COMPARATIVE ANALYSIS OF FINANCIAL DISTRESS METHODS IN THE AUTOMOTIVE COMPONENT INDUSTRY: ALTMAN, GROVER, AND ZMIJEWSKI

This study aims to determine whether there are differences between the Altman Z-Score, Grover, and Zmijewski methods in predicting financial distress. Moreover, to identify the most accurate prediction method in predicting Automotive and Component companies registered in Indonesia. The population of this study is the financial statements of automotive and component companies listed on the Indonesia Stock Exchange for the period 2016 to 2020. The sampling technique is pair matching sampling with a sample of 12 companies. A ratio scale measured the dependent and independent variables. The method used is descriptive analysis and normality test, followed by the Kruskal-Wallis test using the SPSS version 25 program. The results showed significant differences between the Altman, Grover, and Zmijewski methods in predicting financial distress. And, the Grover method is the most accurate method for predicting financial distress conditions in automotive and component companies in Indonesia because it has the highest accuracy rate compared to other methods at 85%, followed by the Altman method at 83.33% and the Zmijewski method at 66.66%.