Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Indonesian Journal of Islamic Economics and Business
Salsabiila, Salwa
Unknown Affiliation
Religion Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Social Sciences

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Analisis Financial Distress Pada Bank Umum Syariah Di Indonesia Dengan Menggunakan Metode Altman Z-Score, Grover Dan Fulmer Periode 2020-2024 Salsabiila, Salwa; Amalia, Farah; Muyassarah
Indonesian Journal of Islamic Economics and Business Vol. 10 No. 2 (2025): Indonesian Journal of Islamic Economics and Business
Publisher : Fakultas Ekonomi dan Bisnis Islam UIN STS Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30631/ijoieb.v10i2.3739

Abstract

This study analyzes the financial distress conditions of Islamic Commercial Banks (Bank Umum Syariah/BUS) in Indonesia during 2020–2024 using the Altman Z-Score, Grover, and Fulmer models. Employing a quantitative descriptive-comparative approach, the research uses secondary data from annual financial reports of banks selected through purposive sampling with criteria of operating for at least five years, having complete financial statements for 2020–2024, and recording positive EBIT. The analysis applies the three models to assess financial health, with the confusion matrix used to measure accuracy, precision, recall, specificity, and negative predictive value (NPV). Results show that all Islamic banks are generally in a healthy condition, indicated by a Capital Adequacy Ratio (CAR) ≥ 8%. The modified Altman Z-Score achieved 87.27% accuracy and functioned effectively as an early warning system, while Grover and Fulmer models showed perfect accuracy of 100%, classifying all banks as non-distressed. Among the three, the Grover model is the most suitable for Islamic banking due to its simplicity and consistency with empirical data. This study contributes by integrating confusion matrix validation, enhancing the reliability of financial distress prediction in Islamic banking institutions.
Co-Authors Amalia, Farah Muyassarah