014).The purpose of this study is to demonstrate how independent variables impact dependent variables, with the inclusion of mediating variables, allowing for a broad conclusion to be drawn from the results.This study utilizes a quantitative approach in its research methodology to test hypotheses.The study uses quantitative data from financial statements of companies in the Bisnis-27 Index on the Indonesia Stock Exchange (IDX) from 2017 to 2021.

Population and Sample
The population includes all 27 companies listed on the Bisnis-27 Index from 2013 to 2022.The sample was chosen using purposive sampling methods.The study will include companies that meet the following criteria: (1) being listed on the Bisnis-27 Index on the Indonesia Stock Exchange (IDX) between 2013-2022, (2) being continuously included in the Bisnis-27 Index from 2013-2022, and (3) providing data on Current Ratio (CR), Net Profit Margin (NPM), and Debt to Equity Ratio (DER) from 2013-2022.According to these criteria, a total of 6 companies were chosen for the study.

Analysis Method
The quantitative data analysis methods utilized in this study are analytical techniques.Quantitative data analysis consists of handling, displaying, and conducting computations to characterize the data (Siregar, 2015:125).The methods for analyzing the data to solve the research issues consist of descriptive statistics, Path Analysis, panel data regression analysis, classical assumption tests, and are also expanded with Sobel Test analysis.Eviews 12 is the data analysis tool used in this study.

RESULTS AND DISCUSSION Descriptive Statistical Test
The descriptive statistics output was processed using Eviews version 12, yielding the following results and analysis: (TLKM) during the year 2020.This suggests that TLKM had lower liquidity compared to other companies, with a Current Ratio (CR) below average.Simply put, only 63.7% of TLKM's current liabilities were backed by current assets.In 2020, TLKM saw a growth of 18.40% in its current liabilities compared to the previous year, going up from IDR 58,369 million to IDR 69,093 million.This was because the company's current assets grew at a slower rate than the rise in current liabilities in that year.The COVID-19 pandemic heightened the company's challenges, putting pressure on its performance and requiring it to sustain and grow in a sluggish economy.PT Charoen Pokphand Indonesia Tbk reached the highest liquidity value of 3.792.CPIN was established in 2013.This suggests that CPIN was very capable of fulfilling its immediate debts, with IDR 3.792 in current assets for every IDR 1.00 of current liabilities.
PT Charoen Pokphand Indonesia Tbk recorded the lowest profitability value of 0.051 among companies in the Bisnis-27 Index from 2013 to 2022.CPIN was reported in 2017.This shows that CPIN's sales contribution to net profit was relatively less strong when compared to other companies in the Bisnis-27 Index.As per Bisnis (https://market.bisnis.com),CPIN's sales in 2017 were IDR 49.37 trillion, a jump from IDR 38.26 trillion the year before, with a rise in cost of goods sold to IDR 43.11 trillion from IDR 31.74 trillion.Meanwhile, PT Adaro Energy Indonesia Tbk reached a profitability variable of 0.349 or 34.49%.In the year 2022, ADRO will be operational.This indicates that ADRO achieved a net profit of 34.49% from its overall revenue.During that year, ADRO announced a full net profit of US$2.83 billion, equal to IDR 43.23 trillion, showing a 175% growth compared to the previous year, according to Bisnis (https://market.bisnis.com).ADRO's revenue increase was fueled by a rise in sales volume and ASP, backed by elevated coal prices.Weather conditions, supply constraints, and geopolitical events led to prices remaining high, which in turn drove up the annual growth in ASP.ADRO's revenue saw a significant increase as a result of effective operations and the positive effect of increased selling prices for their products, leading to more than a doubling in revenue.
The average liquidity variable is 1.708, higher than its standard deviation of 0.588, while the average profitability variable is 0.118633, higher than its standard deviation of 0.0549.This suggests that the liquidity variable has a well-balanced data distribution with low data deviation, indicating that the data is homogeneous or less varied.With less deviation, the variability of the data is also reduced.Having a probability value of 0.1559 > 0.05, H0 is accepted, demonstrating that the suitable model for substructural 1 is the Common Effect Model (CEM).Cross-section F 2.798608 -5,53 0.17847 Cross-section Chisquare 14.057808 5 0.10556 H1 is accepted for substructural 2 with a probability value of 0,0152 < 0,05, suggesting that the Fixed Effect Model (FEM) is the most suitable model.H0 is accepted for substructural 2 with a probability value of 0,0689 > 0,05, suggesting that the Commom Effect Model (CEM) is the most suitable model.H1 is accepted for substructural 2 with a probability value of 0,0145 < 0,05, suggesting that the Random Effect Model (REM) is the most suitable model.

Classical Assumptions Testing 1. Normality Test
Once the Common Effect Model (CEM) is identified as suitable for substructures 1 and 2, and the Random Effect Model (REM) for substructure 3, the subsequent task is to conduct a normality assessment.This assessment is conducted to determine if the residuals of the regression model adhere to a normal distribution.If the Jarque-Bera probability value exceeds 0.05, it suggests that the model follows a normal distribution.Yet, when the Jarque-Bera probability value is below 0.05, the data in the model is not distributed normally.The normality test results for each substructure are provided below:  According to the normality test results for substructural 1, the Jarque-Bera value is 0.933305, exceeding 0.05.Hence, we can infer that the data in substructure 1 follows a normal distribution.

Figure 2. Normality Test of Substructure 2
The Jarque-Bera value for substructural 2 is 0.537913, indicating non-normal distribution as it exceeds 0.05.This shows that the data in subset 2 follows a normal distribution.Based on the outcomes of both examinations, it can be inferred that the data in substructural 1 and substructural 2 follow the normal distribution.Nevertheless, there is no need for normality testing in substructural 3 because the chosen model estimation is the Random Effect Model (REM).

Multicollinearity Test
The study included a multicollinearity test to check if the regression model's independent variables are uncorrelated.The multicollinearity test is exclusively conducted on models with multiple independent variables.Hence, there is no need for multicollinearity testing for substructures 1 and 2. In the case of substructural 3, the multicollinearity test can be skipped as the chosen model estimation is the Random Effect Model.

Heteroscedasticity Test
The reason for performing a heteroscedasticity test is to assess if there is a variation in variance among the residuals of different observations in the regression model.This study utilized the Glejser test, which involves regressing AbsUi against the independent variables through a regression equation.If the probability value exceeds 0.05, it can be inferred that there is no evidence of heteroscedasticity present in the regression model.The outcomes of the test for heteroscedasticity for substructural models 1 and 2 are as listed below: Having a probability value of 0.1817 greater than 0.05 indicates that there is no evidence of heteroscedasticity in the regression model for substructural 1.A probability value of 0.0532, higher than 0.05, indicates that the regression model for substructural 2 does not exhibit heteroscedasticity.Moreover, the heteroscedasticity test is not needed for substructural 3 as the Random Effects Model (REM) is the chosen model.Findings for Hypothesis 1 are outlined in Table 14.The t-value for the influence of the CR variable on NPM is -0.172465, compared to the critical t-value of 2.00247 for a probability of 0.05 and degrees of freedom of 57.Given that the t-value is lower than the t-table value, with a significance level of 0.8637 which exceeds 0.05, it can be inferred that CR's influence on NPM is both negative and statistically insignificant.As a result, Hypothesis 1 stating that CR positively and significantly influences NPM is not supported, or "H1 is rejected."2. The Influence of Current Ratio on Debt to Equity Ratio.

Hypothesis Testing Results
The calculated t-value for the impact of the Current Ratio (CR) on the Debt-to-Equity Ratio (DER) is -5.301295, as indicated in Table 12 from the results of hypothesis test 2. Comparatively, the critical t-value for a 0.05 significance level and 59 degrees of freedom (60-1) is 2.00100.As the t-value (-5.301295) is lower than the critical t-table value (-2.00100) and the significance level is 0.0000 (lower than 0.05), we can infer that CR negatively and significantly impacts DER.Thus, hypothesis 2, which contends that CR has a negative and significant impact on DER, is confirmed, or "H2 is accepted."

The Influence of Current Ratio on Debt to Asset Ratio.
The results of the hypothesis test for Hypothesis 3, presented in Table 13, reveal that the t-value for the impact of the CR variable on DAR is -4.832751.The t-table value is 2.00100, given a probability of 0.05 and degrees of freedom (60-1=59).The negative t-value being lower than the negative t-table value (−4.832751<−2.00100) with a significance level of 0.0000, smaller than 0.05, leads to the conclusion that CR negatively and significantly influences DAR.As a result, Hypothesis 3, which claims that CR negatively and significantly impacts DAR, is supported, or "H3 is accepted."

The Influence of Debt to Equity Ratio on Net Profit Margin.
The findings of Hypothesis Test 4, displayed in Table 14, indicate that the computed t-value for the impact of DER on NPM is -0.029951.The t-value needed for a significance level of 0.05 and 57 degrees of freedom is 2.00247.Because the computed t-value (-0.029951) surpasses the negative critical t-value (-2.00247) and the significance level (0.9762) is above 0.05, it is inferred that the DER does not have a significant impact on NPM.As a result, the claim in Hypothesis 3 stating that DER positively and significantly impacts NPM has been disapproved, or "H4 is rejected."

The Influence of Debt to Asset Ratio on Net Profit Margin .
The data from Hypothesis Test 5, displayed in Table 14, suggest that the t-value for the impact of DAR on NPM is -0.669565.The t-value required for a significance level of 0.05 and 57 degrees of freedom is 2.00247.The t-value calculated (−0.669565) exceeds the negative critical t-value (−2.00247) and with a significance level of 0.5059 > 0.05, it can be concluded that DAR has a negligible and negative impact on NPM.Hypothesis 5, which claims that DAR negatively and significantly impacts NPM, is not supported and therefore rejected as "H5 is rejected."

Sobel Test
The Sobel Test evaluates how an intervening variable affects the connection between independent and dependent variables.The Sobel Test is computed using this formula: = √ 2   2 +  2   2 +   2   2 -Sa is the standard error of the coefficient a, -Sb is the standard error of the coefficient b, -a is the regression coefficient of the independent variable (X) on the mediator variable (Z), -b is the regression coefficient of the mediator variable (Z) on the dependent variable (Y).The Sobel Test formula is utilized to examine the importance of the partial indirect effect.The calculation of the indirect effect's importance is done using the formula provided below:

Impact of Liquidity on
According to the findings, the calculated t value of 0.15 is lower than the t table value of 1.66 (0.15 < 1.66).Thus, it can be inferred that the Debt to Equity Ratio (DER) is not a significant mediator of the impact of liquidity on profitability within the capital structure."H5 Rejected" According to the findings, with a t-table of 1.66, the calculated t-value is 6.49, exceeding the t-table (6.49> 1.66), indicating that the Debt to Asset Ratio (DAR) effectively mediates the impact of liquidity on profitability."H6 Accepted"

DISCUSSION
Having a lot of cash available in a company doesn't always mean it will be profitable; instead, it could result in funds not being utilized that could have been invested to make money for the company (Fransisca & Widjaja, 2019).Indeed, companies with lower liquidity levels may actually experience higher profitability than those with higher liquidity.The company's assets are better used to fund obligations rather than to improve profits, as shown by research by various authors (Anggarsari & Aji, 2018).This finding is supported by previous research, including studies by Maharani et al. (2022), Sulistiono & Nur, (2023), Safrani &Alwi (2021), andRamadhan Ersyafdi et al. (2022) This research suggests that liquidity, measured by the Current Ratio (CR), does not significantly affect profitability, indicated by the Net Profit Margin.
Any rise in the Current Ratio of a company will notably lower its Debt to Equity Ratio and Debt to Asset Ratio.This is in line with the Pecking Order Theory, which states that firms tend to prioritize internal funding over external funding because it is less risky, while external financing is more risky and could lead to higher interest expenses.Hence, an increased level of liquidity within a company typically leads to a decrease in its capital structure.Simply put, a company with strong liquidity can easily pay off its short-term debts, showing a significant amount of internal funds and reducing the need for borrowing (Afa & Hazmi, 2021).Having high liquidity also gives the company financial freedom, enabling it to utilize existing cash for investments or strategic initiatives without taking on extra debt.Furthermore, it allows the company to more effectively handle crises or economic uncertainties without encountering major financial hardships.This conclusion is backed up by prior research, such as studies conducted by Zalukhu et al.The study suggests that the impact of liquidity on profitability is more significant when mediated by capital structure than when considered directly.Furthermore, the Sobel test outcomes indicate that the capital structure plays a significant and complete mediating role in this connection.As stated by Subagyo (2018), full mediation occurs when the independent variable affects the dependent variable solely through the mediator variable, with this study's results demonstrating that the Current Ratio (CR) does not directly impact Net Profit Margin (NPM).A small Debt to Asset Ratio (DAR) may indicate a safer financial strategy.Moreover, maintaining a high level of liquidity to decrease the Debt Asset Ratio can lead to a decrease in interest costs and have a favorable effect on Net Profit Margin.Reduced interest costs increase the net income generated from the company's activities.
The way in which a company chooses to fund its activities greatly affects its risk, income, and overall performance (Ichwanudin et al., 2023).If a company fails to make proper decisions about its capital structure, it could experience various detrimental outcomes.This can involve higher capital expenses, since relying too much on debt can result in increased interest payments that reduce net income, disturb profit margins, and raise the likelihood of bankruptcy in case of economic downturn.
Liquidity pertains to a firm's capacity to fulfill its immediate liabilities.A company that has ideal liquidity is expected to efficiently use its own funds, like retained earnings, for capital requirements and investment funding without depending on outside sources.This is in line with the Pecking Order Theory, as firms with high liquidity often choose a cautious capital structure with a low Debt-to-Asset Ratio (DAR) due to their capacity to cover short-term debts without taking on more debt.While high liquidity may not have a direct impact on profitability, it can affect profitability indirectly through the use of capital structure.
Previous research by (Mudjijah & Hikmanto, 2018), supports the findings of this study, showing that the influence of liquidity on profitability can be moderated by capital structure.

CONCLUSION
The results of this research indicate that profitability is not significantly affected by liquidity.Whether liquidity levels rise or fall, there is no substantial impact on profitability.This is largely because higher liquidity levels lead to holding more cash, rather than investing in productive assets, which can result in less optimal company performance.Furthermore, liquidity has a significant negative impact on the capital structure, particularly on the Debt-to-Equity Ratio (DER).As liquidity increases, companies tend to reduce their DER, opting to fund investments internally and reduce dependence on external borrowing.Similarly, liquidity significantly negatively affects the Debt-to-Assets Ratio (DAR).Companies with high liquidity often use their internal funds for operations and investments, thus decreasing their reliance on external debt and improving financial stability.The study also finds that the capital structure, as measured by DER, does not mediate the relationship between liquidity and profitability.This suggests that changes in DER do not significantly alter the effect of liquidity on profitability.However, the relationship is mediated by DAR, indicating that DAR plays a role in how liquidity influences profitability.High levels of liquidity decrease the need for borrowing, whereas low liquidity increases reliance on debt.The DAR demonstrates how high liquidity encourages the use of internal capital, which enhances operational efficiency and financial health, thereby impacting profitability.These findings align with previous studies, highlighting the indirect importance of liquidity management in influencing capital structure and profitability.Effective liquidity management is crucial for enhancing financial performance and ensuring long-term stability.

Table 3 . Langrange Multiplier Test of Susstructure 1 Test Hypothesis Cross- section Time Both
H0 is accepted for substructural 1 with a probability value of 0.6833 > 0.05, suggesting that the Common Effect Model (CEM) is the most suitable model.2.

Table 5 . Hausmen test of Susstructure 2
H0 is accepted for substructural 2 with a probability value of 0,4667 > 0,05, suggesting that the Random Effect Model (REM) is the most suitable model.

Table 8 . Hausmen test of Susstructure 3
suggesting that the Fixed Effect Model (FEM) is the most suitable model.