Analisis Model Altman Z-Score, Grover, dan Zmijewski Untuk Memprediksi Kebangkrutan Perusahaan Subsektor Konstruksi - Diva Aulia Hanif; Hero Priono (ARBITRASE: Journal of Economics and Accounting, 2025)
This study aims to compare the accuracy of three bankruptcy prediction models—Altman Z-Score, Grover, and Zmijewski—in identifying the financial condition of companies in the construction subsector listed on the Indonesia Stock Exchange (IDX) during the 2020–2023 period. The background of this research is based on the high vulnerability of the construction sector to economic pressures, especially in the post-COVID-19 era, which has created a growing need for accurate financial prediction tools. This research adopts a quantitative approach using secondary data in the form of financial statements from 20 companies over four years. The analysis techniques employed include descriptive statistics, the Kruskal-Wallis H test to examine differences between models, and an accuracy test to assess the predictive precision of each model. The findings indicate significant differences among the three models, with Grover showing the highest accuracy rate at 80%, followed by Zmijewski at 75%, and Altman Z-Score at 49%. Therefore, the Grover model is considered the most effective in predicting bankruptcy in this subsector. These findings offer important implications for investors, management, and other stakeholders in making more informed financial decisions.