Analisis Perbandingan Tingkat Akurasi Model Altman Z-Score, Springate, Zmijewski, Taffler, dan Grover dalam Memprediksi Financial Distress Pada BPD yang Memiliki UUS Tahun 2019-2024
DOI:
https://doi.org/10.32502/balance.v10i2.932Keywords:
Altman Z-Score, Grover, Springate, Taffler, ZmijewskiAbstract
The banking sector, particularly Regional Development Banks (BPD) with General Sharia Units (UUS), plays a strategic role in supporting regional economies. The 2019-2024 period was marked by significant economic dynamics, including the impact of the Covid-19 pandemic, which triggered a slowdown in growth and potential financial difficulties in the banking sector. This study aims to determine the accuracy level of the Altman Z-Score, Springate, Zmijewski, Taffler, and Grover models in predicting potential financial distress in BPD with UUS from 2019 to 2024. Using a descriptive quantitative approach with purposive sampling, 11 companies were selected. The results show that the Altman Z-Score and Taffler models have the highest accuracy rate of 100%, followed by Grover 90.9%, Springate 87.8%, and Zmijewski 74.2%. Therefore, the Altman Z-Score and Taffler models are the most accurate predictors of financial distress in BPD with UUS.
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