Comparation Of Bankruptcy Prediction At Retail Companies In Indonesia Using Altman, Zmijewski and Springate Methods

Abstract

The Indonesian retail sector, a significant contributor to the nation's GDP, faces challenges due to digital transformation, shifting consumer behavior, and increased competition from e-commerce platforms, leading to potential bankruptcy risks among traditional retailers. This study aims to compare the Altman, Zmijewski, and Springate models in predicting bankruptcy of retail companies listed on the Indonesia Stock Exchange from 2019 to 2023. Using financial data from 11 retail companies, the study calculated bankruptcy predictions using the three models and performed statistical tests (Kolmogorov-Smirnov and Kruskal-Wallis tests) to compare their predictive accuracy. The results indicated that the Zmijewski model had the highest prediction accuracy at 90.91%, followed by the Springate model at 81.82%, and the Altman model at 45.45%. The Zmijewski model predicted one company as potentially bankrupt, while the other models provided varying predictions. The study concludes that the Zmijewski model is highest prediction rate in predicting bankruptcy in Indonesian retail companies. This has implications for investors and stakeholders in assessing financial health and making informed decisions