This study aims to find the most accurate predictive model for detecting potential bankruptcy in basic industrial and chemical manufacturing companies listed on the Indonesia Stock Exchange (IDX) for the 2017-2021 period by comparing three models namely the Altman Z-Score, Springate S-Score, and Zmijewski X-score. Samples were taken using a purposive sampling technique and a sample of 26 companies was obtained. Data is taken through financial reports published by the company. Comparisons were made by conducting a One Way ANOVA test and analyzing the level of accuracy and error in each model prediction. The results showed that there were significant differences in the results between the Altman Z-Score, Springate S-Score, and Zmijewski X-Score models and based on the level of accuracy and error resulted that the Springate S-Score model had the highest accuracy rate of 96,15% and the the lowest error of 3,85%. So that the most accurate prediction model for detecting potential bankruptcy in basic sector and chemical manufacturing companies listed on the Indonesia Stock Exchange for the 2017-2021 period is the Springate S-Score.
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