EVALUATION OF PREDICTION ACCURACY MODELS FOR BANKRUPTCY IN INDONESIAN BANKS

Abstract

This research aims to find the most accurate model for predicting bankruptcy in the Indonesian banking industry. The data used are secondary data in the form of financial reports from 2018 to 2022. The methodology includes hypothesis testing using normality, homogeneity, and one-way ANOVA tests. The research results indicate that the Springate model is the most suitable model for predicting bankruptcy in the Indonesian banking industry, followed by the Zmijewski model, and the Altman model. The results obtained are relevant for financial managers and regulatory authorities, showing that the Springate model can be used to assess the financial health of the banking industry in Indonesia and to take concrete preventive measures before bankruptcy occurs.

Keywords

• indonesia stock exchange
• financial soundness
• banking supervision