ANALYSIS FINANCIAL RATIOS ON FINANCIAL DISTRESS OF TRANSPORTATION COMPANY LISTED ON INDONESIAN STOCK EXCHANGE IN 2017-2020 PERIOD

This study wants to see and analyze how the business and financial conditions of transportation companies affected by the covid-19 pandemic using financial ratios measured by CR, DER, ROA, and TATO, which are strengthened in the use of the Altman Z-Score Method as a detector financial distress. The method of this research using altman z-score to predict financial distress with financial ratios and also the data analyze with logistic regression. The result we can find and analyze the effect of liquidity ratio (CR), leverage ratio (DER), profitability ratio (ROA) and activity ratio (TATO) on financial distress condition in transportation company that listed on the Indonesia Stock Exchange for the study from 2017-2020. This study aims to determine the effect of financial ratios, namely the liquidity ratio as measured by the Current Ratio (CR), the leverage ratio as measured by the Debt Equity Ratio (DER), the profitability ratio as measured by Return On Assets (ROA) and the activity ratio as measured by Total Assets Turnover (TATO) on financial distress conditions in transportation companies listed on the Indonesia Stock Exchange for the study period from 2017-2020. So, based on the results of the logistic regression that has been carried out in this study, Liquidity Ratio measured using the Current Ratio (CR) has a positive effect in predicting financial distress conditions, Leverage ratio as measured by using the Debt Equity Ratio (DER) has no effect in predicting financial distress, Profitability ratio as measured by using Return On Assets (ROA) has no effect in predicting financial distress in transportation companies listed on the Indonesia Stock Exchange, and Activity ratio as measured using Total Assets Turnover (TATO) has a positive effect in predicting financial distress


INTRODUCTION Research Background
Indonesia is the 4th largest and most populous country in the world consisting of small and large islands. Indonesia itself is a country with a geography in the form of an archipelago and stretches along the equator from Sabang to Merauke with very promising tourism potential and is often in the spotlight of the world. Indonesia's large and wide territory supports various companies to provide transportation services such as land transportation, sea transportation and air transportation. Transportation is really needed by the community for the present and the future because it facilitates human access in carrying out daily activities.
However, the current condition of the Indonesian economy is at the stage of facing challenges such as a global economic slowdown, higher inflation, and a weakening exchange rate. So that it has an impact on the condition of the Indonesian economy and makes the business world no better than in previous years. This is experienced by sea, land, and air transportation companies where the rupiah exchange rate is getting weaker and continues to weaken periodically causing spare parts to become expensive and the company's operational costs to increase as well as a decrease in the number of passengers from all types of transportation, both sea, land, and air (Hafsari and Setiawanta, 2020).
Under these conditions, if companies try to survive in these conditions, the company must suppress operational costs terminate employees, and make offers to creditors regarding the payment of the company's principal debt. However, if the company is not able to allocate resources (assets) for various operational activities appropriately and financial problems are allowed to drag on, this can affect the company's performance because it will pose a high risk so that the company will be able to experience financial problems and bankruptcy. Therefore, many companies experience a phase or condition where the company's cash flows experience negative results for some time and it is difficult to pay their obligations. This condition is called financial distress.
Financial distress is a financial condition pressure where the company is in trouble or crisis or is not healthy that Business Management and Accounting _Volume 2 Issue 1 (2022) "Strengthening Youth Potential for Sustainable Innovation" 349 occurred before the company went bankrupt (Altman, 2014). Financial distress is also a company's financial pressure which causes a company's financial condition to be not well constrained and threatened with bankruptcy to the detriment of investors' returns (Altman et al., 2017). Financial distress occurs when the company fails or is no longer able to meet the debtor's obligations due to lack and insufficient funds to run or continue the business in the company again (Muchlisin Riadi, 2018). Financial distress is a company management error in managing or managing its business operation plan for the long term (Kisman and Krisandi, 2019). Usually, financial distress shows a declining trend in the financial performance of a company. In other words, it begins with financial distress warning where companies experience financial difficulties in generating profits or earnings income, which continues to decline from year to year.
Financial statements are a tool that can be used by a potential investor to obtain information about the financial position, estimate whether it is stable or not and the business results achieved by a company have reached the target or not. Financial statement analysis can provide an early picture of a company's bankruptcy. Financial statement analysis can also be a very useful tool for management to evaluate business performance and as material for consideration by potential investors in making investment decisions. A business activity carried out by a company certainly has a goal to be achieved by the owner or holder of the company. The company's profit that will be obtained is an achievement of a predetermined target. Achieving targets is very important for the company because achieving the targets that have been set or exceeding the targets set is a separate achievement for the company's management.
The impact of the covid-19 pandemic is considered to have distorted all aspects of people's lives where transportation is public transportation that must be present in every community activity. However, an observer of public transportation policy, Bambang Istianto, said that the transportation sector experienced 80 percent distortion during the covid-19 period, and many bus operators went out of business (Mediaindonesia.com, 2021). Thus, train and aircraft operations are also greatly affected and exacerbated by government policies that impose social restrictions or restrictions on interactions between individuals including PPKM, PSBB, Lockdown, and Work From Home (WFH) enforcement, followed by strict health protocols in public transportation facilities, such as swabs and antigen tests as an effort by the government to suppress the transmission of covid-19. Thus making transportation companies experience losses in their business and business activities.
This is, in 2020 transportation companies experienced enormous losses due to the covid-19 pandemic which had an impact on the operation of the transportation business, both land, water, and air. Thus, the company cannot control its company management properly. However, many of them were able to survive the covid-19 pandemic and could even generate more profits than the previous year.
Thus, the importance of this study wants to see and analyze how the business and financial conditions of transportation companies affected by the covid-19 pandemic using financial ratios measured by CR, DER, ROA, and TATO, which are strengthened in the use of the Altman Z-Score Method as a detector financial distress. With the prediction of the level of bankruptcy on the company's financial condition or financial performance using financial ratios, it is an interesting topic to be studied by many researchers and can also be studied further in the future. I took this topic because there are many transportation companies that have not detected problems that have not been answered in previous research so that the bankruptcy rate of transportation companies has increased dramatically with the addition of the covid-19 pandemic. This research is expected to contribute conceptually, especially regarding financial distress. Then, it can provide input for companies, especially transportation companies, in making decisions to maintain the continuity of their business activities or businesses related to preventive actions to avoid financial distress. And can be used as a consideration in making decisions for potential investors before investing in the company. Based on the description above, the author is interested in researching with the title "ANALYSIS FINANCIAL RATIOS ON FINANCIAL DISTRESS OF TRANSPORTATION COMPANY LISTED ON

Theoretical Benefits
This research is expected to be able to deepen the knowledge gained to implement and predict real situations or cases that occur by using financial ratios as a prediction of financial distress in transportation companies using the Altman Z-Score method.

Policy Benefits
This research is expected to be able to provide policy direction on how to make decisions in analyzing financial statements that involve financial ratios as a prediction of financial distress and find out what strategies are used so that companies can survive.

3.Practical Benefits a. For Company
This research is expected to be a consideration for companies from related parties in analyzing the company's performance to detect early potential for financial distress and corporate bankruptcy.

b. For Investor
This research can be expected to provide information to investors as consideration for making decisions in investing their capital into companies in the future.

Bankruptey Theory
Bankruptcy is the point where the company experiences a condition of inability to pay an obligation on time because its debt and equity are not sufficient to support the balance sheet. Thus, the company is unable to continue its operational activities if the company's financial condition declines.
According to (Ross, Westerfield, Finance and Edition, 2003), bankruptcy is defined as follows: 1. Business failure A situation where the business ends up with a credit loss and all of the company's capital is exhausted. This, can stop the company's operations because of its inability to make a profit.

Legal bankruptcy
Bankruptcy in which the company is in legal proceedings to liquidate and reorganize the business.

Technical insolvency
A condition where the company does not fulfill its obligations at the specified maturity.

Accounting insolvency
A company that has negative income and total liabilities are greater than total assets.
According to Fitriani (2011) as cited by (Fadrul and Ridawati, 2020) , Bankruptcy is the failure of a company that runs its operations to generate profits until the company is in a critical period in managing its finances. Furthermore, (Onakoya and Olotu, 2017) say that bankruptcy is when a company does not get sufficient income or profit to cover the costs for the company's needs. This company is said to manifest a negative economic value.
According to (Eugene F. Brigham and Joel F. Houston, 2019) Bankruptcy is usually defined as the company's failure to regulate or run the company's operations to generate profits and is defined as follows: 1. Economic failure, is a condition where the company loses money or the company's income is not able to cover the costs incurred by the company itself, meaning that the profit rate is smaller than the cost of capital or the present value of the company's cash flow is smaller than its liabilities. This failure occurs because it occurs when the actual cash flow of the company is far below the distributed cash flow.
2. Financial failure, is a condition where the company is experiencing difficulty in funds, either cash funds or working capital funds. Some asset and liability management plays a very important role in arrangements to prevent financial failure. Financial failure can also be interpreted as insolvency that distinguishes between the cash flow basis and the stock basis.
The definition of default has several meanings, failure is defined as the company's inability to pay its financial obligations as they fall due and also failure is when the Business Management and Accounting _Volume 2 Issue 1 (2022) "Strengthening Youth Potential for Sustainable Innovation" 351 company is unable to pay their suppliers, shareholders or lenders. Bankruptcy varies from the number of attributes or what attributes are considered. One of the most popular models is the Altman Z-Score method with a five factor multivariate discriminant analysis model.

Financial Statements
According to (Ikatan Akuntan Indonesia, 2012) states that financial statements are a structured presentation of the financial position and financial performance of an entity. The purpose of a financial statement is to provide information about the financial position, financial performance, and cash flows of an entity that is useful to most users of financial statements in making economic decisions. According to Kasmir (2015) as cited by (Sari, Hasbiyadi and Arif, 2020) Financial statements are reports that show the company's financial condition at this time or in a certain period. The purpose of financial statements that show the current condition of the company is the current condition of a company (the company is healthy or not). Usually financial reports are made per period of three months or six months for the company's internal interests.
Meanwhile, for a wider report, it is carried out once a year. In addition, the existence of this financial report can find out the current position of the company after analyzing its financial statements.

Financial Ratios
Company performance is a formal effort carried out by the company to evaluate the efficiency and effectiveness of the company's activities that have been carried out in a certain period of time. According to Fahmi (2014:108) as cited by (Satiaputra and Suherman, 2019) Financial performance is the result that has been achieved by company management in carrying out its function to manage company assets effectively for a certain period. Another definition, financial performance is the company's ability to manage and control its resources. From the above understanding it can be concluded that the financial performance of a company is a formal business that has been run by the company. Based on the analysis obtained, the use of liquidity ratios, leverage, and profitability have a positive effect on the assessment of the company's financial performance. Financial performance and operating performance are things that companies can do to measure the success of a company in generating profits, so that they can see the company's prospects in the future, growth and potential for company development by relying on the company's resources. A company can be said to be successful if it has achieved the standards and initial goals set by the company. Financial performance is analyzed by financial ratio analysis according to (Eugene F. Brigham and Joel F. Houston, 2019), the ratios are as follows:

Liquidity Ratio
Ratio to find out the size of the company's ability when the need increases. According to (Ross, Westerfield and Jaffe, 2004) liquidity ratio is a ratio that describes the company's ability to meet short-term obligations. This means that if the company is billed, the company will be able to meet the debt, especially debt that is due. The liquidity ratio that is the focus of this research is the type of ratio of Current Ratio (CR) can be used as a tool to measure the level of security of a company (Kasmir, S.E., 2018). The formula for calculating CR is as follows:

Leverage Ratio
Ratio to determine the size of the company's funding to debt and equity. This ratio shows the company's ability to meet all of its financial obligations if the company is liquidated at that time. That is, how much debt is borne by the company compared to the assets owned by the company in measuring the company's ability to pay all its obligations, both short-term and long-term if the company goes into liquidation. The leverage ratio that is the focus of this research is the Debt To Equity Ratio (DER). This ratio calculates the extent to which the company's assets are financed using debt. This ratio can be calculated by comparing the company's total debt with total equity (Kasmir, S.E., 2018). The formula for calculating DER is as follows:

Profitability Ratio
According to (Weygandt Kimmel Kieso, 2013) the ratio is to determine the size of the company's ability to earn profits, as well as to determine the size of the company in realizing the comparison between profits and assets and between capital in generating these profits. Profitability ratio is a ratio to assess the company's ability to seek profit. And the profitability ratios show the combined effect of liquidity, asset management and debt on operating results. The profitability ratio that is the focus of this research is the Return on Assets (ROA). This ratio reflects how big the return is by utilizing the assets owned by the company to generate profits. So, if ROA increases, it means that the company's sales level will increase and ultimately will increase the profits that can be enjoyed by shareholders (Kasmir, S.E., 2018). The formula for calculating ROA is as follows:

Activity Ratio
Proceedings Ratio to determine efficiency measures both in managing assets and in the use of assets in obtaining company loans. According to Munawir (2002:240) in (Rahayu, Suwendra and Yuianthini, 2016), activity ratio, namely the ratio to assess the company's ability to carry out daily activities or the company's ability to sell, collect receivables and use assets owned. The activity ratio that is the focus of this research is the Total Assets Turn Over (TATO). This ratio can be used to measure the ability to turn over all assets owned by the company and measure how many sales are obtained (Kasmir, S.E., 2018). The formula for calculating TATO is as follows:

ALTMAN Z-SCORE METHOD
Edward I Altman is a researcher who researched a Z-Score analysis method for the first time, which method is known as Multiple Discriminant Analysis (MDA). The Altman Z-Score method is a financial analysis model to identify or predict a company's financial performance related to the potential for bankruptcy due to the problems that exist in a company. The Altman Z-Score method has varying percentages of accuracy for each sample such as 95% accuracy for one year before bankruptcy, 72% for two years before bankruptcy, 48%, 29%, and 36%, respectively for three, four and five years before the bankruptcy occurred.
In addition, it is also known that companies with very low profitability have the potential to go bankrupt. Until now, the Z-score is still widely used by researchers, practitioners, and academics in accounting and other fields.
Altman used his bankruptcy model to become the first Altman (Altman I Edwarrd, 1968), revised, and modified Altman (Altman, Hartzell and Peck, 1998). The development of the Altman model can be seen from the first time it was used to predict the bankruptcy of a public manufacturing company. Then, Altman revised the bankruptcy model into a model that can be used to predict the probability of bankruptcy models for private and public manufacturing companies. Furthermore, Altman modified his model to be applicable in all companies, such as manufacturing companies, nonmanufacturers, and bond issuers. The Altman Z-Score method is a model that calculates bankruptcy in companies that have gone public and large companies. The factors in this model are grouped into 5 standard ratios, namely the ratio of profitability, liquidity, leverage, solvency, and activity. The formula of this Altman Z-Score method (Altman, 2000) is: Z= 1,2 X1 + 1,4 X2 + 3,3 X3 + 0,6 X4 + 1,0 X5 The following is an explanation of the ratio variables contained in the Altman Z-score method:

Working Capital/Total Assets (X1)
This ratio measures the company's liquid assets compared to its size, where working capital is meant as the difference between current assets and current liabilities. If the company has relatively high working capital compared to total assets, then the company has relatively good liquidity (Altman, 2000). Meanwhile, companies that often experience operating losses will see the depreciation of their current assets compared to their total assets. The formula in this ratio is:

Retained Earnings/Total Assets (X2)
Retained earnings are considered as the total amount of reinvested earnings or profits that are not distributed to shareholders. Retained Earnings to Total Assets basically measures the level of leverage and cumulative profitability of a company. When this ratio is high, it implies that the company has financed its assets through earnings retention and is not using a lot of debt. This ratio also shows the strength of earnings and the age of the company (Altman, 2000). The formula in this ratio is:

Earnings Before Interest and Taxes/Total Assets (X3)
This Earnings Before Interest and Taxes to Total Assets ratio shows profitability, which specifically measures the rate of return the company generates from its assets. In other words, if the ratio is high, it shows the company is able to utilize its assets to generate profits efficiently. This ratio also estimates the cash stock which will be allocated to creditors, government and shareholders. With this, this ratio is very appropriate for investigating corporate bankruptcy because the ultimate existence of a company depends on the strength of earnings (Altman, 2000). The formula in this ratio is: Earnings before interest and taxes decreased due to the increase in operational costs related to the company's expansion and extraordinary transactions that occurred such as tax amnesty fees and cargo cartel contingent fines. According to Christina, et al (2020) as cited by (Yunus, 2019) stated that profit gains were caused by improving financial and operational performance, and experiencing a decline which was the impact of an increase in the company's operating costs.

Market Value Equity/Book Value of Total Liabilities (X4)
This ratio measures how quickly the company's assets will decline when the company becomes bankrupt when the liabilities exceed the assets calculated by the company's market value. The market value of equity is equal to the product of the company's share price with the number of shares outstanding such as common stock and preferred stock. The higher the ratio, the less companies rely on debt and have a higher chance of surviving when there is an economic downturn (Altman, 2000). The formula in this ratio is: If a company experiences fluctuations such as a decrease in the value of shares with an increasing capital market value, then it occurs because of changes in the value of the shares that always change every year. According to Hendrayana and Yasa (2015) in (Yunus, 2019) stated that changes in stock prices are influenced by company performance as measured by the company's health level, if the company's performance is good, the company's value will be high. Then, the book value of debt, if it increases every year, it could be due to the increase in bonds payable along with the issuance of Sukuk, growth in third-party trade payables in aviation services, increase in bank debt related to the company's working capital facilities finance fuel and aircraft asset maintenance.

Sales/Total Assets (X5)
The ratio of sales to total assets measures the ability of a business to generate sales with the smallest possible assets. This ratio is an asset turnover ratio, namely the company's ability to generate income from its assets. This ratio also measures the company's ability to face competitive conditions. The higher the ratio, the better the company will use its assets to generate sales and profit (Altman, 2000). The formula in this ratio is: The company classification is based on the Z value in the first Altman method. The following is a scoring The criteria used to predict company bankruptcy with this method are companies that have a Z score > 2,99 are classified as healthy companies, while companies that have a Z score < 1,81 are classified as companies that have the potential to go bankrupt. Furthermore, scores between 1,81 -2,99 are classified as companies in the grey area.
Then, the company classification is based on the Z value in the revised Altman method. The following table shows the revised Altman Z-Score method: The criteria used to predict company bankruptcy with this method are companies that have a Z score > 2,90 are classified as healthy companies, while companies that have a Z score < 1,23 are classified as companies that have the potential to go bankrupt. Furthermore, scores between 1,23 -2,90 are classified as companies in the grey area.
Then, the company classification is based on the Z value in the modified Altman method. The following table shows the modified Altman Z-Score method: The criteria used to predict company bankruptcy with this method are companies that have a Z score > 2,60 are classified as healthy companies, while companies that have a Z score < 1,10 are classified as companies that have the potential to go bankrupt. Furthermore, scores between 1,10 -2,60 are classified as companies in the grey area.

Explanatory Variables
Variables are divided into two types, namely independent variables, and dependent variables. The dependent variable in this study is Financial Distress on financial performance in the financial statements of transportation company for the 2017-2020 period with Altman Z-score method.
The independent variable is referred to as the output variable or criteria, this variable is a variable that is influenced by the independent variable. The independent variables in this study is the effect of financial ratio such as liquidity ratio (CR), leverage ratio (DER), profitability ratio (ROA), and activity ratio (TATO).

Previous Research
Research Model

Liquidity Ratio (CR) on Financial Distress
The Liquidity Ratio shows the ability of a company to meet its financial obligations that must be fulfilled immediately or the company's ability to meet its financial obligations when billed. High liquidity will reflect the company's ability to pay off its debts, which is also high, indicating that the company is in good health.
Based on research from (Jumliana, 2018) current ratio is one type of liquidity used to measure the company's ability to meet current debt with current assets. The higher the current ratio owned by the company, the company is protected from financial difficulties and vice versa. That is, the Current Ratio has a positive effect on financial distress.
Then, based on research by (Dirhansyah Siregar, 2019) if the current ratio is larger and has a positive effect, the smaller the occurrence of financial distress experienced by the company.

H1: Liquidity Ratio measured by Current Ratio (CR)
has a positive effect on financial distress.

Leverage Ratio (DER) on Financial Distress
Leverage ratio is the ratio used by the company to measure the company's ability to meet its long-term obligations such as interest payments on debt, if the company cannot make payments on existing debts that are greater than the assets owned, the greater the possibility of financial distress if it is not addressed properly good.
According to research from (Makkulau, 2020) that there is no influence between the DER variable and financial distress. This is because companies with high DER are not categorized as companies experiencing financial difficulties and vice versa. Thus, the debt proxied by DER is not able to predict the company's financial difficulties, because the company in obtaining sources of funds will choose a small risk and will improve the management of the company to get high profits.
However, based on research from (Anza, 2020) that the leverage presented can be developed by companies that have risks that have financial difficulties. The amount of DER owned by the company indicates the size of the company's ability to use debt to finance its assets. If a finance company uses more debt, this will pose a risk of difficulty in payment in the future as a result of the debt being greater than the assets owned. If this situation cannot be handled properly, the potential for financial distress will be even greater.
H2: Leverage Ratio measured by Debt Equity Ratio (DER) has a positive effect on financial distress.

Profitability Ratio (ROA) on Financial Distress
The profitability ratio is the ability of the company's management to obtain profits or profits. The greater the profitability obtained, the lower the risk of the company experiencing financial distress. The profitability ratio with the ROA proxy shows the overall current assets used for company operations that can provide profits for the company.
According to research from (Jumliana, 2018) ROA is one type of profitability ratio used to measure how much net income is obtained when measured by the value of its assets. The greater the ROA, the better the company will generate profits so that the company will avoid financial difficulties.

H3: Profitability Ratio measured by Return On Assets (ROA) has a positive effect on financial distress Activity Ratio (TATO) on Financial Distress
The activity ratio can describe the level of efficiency of the company in utilizing existing resources in the company. The high activity of the company will increase the company's profit, this makes the company in a financially secure position.
According to research from (Ramadhani, 2019) financial difficulties can occur if the company cannot utilize assets effectively to increase sales, the company cannot obtain income and losses that will be experienced from asset depreciation. Thus, TATO has a significant negative effect on financial distress. But, according to research from (Nurvita and Budiarti, 2019) total assets turnover is used to measure the company's effectiveness in using its assets. The higher the total asset turnover ratio, the better and faster the company's ability to earn an income is, and the smaller the risk of the company experiencing financial distress. Thus, it can be concluded that TATO has a Business Management and Accounting _Volume 2 Issue 1 (2022) "Strengthening Youth Potential for Sustainable Innovation" 356 relationship and they have positive effect on financial distress.

H4: Activity Ratio measured by Total Asset Turnover (TATO) has a positive effect on financial distress
Based on previous research, the development hypotheses contained in transportation company listed on IDX period of year 2017-2020 are as follows: 1. H1: Liquidity Ratio measured by Current Ratio (CR) has a positive effect on financial distress.

Type of Reseach
In quantitative research, generally the research has a wider scope and more diverse variations than qualitative research. Quantitative research is more systematic, planned, structured, clear from the beginning to the end of the research and is not influenced by the conditions that exist in the field (Siyoto & Sodik, 2015). This type of research is quantitative research, which is a systematic study of a phenomenon by collecting data that can be measured by statistical, mathematical, or computational engineering calculations (Hardani. Ustiawaty, 2017). This study is a quantitative study because this study provides an overview of the company's financial health level during 2017-2020 using calculations in the form of financial ratio analysis contained in the Altman Z-Score method.

Sampling Technique
In this study using purposive sampling technique, where the technique of determining the sample through certain considerations. This criteria of study based on: 1. Transportation companies that report and publish their financial statements on the Indonesia Stock Exchange for the period 2017-2020 2. A transportation company with an active status or always listed on the Indonesia Stock Exchange during the specified period, namely the 2017-2020 period 3. Annual data of transportation companies experiencing grey zones in the Altman Z-Score Method

Data Collection Technique
In this study, to obtain data, researchers used the documentation method, namely collecting data in the form of financial statements of transportation companies obtained from the Indonesia Stock Exchange website, namely www.idx.co.id and also using financial reports on the transportation company website in 2017-2020 which became the object during the research period. And can also use data collection techniques such as literature studies, journals and articles to strengthen the data presented in this study (Uma Sekaran & Roger Bogie, 2016).

Population and Sample
According to (Sari and Sugiyono, 2016) The population is the total number consisting of objects or subjects that have certain characteristics and qualities determined by the researcher to be studied and then draw conclusions. Based on the above understanding, the population in this study is the financial statements at transportation company, both land, sea and air which are listed on the Indonesia Stock Exchange.
In this study, the criteria of population for transportation company in Indonesia period 2017-2020 as follows :

Analysis Data Technique
This study uses data analysis techniques by calculating financial distress based on financial statement data at transportation company both land, sea and air obtained on the Indonesia Stock Exchange or the official website of company with measurement by financial ratios such liquidity ratio (CR), leverage ratio (DER), profitability ratio (ROA) and activity ratio (TATO) on financial distress using the Altman Z-Score method to predict bankruptcy. In order for this study to obtain more robust data, it can be tested with the following tests:

Descriptive Statistic Test
The descriptive method according to (Sari and Sugiyono, 2016) is a data analysis technique to explain or describe and describe data in general or generalization, by calculating the maximum value, minimum value, and average value. This study uses financial ratio data such as CR, DER, ROA, and TATOs on transportation companies listed on the Indonesia Stock Exchange for the 2017-2020 period.

Classic Assumption Test
This study only uses the multicollinearity test because it is based on (Imam Ghozali, 2018) that hypothesis testing using logistic regression analysis does not use the normality test, heteroscedasticity test, and autocorrelation test because before hypothesis testing is carried out, the first step that must be done is to assess the feasibility of the regression model. and assess model fit. The function of assessing the feasibility of the regression model and the fit model is a substitute for the classical assumption test.

a. Multicolllinearity Test
The multicollinearity test aims to test whether the regression model found a correlation between the independent variables. A good regression model should not correlate with the independent variables. If the independent variables are correlated with each other, then this variable is not orthogonal. Orthogonal variables are independent variables whose correlation value between independent variables is equal to zero. To detect the presence or absence of multicollinearity in the regression model, the standard error value of the independent variable is less than one, the beta coefficient value is also smaller than one. Next is the tolerance value of the four independent variables, all > 0.100. Likewise with the value of VIF < 10.00 (Imam Ghozali, 2018

Omnibus Test of Model Coefficients
According to (Imam Ghozali, 2018) this test is a test conducted to test whether the independent variables can have a simultaneous effect on the dependent variable. This can be seen from the significant value greater than 0.05, the independent variable simultaneously has no effect on the dependent variable and vice versa.

Coefficients Determinant Test (R²)
Based on (Imam Ghozali, 2018) Cox and Snell's R Square is a measure that tries to imitate the size of R² in multiple regression which is based on the Likelihood estimation technique with a maximum value of less than 1 (one) making it difficult to interpret. Nagelkerke's R Square is a modification of the Cox and Snell coefficients to ensure that the value varies from 0 (zero) to 1 (one). This is done by dividing the value of Cox and Snell's R² by its maximum value. Table   According to (Imam Ghozali, 2018) The table is used to calculate the true and false estimation values. In the column are the two predicted values of the dependent variable in terms of "Non-Financial Distress" (1) and "Financial Distress" (0), while the row shows the actual value of the dependent variable. In a perfect model, all cases will be on the diagonal with a 100% forecasting accuracy.

b. Hypothesis Test 1. Wald Test
In this logistic regression analysis, a partial test was carried out with the Wald test used to test whether there was an effect of the independent variable on the dependent variable partially. The level of significance that must be considered is the significance value < 0.05 then it is accepted (significant regression coefficient), which means that the independent variable affects the dependent variable. Then, if the significance value is > 0.05 the hypothesis is rejected (regression coefficient is not significant), which means that the independent variable does not affect the dependent variable.
In this test, we will use the following logistic regression analysis equation:

General Discription of Research Object
The objects in this study are all transportation companies in Indonesia from 2017-2020 period. The total number of transportation companies in Indonesia is 43 companies during 2017-2020. So, with a period of 4 years, the amount of data obtained is 115 research data that must be sought. The data used is an annual report that presents Current Assets, Current Liabilities, Total Assets, Total Liabilities, Total Equity, Net Income, Net Sales, Working Capital, Retained Earnings, Earning Before Interest and Taxes, Market Value Of Equity. Then, the research method used in this study is Logistic Regression Analysis with Altman Z-Score Method as a detector of financial distress.

Statistic Descriptive Test
Descriptive statistical analysis is used to explain the quality of research data as reflected in the mean and standard deviation, if the mean value is greater than the standard deviation, the data quality can be said to be good. Descriptive statistics can be seen in Table 4.1 as follows: that are affected by financial distress and companies that are not affected by financial distress. There are 94 sample data for the category of companies affected by financial distress. Then, the category of companies that are not Business Management and Accounting _Volume 2 Issue 1 (2022) "Strengthening Youth Potential for Sustainable Innovation" 360 affected by financial distress there is 21 sample data. The percentage result for companies affected by financial distress is 81.7%. Then, the percentage of companies that are not affected by financial distress is 18.3%.

Multicollinearity Test
This test aims to test whether the regression model found a correlation between the independent variables. A good regression model does not correlate with the independent variables. We can see in Table 4.3, to ascertain whether there is a correlation between the independent variables or not.
With the results we see, the results of the correlation between the independent variables show that only the Return On Assets (ROA) variable has a fairly high correlation with the Current Ratio (CR) variable with a correlation level of -0.317 or about 31%. Because this correlation is still very far below 0.95 or 95%, it can be said that there is no serious multicollinearity.
Referring to the results of the multicollinearity test that has been carried out, the requirement that there is no multicollinearity can also be seen from the tolerance value whether it is more than 0.100 and the Variance Inflation Factor (VIF) value is less than 10.00.
With that, we can see in Table 4.4 that in this study, the tolerance value for CR is 0.879 more than 0.100 and the VIF value for CR is 1.138 less than 10.00. Then, the tolerance value on the DER is 0.895 more than 0.100 and the VIF value on the DER is 1.118 less than 10,00. Then, the tolerance value on ROA is 0.865 and the VIF value on ROA is 1.156. Then, the tolerance value for TATO is 0.912 and the VIF value for TATO is 1.097. So, it can be concluded that this research does not have multicollinearity between independent variables in the regression model.

Regression Logistic Analysis
This study uses independent variables with 2 categories so the test uses logistic regression. In this study, the dependent variable consisted of 2, namely "Financial Distress" marked with code 0 and "Non-Financial Distress" marked with code 1.
The data processing application used in this research is IBM SPSS Statistics version 26 with 115 processed data. The completeness of the data used in this study can be seen in Table 4.5 as follows: From Table 4.5, it can be seen that there is no missing data because the output above the value of missing cases = 0, so the amount of data used in the complete study is 115 data.

Assesing Model Fit
Assessing the feasibility of the model used, it is necessary to test the following hypotheses:

Omnibus Test of Model Coefficients
This test is conducted to test whether the independent variable has a simultaneous effect on the dependent variable. If the significant value is greater than (0.05 or 5%) then the independent variable simultaneously does not affect the dependent variable, if the significant value is less than (0.05 or 5%) then the independent variable simultaneously affects the dependent variable.
Based on the results of the research test in Table 4.10 above, it shows a significant value of 0.000 < 0.05, so indicating that the data in this study is feasible to use.

Coefficient of Determinant Test (R²)
The coefficient of determination shows how much the variability of the dependent variable in this study, namely financial distress, can be explained by the independent variables, namely the liquidity ratio (CR), leverage ratio (DER), profitability ratio (ROA) and activity ratio (TATO). The coefficient of determination in this study is indicated by the value of Nagelkerke R Square. Nagelkerke R Square is a modification of the Cox and Snell coefficients to ensure the value varies from zero to one. This is done by dividing the Cox and Snell values that can be interpreted according to the R-Square value in multiple linear regression.

Classification Table
Further explanation regarding the results of the logistic regression on the classification results shows the predictive power of the regression model to predict the probability of receiving the liquidity ratio (CR), leverage ratio (DER), profitability ratio (ROA), and activity ratio (TATO) with an explanation of financial distress. The results of this classification are used to clarify the description or regression of the logistic model with research data, which shows the predicted results with the research results.
Based on the output results in Table 4.11, the regression model used can guess from the original data of 89.6% correctly and the remaining 10.4% is a wrong guess. The ability to predict accurately in the "Non-Financial Distress" category is 52.4% while the "Financial Distress" category is 97.9%. With this, the 115 data samples used are 10 + 11 = 22 data samples that do not experience financial distress (Non-Financial Distress). The sample that does not experience financial distress is 11 data samples and the sample that should not have financial distress but has financial distress has 10 data samples. Then, there are 92 + 10 = 112 data samples experiencing financial distress. The sample experiencing financial distress did not collect 92 data samples and should have 10 data samples.

Hypothesis Testing (Wald Test)
Wald's test contained in the logistic regression analysis was used to test that there was no significant effect of each independent variable on the dependent variable. Processing and calculating data using SPSS 26 for windows program. The results of hypothesis testing are described in Table 4.12 as follows: From the calculation results as shown in Table 4.12, the equations of the logistics model in this study can be stated as follows: In more detail, the effect of each independent variable on the dependent variable will be described as follows:

Liquidity Ratio (CR)
Based on the test results in Table 4.12, the coefficient value of the CR variable is 0.804 and the significance value is 0.001. Because the significance value is smaller than the required significance value, namely 0.001 < 0.05, the CR variable is declared to have a positive significant effect on the financial distress condition of a company. This shows that there is a rejection of Hο and acceptance of Ha. Thus, the first hypothesis in this study which states that the liquidity ratio (CR) has a positive significant effect on financial distress is accepted.

Leverage Ratio (DER)
Based on the test results in Table 4.12, the coefficient value of the DER variable is -0.252 and the significance value is 0.303. Because the significance value is greater than the required significance value, namely 0.303 > 0.05, the DER variable is declared to have no significant effect on the financial distress condition of a company. This shows that there is acceptance of Hο and rejection of Ha. Thus, the second hypothesis in this study which states that the leverage ratio (DER) has a positive effect on financial distress is rejected.

Profitability Ratio (ROA)
Based on the test results in Table 4 profitability ratio (ROA) has a positive effect on financial distress is rejected. Due to the absence of a significant effect but the positive coefficient on financial distress where the level of significance obtained is greater than 0.05.

Activity Ratio (TATO)
Based on the test results in Table 4.12, the coefficient value of the TATO variable is 1.774 and the significance value is 0.020. Because the significance value is greater than the required significance value of 0.020 < 0.05, the TATO variable is declared to have a positive significant effect on the financial distress condition of a company. This shows that there is a rejection of Hο and acceptance of Ha. Thus, the fourth hypothesis in this study which states that the activity ratio (TATO) has a positive significant effect on financial distress is accepted.
Overall, the results of hypothesis testing are presented in Table 4.13 as follows:

Discussion
This study aims to examine the ability of the liquidity ratio (CR), leverage ratio (DER), profitability ratio (ROA), and activity ratio (TATO) in predicting the financial distress status of transportation companies in Indonesia.

The Effect of Liquidity Ratio (CR) on Financial Distress
Based on the results of data analysis, it can be seen that the liquidity ratio as measured by the current ratio has a positive influence in predicting financial distress. Thus, the first hypothesis in this study is accepted. Due to the coefficient of the CR variable of 0.804 and its significance value of 0.001 < 0.05. With this, indeed, the higher the company's ability to pay off its debts, the more protected or healthier the company will be and avoid financial distress. The results of this study support research from (Jumliana, 2018) and research from (Dirhansyah Siregar, 2019) where the Current Ratio results obtained have a positive effect on financial distress.

The Effect of Leverage Ratio (DER) on Financial Distress
Based on the results of data analysis, it can be seen that the leverage ratio as measured by the debt equity ratio has no effect in predicting financial distress. Thus, the second hypothesis in this study is rejected. Due to the coefficient of the DER variable of -0.252 and its significance value of 0.303 > 0.05. The results of this study support research from (Makkulau, 2020) where the DER results obtained do not affect financial distress.

The Effect of Profitability Ratio (ROA) on Financial Distress
Based on the results of data analysis, it can be seen that the profitability ratio as measured by return on assets has no effect in predicting financial distress. Thus, the third hypothesis in this study is rejected. Because the coefficient of the ROA variable is 2.870 and the significance value is 0.352 > 0.05. The results of this study not support research from (Jumliana, 2018) where the ROA results obtained have a positive effect on financial distress.

The Effect of Activity Ratio (TATO) on Financial Distress
Based on the results of data analysis, it can be seen that the activity ratio as measured by total assets turnover has positive effect in predicting financial distress. Thus, the fourth hypothesis in this study is accepted. With this, the higher the TATO, the faster the turnover of assets and profit. In a sense, the company can be considered efficient in using all of its assets in generating sales. The results of this study support research from (Nurvita and Budiarti, 2019) where the TATO results obtained have positive effect in predicting financial distress.

Conclusion
This study aims to determine the effect of financial ratios, namely the liquidity ratio as measured by the Current Ratio (CR), the leverage ratio as measured by the Debt Equity Ratio (DER), the profitability ratio as measured by Return On Assets (ROA) and the activity ratio as measured by Total Assets Turnover (TATO) on financial distress conditions in transportation companies listed on the Indonesia Stock Exchange for the study period from 2017-2020. So, based on the results of the logistic regression that has been carried out in this study, the following conclusions can be drawn: 1. Liquidity Ratio measured using the Current Ratio (CR) has a positive effect in predicting financial distress conditions in transportation companies listed on the Indonesia Stock Exchange.
2. Leverage ratio as measured by using the Debt Equity Ratio (DER) has no effect in predicting financial distress conditions in transportation companies listed on the Indonesia Stock Exchange.
Business Management and Accounting _Volume 2 Issue 1 (2022) "Strengthening Youth Potential for Sustainable Innovation" 364 3. Profitability ratio as measured by using Return On Assets (ROA) has no effect but the positive coefficient in predicting financial distress conditions in transportation companies listed on the Indonesia Stock Exchange.
4. Activity ratio as measured using Total Assets Turnover (TATO) has positive effect in predicting financial distress conditions in transportation companies listed on the Indonesia Stock Exchange.

Suggestion
1. For companies, pay more attention to their financial statements to know how to overcome them so that the company's management does not fall into financial distress.
2. For investors, this research can be used as a basis for making the right decisions whether the company is in a state of financial difficulty or to be clearer when investing in a company.
3. For further researchers, it is possible to develop research samples not only on transportation companies but also on other companies listed on the Indonesia Stock Exchange.
4. For further researchers, they can use or add other financial ratios that may affect financial distress.
5. For further researchers, they can add their research period so that more and more samples will be studied.

Limitations
1. This study only uses financial ratios to predict the company's financial distress. So, there may be other factors that have not been used that can affect the results of this study to predict the condition of financial distress in this study.
2. The period in this study was only four years and only obtained 115 annual data which were processed to be used as research objects.
3. This study only takes a sample of transportation companies listed on the Indonesia Stock Exchange.