The Potential Financial Distress in Special Notation Companies on the Indonesia Stock Exchange: Prediction Model Approach

Abstract

This research aims to predict the potential financial distress in companies with special notation on the Indonesia Stock Exchange during the period from January 1, 2021, to December 2022, using the Modified Altman Model (Z-Score) and the Springate Model (S-Score) approaches. Data for the study were obtained from the official website of the Indonesia Stock Exchange, employing purposive sampling as the sampling technique. Based on the criteria, a total of 280 research observations were obtained. The results indicate that both models can predict the potential financial distress of companies using financial ratios. Furthermore, the research findings reveal differences in the accuracy level of predicting potential financial distress between the Modified Altman Z-Score and Springate models. The Modified Altman Z-Score model demonstrates higher accuracy compared to the Springate model in predicting the potential financial distress of companies with special notation. This research provides important information for companies with special notation codes that experience financial distress, to immediately improve financial conditions, and provides a basis for strategic decision making to ensure the sustainability of the company and for investors and other interested parties can be used as a basis for investment decision making.