PREDIKSI FINANCIAL DISTRESS BANK SYARIAH DENGAN METODE PENDEKATAN ALTMAN Z-SCORE, SPRINGATE S-SCORE, DAN GROVER G SCORE DI WILAYAH ASEAN

Muhammad, Faizal Assyiddiq (2026) PREDIKSI FINANCIAL DISTRESS BANK SYARIAH DENGAN METODE PENDEKATAN ALTMAN Z-SCORE, SPRINGATE S-SCORE, DAN GROVER G SCORE DI WILAYAH ASEAN. Diploma thesis, UIN Raden Intan Lampung.

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Abstract

Abstract This study aims to analyze and compare the accuracy levels of the Altman Z-Score, Springate S-Score, and Grover G-Score models in predicting financial distress conditions in Islamic banks within the ASEAN region. The study area includes Indonesia, Malaysia, Brunei Darussalam, and Thailand during the 2020–2024 period. This research is motivated by the significant growth of Islamic banking assets, which nevertheless still faces unique operational risk challenges compared to conventional banks. The research method used is a quantitative approach with a purposive sampling technique applied to Islamic commercial banks in ASEAN. The research sample consists of four major banks: Bank Muamalat Indonesia (BMI), Bank Islam Malaysia Berhad (BIMB), Bank Islam Brunei Darussalam (BIBD), and Islamic Bank of Thailand (iBank). The analyzed data are secondary data obtained from published annual financial reports for the 2020- 2024 period. The calculation results indicate disparities in financial performance among the banks. The Altman Z-Score model produced an accuracy rate of 62.5%, while the Springate S-Score model showed an accuracy level of 50%. The main finding reveals that the Grover G-Score model proved to be the most effective and accurate model, with an accuracy rate reaching 100%, where all sample banks were categorized as financially healthy during the research period according to this model. These findings confirm that the Grover G-Score model is the most relevant Early Warning System instrument for regulators and Islamic banking management in ASEAN to mitigate bankruptcy risk and maintain the stability of the regional financial system. Keywords: Financial Distress, Sharia Bank, ASEAN, Prediction Model. Abstrak Penelitian ini bertujuan untuk menganalisis dan membandingkan tingkat akurasi model Altman Z-Score, Springate S-Score, dan Grover G-Score dalam memprediksi kondisi financial distress pada bank syariah di kawasan ASEAN. Wilayah penelitian mencakup Indonesia, Malaysia, Brunei Darussalam, dan Thailand selama periode 2020-2024. Penelitian ini dilatarbelakangi oleh pertumbuhan aset perbankan syariah yang signifikan, namun tetap menghadapi tantangan risiko operasional yang khas dibandingkan dengan bank konvensional. Metode penelitian yang digunakan adalah pendekatan kuantitatif dengan teknik purposive sampling yang diterapkan pada bank umum syariah di kawasan ASEAN. Sampel penelitian terdiri dari empat bank utama, yaitu Bank Muamalat Indonesia (BMI), Bank Islam Malaysia Berhad (BIMB), Bank Islam Brunei Darussalam (BIBD), dan Islamic Bank of Thailand (iBank). Data yang dianalisis merupakan data sekunder yang diperoleh dari laporan keuangan tahunan yang dipublikasikan selama periode 2020-2024. Hasil perhitungan menunjukkan adanya perbedaan kinerja keuangan di antara bank-bank tersebut. Model Altman Z-Score menghasilkan tingkat akurasi sebesar 62,5%, sedangkan model Springate S-Score menunjukkan tingkat akurasi sebesar 50%. Temuan utama penelitian ini menunjukkan bahwa model Grover G-Score terbukti menjadi model yang paling efektif dan akurat dengan tingkat akurasi mencapai 100%, di mana seluruh bank sampel dikategorikan dalam kondisi sehat secara finansial selama periode penelitian menurut model ini. Temuan ini menegaskan bahwa model Grover G-Score merupakan instrumen Early Warning System yang paling relevan bagi regulator dan manajemen perbankan syariah di kawasan ASEAN dalam memitigasi risiko kebangkrutan serta menjaga stabilitas sistem keuangan regional. Kata Kunci: Financial Distress, Bank Syariah, ASEAN, Model Prediksi.

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