Classification of financial distress status in manufacturing companies listed on the Indonesia stock exchange in 2019 with multiple discriminant analysis altman z-score and multiple discriminant analysis stepwise.

This study uses the MDA (Multiple Discriminant Analysis) Altman Z-Score to predict the status of financial distress in manufacturing companies listed on the Indonesia Stock Exchange in 2019. MDA Stepwise model is used to prove that the variables used in Altman Z-Score method are best variables for predicting financial distress. MDA Altman Z-Score uses five variables from financial ratios are working capital/total assets, retained earnings/total assets, earnings before interest and taxes/total assets, market value equility/book value of total liabilities and sales/total assets. The variables used in MDA Stepwise are 38 financial ratios. In this study, the results obtained for the best prediction of financial distress status using MDA Stepwise seen from the highest accuracy value (84.54%) and significant variables in predicting financial distress status are capital market to book value of debt, sales/work capital, and sales/current assets variables. The best classification for manufacturing companies if they are classified into 3 groups, namely the group not experiencing financial distress, gray area and experiencing financial distress. The category of the grouping of companies resulted in 73 companies experiencing financial distress one company was in the gray area and nine companies did not experience financial distress. [ABSTRACT FROM AUTHOR]