COMPARISON OF MODEL ACCURACY LEVELS BETWEEN ALTMAN Z SCORE AND ZMIJEWSKI IN PREDICTING FINANCIAL DISTRESS IN COMPANIES WITH SPECIAL NOTATION IN INDONESIA

Abstract

The phenomenon of financial distress in public companies is an important concern for investors and stakeholders. The Indonesia Stock Exchange (IDX) applies a special notation as an indicator for companies experiencing financial problems. To predict financial distress, there are several commonly used models, including Altman Z-Score and Zmijewski X-Score. This study aims to determine if there is a significant difference in the value of the prediction results of the Altman and Zmijewski models and to determine which Altman or Zmijewski model is more accurate in predicting financial distress in companies with special notations in Indonesia. This research uses a quantitative approach with a comparative method. The research sample consists of 48 companies with a total of 144 observations. Data analysis was carried out by descriptive statistical test, Mann-Whitney difference test, and prediction model accuracy test. The results showed that there was a significant difference between the predicted values of the two models. The research results show that the Altman model has a higher accuracy rate of 73.61% than the Zmijewski model which only has an accuracy of 68.75%. This finding supports the signaling theory that financial performance can continue to get worse and worse and can indicate that the company gets a special notation, thus influencing investor decisions and can lead to bankruptcy. Thus, the Altman model is more recommended for investors in evaluating the risk of corporate financial distress.