Rahmawati, Nanda Marifah
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Analisis financial distress dengan metode altman, zmijewski, grover, springate, ohlson dan zavgren Rahmawati, Nanda Marifah; Setyorini, Wahyu; Kusumowati, Dewi
Jurnal Ilmiah Bisnis dan Perpajakan (Bijak) Vol 6, No 2 (2024): July 2024
Publisher : University of Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/j.bijak.v6i2.13762

Abstract

This study aims to analyze the accuracy of six financial distress prediction models, namely the Altman, Zmijewski, Grover, Springate, Ohlson and Zavgren models  in transportation companies listed on the Indonesia Stock Exchange during the 2020-2022 period. The results showed that the models that had the highest level of accuracy were  the Grover  and Springate models, but the type of dangerous error Springate was higher than Grover, making Grover the most accurate model in this study. Zmijewski and Altman's models have a fairly high degree of accuracy, but both have dangerous types of errors as well. Altman's dangerous error type is higher than Zmijewski's, so Zmijewski's model is more accurate than Altman's. Ohlson and Zavgren's models have a low accuracy rate, but Ohlson's dangerous error type is so low that even Zavgren does not perform dangerous error types. However, this cannot make Ohlson and Zavgren the most accurate method because of their low accuracy