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Comparative Analysis and Accuracy of Altman Z-Score, Springate, Zmijewski, and Grover Models in Predicting Financial Distress in Basic Industry and Chemical Sector Companies on the Indonesia Stock Exchange for the 2020-2025 Period

2026 · International Journal of Management Studies and Social Science Research · 0 citations · 35 references

Abstract

This study aims to examine the comparative analysis and accuracy of the Altman Z-score, Springate, Zmijewski, and Grover models in predicting financial distress in basic and chemical industry sector companies on the Indonesia Stock Exchange for the period 2020-2025. This study uses a quantitative approach with a descriptive-comparative type. The study population is all companies listed on the IDX in the basic and chemical industry category according to JASICA sector code 3. The sample of this study is the basic and chemical industry sector companies listed on the IDX for the period 2020- 2025 and meet all the established criteria. This study aims to answer three research questions; the conclusions of this study are described as follows. First, regarding the problem formulation regarding the results of financial distress prediction based on each model individually, the four models show different classification patterns according to the characteristics of their respective formulas. Second, regarding the formulation of the problem regarding whether there is a significant difference between the prediction results of the four models, the results of the non-parametric pairwise comparison test prove that there is a significant difference between the prediction results of the Altman Z''-Score, Springate, Zmijewski, and Grover models, both at the categorical classification level (Healthy/Distress) and at the underlying raw score level. Third, regarding the formulation of the problem regarding which model has the highest level of accuracy, the results of the accuracy test using a confusion matrix show that the Grover G-Score model has the highest level of overall accuracy compared to the other three models, so it is determined as the model with the highest level of accuracy in predicting financial distress in basic and chemical industry sector companies listed on the Indonesia Stock Exchange period 2020–2025.

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