Pengukuran Potensi Financial Distress Pada Perusahaan Pertambangan Sektor Batu Bara Tahun 2021 – 2023

Nadzuba Vio Larizza; Mulyaningtyas Mulyaningtyas

doi:10.55606/jaemb.v5i3.7774

Authors

Nadzuba Vio Larizza Institut Teknologi dan Bisnis Asia Malang
Mulyaningtyas Mulyaningtyas Institut Teknologi dan Bisnis Asia Malang

DOI:

https://doi.org/10.55606/jaemb.v5i3.7774

Keywords:

Financial Distress, Prediction Model, Coal Mining Industry

Abstract

The purpose of this study is to assess the accuracy of three bankruptcy prediction models: Altman Z-Score, Springate S-Score, and Grover in coal mining companies listed on the Indonesia Stock Exchange during the period 2021 to 2023. The analysis process was conducted using a statistical approach including descriptive analysis, normality test, ANOVA, and Games-Howell post-hoc follow-up test. The research findings indicate significant differences between the three models. The Altman Z-Score shows more conservative results, highlighting high risks, while the Springate S-Score provides optimistic results with an accuracy of 93.33%. The Grover model shows the highest performance with an accuracy level reaching 100%. Based on these results, Grover is considered the most superior in identifying bankruptcy risks in the coal mining sector. The results of this study are expected to serve as a strategic reference for business actors and investors in data-driven decision-making..

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