THE ACCURACY ANALYSIS OF FINANCIAL DISTRESS MODEL A BENCHMARK OF OPERATIONAL PERFORMANCE AND FIRMS’ INVESTMENT - Alang , Syamsu (Asian Finance & Banking Review, 2025)
This study aims to find out the difference in the level of model accuracy among the Modified Altman Prediction (Z-Score), Springate (S-Score), and Zmijewski prediction models in predicting financial distress as a model of predicting operational Management and investment performance benchmarks in Transportation sub-sector firms in the Indonesian Stock Exchange (IDX) for the 4-period time. This study is a quantitative descriptive approach. The sampling technique is purposive sampling. This study utilizes sample data from the IDX, specifically www.idx.co.id, as well as the official websites of each firm. The results demonstrate that the Modification Altman Z-Score model can predict financial distress or potential bankruptcy by correctly assigning as many as 26 out of 48 samples, achieving an accuracy rate of 54.17%. The Springate S-Score model can predict financial distress or potential bankruptcy by assigning as many as 24 samples from 48 samples with an accuracy rate of 50%. The Zmijewski model was able to predict financial distress or potential bankruptcy with the highest accuracy level among the models used in this study, achieving an accuracy rate of 70.83% on 34 out of 48 samples. The conclusion from the three model bankruptcies is that the Zmijewski model is the most suitable for firms to use if they want to attract potential investors. It is used to predict financial distress and operational performance, as well as to inform firms’ investment decisions. The findings of this study suggest that additional financial distress prediction models, such as Ohlson, Grover, and others, can be utilized to compare and contrast the yields of financial distress analysis. JEL Classification Codes: C52, G01, G32, L90, N25.