The Effect of Liquidity, Profitability, Leverage and Activity on Financial Distress

Financial difficulties are a problem that occurs in company liquidity, difficult to solve if there is no change in the company structure. When financial difficulties occur, companies experience a lack of working capital. Lack of working capital can be caused by high operating costs or liabilities. Companies experiencing financial difficulties will file for bankruptcy, however there are some companies that do not do this, because the company is still able to survive amidst the problems that occur. The aim of the research is to see how liquidity, profitability, leverage and activity influence financial distress in transportation companies listed on the Indonesian stock exchange in 2018-2022. The research method uses a quantitative descriptive research design with SPSS 26 as a data analysis tool. The research population was 46 transportation companies and the sampling technique used purposive sampling as many as 8 transportation companies listed on the Indonesian Stock Exchange. The research results show that liquidity and activity have no effect on financial distress. Profitability has been significant positive effect on financial distress. Leverage has a negative and significant effect on financial distress. Simultaneously, liquidity, profitability, leverage and activity have a positive and significant effect on financial distress.


LITERATURE REVIEW
This study examines the factors that influence a company's financial distress based on a series of studies.In the study of Andriyani et al. (2018), liquidity using the current ratio has no significant effect on financial distress, while profitability using Return on Assets (ROA) has a significant negative effect.Tukan (2018) found that liquidity is not significantly related to financial distress, while leverage has an insignificant positive effect.Carolina et al. (2017) highlighted that ROA has a significant positive effect, while liquidity is not significantly related to financial distress.In the study of Ardian et al. (2017), liquidity and profitability are not significant, but leverage has a significant positive effect on financial distress.The signaling theory in this text emphasizes that a company's financial statements provide signals to investors regarding the condition and prospects of the company (Jihadi et al., 2021;Markonah et al., 2020).Good signals such as high ROA and high current ratio can attract investors, while bad signals can reduce the value of the company (Setiyowati et al., 2020).The use of financial ratios such as ROA, Current Ratio, and Debt Ratio is key to assessing the potential for financial distress of a company.Overall, this paper highlights the importance of financial ratio analysis in predicting financial distress of manufacturing companies on the IDX, with a primary focus on liquidity, leverage, profitability and activity as relevant variables in this context.The main purpose of financial statements is to provide relevant information regarding the financial health of a company, both for a specific period and over a wider period of time (Margono & Gantino, 2021).This information is not only important for internal parties such as management and employees, but also for external parties such as investors, lenders, suppliers and the general public.Financial statements provide an overview of the company's financial position through information on assets, liabilities, capital, revenues and expenses (Hasibuan et al., 2023).In addition, financial statements also record management's responsibility for the use of company resources.Users of financial statements have different interests according to their roles in the business ecosystem.Investors use financial statements to evaluate potential investment returns and risks, while lenders use the information to assess the company's ability to pay its debts.Employees are interested in the stability and profitability of the company, while suppliers are interested in the company's ability to meet payment obligations.Financial statement analysis methods such as horizontal and vertical analysis help in understanding changes over time and the financial structure of the company (Putri & Rahyuda, 2020;Yufiana, 2021).Other analysis techniques such as ratio analysis are used to measure a company's financial performance, such as the liquidity ratio to assess the company's ability to meet its shortterm obligations.The profitability ratio provides an overview of how efficient a company is in generating profits from sales (Pulungan et al., 2023).The leverage ratio measures the company's level of dependence on debt (Anjani & Budiarti, 2021).By understanding the information available in the financial statements and applying various analysis methods and techniques, stakeholders can make more informed decisions and support the growth and sustainability of the company's business (Dang et al., 2020).
The Interest Coverage Ratio (ICR) is key to measuring a company's ability to pay interest costs without experiencing significant financial difficulties (Nurendra, 2024).Financial difficulties, such as business failure and legal bankruptcy, can threaten the survival of a company and its reputation in the market.Information on financial distress has strategic value for lenders, investors, accountants, management and government (Hanafi et al., 2016).The main causes of financial distress include cash flow mismanagement, operational losses, and excessive debt burden (Carolina et al., 2018).This study will examine the effect of liquidity, profitability, leverage and activity on financial distress in the transportation sector on the Indonesia Stock Exchange (IDX) in 2018-2022.

Liquidity, Profitability, Leverage 1380
According to Arista (2020), the liquidity ratio, also known as the working capital ratio, is used to measure a company's level of liquidity.The measurement of the liquidity ratio yields two outcomes: a company is considered liquid if it can meet its obligations (Wati, 2023).However, the text contains a contradiction regarding liquidity, stating that a company would also be considered liquid if it cannot meet its obligations, which likely represents a misinterpretation.In alignment with the research by Septiani and Dana (2019), liquidity, as proxied by the current ratio, affects financial distress.Their study suggests that an increase in the current ratio level corresponds to a higher likelihood of a company experiencing financial distress.Thus, while the liquidity ratio aims to assess a company's ability to cover short-term liabilities, a high current ratio might indicate potential financial distress due to excessive short-term assets relative to liabilities.

H1: Liquidity has significant effect on a company's financial distress.
Profitability is a ratio used to assess how well a company can return on the investments made within the company.Essentially, a higher profitability ratio indicates the company's strong ability to generate substantial profits.The primary focus of the profitability ratio is to measure a company's earnings.According to Ningsih and Sari (2019), the profitability ratio evaluates a company's ability to generate profits or returns, as well as the effectiveness and efficiency of its management.This is demonstrated by the profits obtained from sales and investment income.Moreover, Islamiyatun (2021) supports this by stating that profitability, measured using the Return on Assets (ROA) indicator, has a positive effect on financial distress.Therefore, understanding profitability ratios helps in assessing a company's financial health, management performance, and potential risks related to financial distress due to inadequate returns.

H2: Profitability has significant effect on the company's financial distress.
According to Putri (2020), the leverage ratio is a metric used to assess the extent to which a company's assets are financed through debt.In a broader context, the leverage ratio evaluates a company's ability to meet both short-term and long-term obligations if the company were to be dissolved or liquidated.This ratio is crucial for understanding the financial structure and risk level associated with a company's debt usage.The research by Andriansyah (2018), as well as Lubis and Patrisia (2019), aligns with this, indicating that there is a significant positive relationship between the leverage ratio and financial distress.This suggests that as a company's leverage increases, its likelihood of experiencing financial distress also rises.Thus, a high leverage ratio can be an indicator of potential financial instability, emphasizing the importance of managing debt levels effectively to avoid negative financial outcomes.

H3: Leverage has significant effect on the company's financial distress.
According to Haifarani et al. (2023), the activity ratio is a metric used to measure a company's efficiency in utilizing its assets.This ratio also helps assess the company's ability to manage its daily operations (Loho et al., 2021).Essentially, the activity ratio indicates whether a company is effectively and efficiently managing its assets or not.Additionally, it shows whether the company can achieve its set targets.The results of this study suggest that a higher activity ratio reflects better asset management and operational efficiency.However, these findings contradict Asfali's (2019) research, which states that the activity ratio, specifically using the Total Asset Turnover (TATO) indicator, has an impact on financial distress.This discrepancy highlights the complexity of financial metrics and suggests that while a high activity ratio generally indicates good performance, it does not necessarily preclude financial difficulties.

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H4: Activity has significant effect on the company's financial distress.
Liquidity, profitability, leverage and activity are some of the factors that can affect financial distress (Fitri & Syamwil, 2020).Shows that CR which measures the company's ability to pay its obligations on time has an influence on financial distress with the help of three other variables.ROA measures the company's ability to generate positive profits overall, DAR looks at the ratio of debt to the company's total assets, and TATO assesses the company's efficiency in using assets to generate sales.These variables are important for companies to consider in order to anticipate the possibility of financial distress, and are also a consideration for investors who want to invest.The results of this study are in accordance with the research of Bernardin & Indriani (2020) which states that liquidity, profitability, leverage and activity have a simultaneous effect on financial distress.H5: Liquidity, Profitability, Leverage and Activity has significant effect on financial distress.

METHODS
The data of this study aims to examine the effect of liquidity, profitability, leverage and activity on financial distress partially and simultaneously in transportation companies on the IDX in 2018-2022.The research method used is quantitative descriptive to describe the social phenomena that occur, by collecting data from the financial statements of companies listed on the Indonesia Stock Exchange.The population of this study was 46 manufacturing companies in the transportation sub-sector listed on the IDX during that period.The data collection method uses documentation of financial reports of transportation manufacturing companies on the IDX.The number of companies in the transportation subsector listed on the Indonesia Stock Exchange (IDX) during the 2018-2022 period.Of the total 46 companies listed in the subsector, only 17 companies consistently published audited annual financial reports in rupiah currency during the period.In addition, there were 21 companies in this subsector that experienced losses for 2-3 consecutive years in the 2018-2022 period.Of all the companies listed, only 8 companies met all the criteria determined to be used as samples in this study.This study includes an analysis of the 8 companies for 5 years, so that there are a total of 40 observation data (8 companies x 5 years).This study examines the effect of liquidity, profitability, leverage and activity on financial distress on the Indonesia Stock Exchange.Descriptive statistical analysis is used to describe company data including minimum, maximum, average, and standard deviation values of independent and dependent Liquidity, Profitability, Leverage 1382 variables.Multiple linear regression adds independent variables to the model to predict the value of the dependent variable.The coefficient of determination measures the relationship between the independent and dependent variables, with the R2 value indicating how well the model can explain the variation of the dependent variable.

RESULTS
The data used in this study were obtained from financial information in the financial statements of the Indonesia Stock Exchange for 2018-2022.The data obtained to be used as variables in this study are Liquidity (Current Ratio), Profitability (Return on Assets Ratio), Leverage (Debt to Assets Ratio), Activity (Total Assets Turnover Ratio), Financial Distress (Interest Coverage Ratio).The financial performance of the companies in this table shows significant variation from 2018 to 2022.Some companies managed to maintain liquidity and profitability, while others experienced fluctuations in debt management and asset utilization efficiency.This reflects the different challenges faced by each company during the period.Descriptive statistical analysis can show the amount of data used in the study and show the minimum, maximum, average, and standard deviation values of each variable.Based on Table 1, it can be explained that the data used in this study amounted to 40 data (N), the minimum, maximum, average and standard deviation values of each variable are explained as follows: Based on Table 1, the characteristics of independent variables (Current Ratio, Return on Assets Ratio, Debt to Assets Ratio, Total Assets Turnover Ratio) and dependent (Interest Coverage Ratio) in 40 data samples for 5 years can be explained as follows.Each variable shows different minimum and maximum values and averages, thus indicating significant data variation between the companies studied.The purpose of the normality test is to determine whether the variables in the regression model have a normal distribution.The test is carried out using One-Sample Kolmogorov-Smirnov, evaluating the Asymp.value.signature.(2 tails).If sig < 0.05 then the data is considered abnormal; if sig > 0.05 then the data is normal.From the histogram image in Figure 2 below, it can be concluded that the histogram curve displays a symmetrical data distribution without any slope to the left or right.This indicates that the data distribution pattern is normal.Based on the normal probability plot in Figure 3, the data shows a normal distribution that meets the regression assumptions.The optimal regression model must meet the requirements of normal distribution and be free from multicollinearity.Multicollinearity, namely the high correlation between independent variables, can be detected by the tolerance value and Variance Inflation Factor (VIF).Tolerance > 0.10 and VIF < 10 indicate the absence of multicollinearity, while tolerance < 0.10 and VIF > 10 indicate the presence of multicollinearity problems.Based on Table 3, the Variance Inflation Factor (VIF) of Liquidity (X1) is 1.496, Profitability (X2) is 1.220, Leverage (X3) is 1.455, and Activity (X4) is 1.455, all of which are less than 10.In addition, the Liquidity Tolerance value (X1) is 0.669, Profitability (X2) is 0.819, Leverage (X3) is 0.687, and Activity (X4) is 0.837, all of which are greater than 0.10.All independent variables have a tolerance value > 0.1 and a VIF value < 10.Thus, it can be concluded that there is no multicollinearity problem in the regression model, indicating that the data is worthy of being studied.Heteroscedasticity testing in regression models determines the variation of residuals evenly across the data.Heteroscedasticity occurs when the variation of residuals is inconsistent, resulting in a wave-like pattern on the Scatterplot graph.A good regression model is one that exhibits homoscedasticity, with uniform residual variation across the data.From Figure 4 Scatterplot, the points are spread randomly, without forming a clear or regular pattern, and are spread both above and below the number 0 on the Y axis.This shows that there is no heteroscedasticity in the regression model so that the regression model is suitable for use.The purpose of autocorrelation testing is to test whether there is a correlation between the disturbance/error of the linear regression model in period t with the disturbance/error in period t-1 (the previous period).A good regression model is a model that does not contain autocorrelation.In this study, the Durbin-Watson test was used to conduct the test by comparing the Durbin-Watson statistics with a significance table value of 5% by considering the sample size and a number of variables.In decision making, if dU < d < 4 -dU then there is no autocorrelation.The results of the autocorrelation test in this study are as follows.Based on the results of table 4, the Durbin Watson statistic is 1.812.This value will be compared with the value of the 5% significance table by considering the number of samples (n) = 40 and the number of independent variables (k = 4) = 4.40.Thus, the upper limit value (dU) is calculated as 1.7209.Because the Durbin Watson statistic of 1.812 is greater than the upper limit (dU) of 1.7209 and smaller than the lower limit (4-dU) of 2.2791 (1.7209 < 1.812 < 2.2791), it can be concluded that there is no autocorrelation because dU < d < 4 -dU.Therefore, this data is suitable for use in research.The R-value is 0.937, which shows that the R-value (0.937) is in the R-value interval (0.801-1,000) with a very strong relationship level.A very strong correlation between the variables Liquidity, Profitability, Leverage and Activity and Financial Distress.This very strong correlation shows that an increase in Liquidity, Profitability, Leverage and Activity causes an increase in Financial Distress.The determination coefficient Adjusted R Square is 0.863

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or 86.3%.This shows that the contribution of the Liquidity, Profitability, Leverage and Activity variables to Financial Distress is 86.3%, while the remaining 13.7% (100% -86.3%) is influenced or explained by other variables not included in this research model.This analysis is used to determine the influence of independent variables on dependent variables using the SPSS 26 program.In the regression equation Y = 32.979+ 0.028X₁ + 4.203X₂ -0.581X₃ + 0.103X₄, the α (constant) value of 32.979 indicates a positive relationship between the independent variables (Liquidity, Profitability, Leverage, Activity) and Financial Distress.Positive regression coefficients for Liquidity (X₁) and Activity (X₄) and negative for Leverage (X₃) indicate the influence of each variable on Financial Distress.The Liquidity Variable does not have a significant effect on Financial Distress in transportation companies on the Indonesia Stock Exchange in 2018-2022, because the significance value (0.445) is greater than alpha (0.05).The Profitability Variable has a positive and significant effect on Financial Distress in transportation companies on the Indonesia Stock Exchange in 2018-2022, because the significance value (0.000) is smaller than alpha (0.05).The Leverage Variable has a negative and significant effect on Financial Distress in transportation companies on the Indonesia Stock Exchange in 2018-2022, because the significance value (0.000) is smaller than alpha (0.05).The Activity Variable does not have a significant effect on Financial Distress in transportation companies on the Indonesia Stock Exchange in 2018-2022, because the significance value (0.623) is greater than alpha (0.05).This test aims to assess the simultaneous influence of Liquidity, Profitability, Leverage and Activity on Financial Distress using the F test.If the significance value <0.05 then Ho is rejected, Ha is accepted; if Fcount> Ftable at α = 0.05 then Ho is rejected, Ha is accepted.These variables simultaneously have the potential to influence Financial Distress at a 95% confidence level.From table 4.13, the significance value is 0.000 which is smaller than 0.05 (0.000 <0.05), and the Fcount value is 62.604 which is greater than the Ftable value (62.604> 2.641).Based on these two criteria, it can be concluded that Ho is rejected and Ha is accepted, in other words, the variables Liquidity, Profitability, Leverage and Activity have a positive and significant effect simultaneously on Financial Distress in transportation companies listed on the Indonesia Stock Exchange in 2018-2022.This test aims to measure the partial influence of Liquidity, Profitability, Leverage and Activity on Financial Distress.Significance is determined by the value of α = 0.05.If Tcount > Ttable, then Ho is rejected, Ha is accepted; otherwise, Ho is accepted, Ha is rejected.Significant variables have the potential to affect Financial Distress.
The test results show that liquidity, profitability, leverage and activity have different effects on financial distress in transportation companies on the Indonesia Stock Exchange in 2018-2022.Liquidity (Current Ratio) partially does not have a significant effect on financial distress (Tcount = 0.773 <Ttable = 2.030), this shows that companies with high liquidity are not always protected from financial crises.While profitability (ROA) has a positive and significant effect on financial distress (Tcount = 14.441>Ttable = 2.030), this shows that companies with high ROA tend to have a lower risk of financial distress.Leverage (DAR) partially has a negative and significant effect on financial distress (Tcount = -3.778>Ttable = -2.030),this shows that although high debt levels are risky, effective use of debt can reduce the possibility of financial distress.While activity (TATO) does not have a significant effect on financial distress (Tcount = 0.773 <Ttable = 2.030), this shows that the efficiency of asset use is not always related to the company's financial risk.Simultaneously, liquidity, profitability, leverage and activity have a positive and significant effect on financial distress (Fcount = 62.604 > Ftable = 2.641), with these variables explaining around 86.3% of the possibility of financial distress in transportation companies.These results show the importance of simultaneously considering the management of liquidity, profitability, leverage, and activity in anticipating and managing the risk of financial distress in the industry concerned.

CONCLUSION
Based on the results of data collection, processing and analysis of transportation companies on the Indonesia Stock Exchange in 2018-2022, the following conclusions were obtained.First, the Current Ratio does not have a significant effect on Financial Distress partially.Second, the Return on Assets Ratio has a positive and significant effect on Financial Distress.Third, the Debt to Assets Ratio has a negative and significant effect on Financial Distress.Fourth, the Total Assets Turnover Ratio does not have a significant effect on Financial Distress.Fifth, simultaneously Liquidity, Profitability, Leverage and Activity have a positive and significant effect on Financial Distress as measured by the Interest Coverage Ratio.The researcher is aware of the limitations of this study that may affect the results.Recommendations for future research include increasing benefits in specific ways.For companies, especially in the transportation sector, it is important to improve financial performance, reduce the risk of financial distress by increasing Return on Assets (ROA) and Debt to Assets Ratio (DAR).Leverage, although it has a negative impact on financial distress, can reduce risk by using debt funds efficiently.For further researchers, it is recommended to add or change independent variables that influence financial distress such as corporate governance mechanisms or labor costs, as well as explore subsectors other than transportation to strengthen understanding of financial ratio variables.

Table 5 .
Dependent Variable Coefficient