This study examines the differences in bankruptcy prediction results using three financial distress models, namely Altman Z-Score, Grover, and Springate. The object of research is textile and garment companies listed on the Indonesia Stock Exchange during the 2019-2023 period. A total of eight companies were selected as samples through purposive sampling technique. The data used is secondary data in the form of financial statements. Data processing was carried out by calculating each model using Microsoft Excel, while statistical testing was carried out through the Shapiro-Wilk and Kruskal-Wallis tests with the help of SPSS version 26 software. The analysis results show that there are significant differences between the three models in predicting potential financial difficulties. The Grover model shows the highest accuracy rate of 100%, followed by the Altman model at 87.50%, and the Springate model at 37.50%.
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