The purpose of this study is to determine the prediction of financial distress analysis using the Altman Z-Score, Zmijewski and Grover methods and to determine the most accurate prediction method of financial distress analysis and the error rate of the three methods used in predicting Retail Sub Sector Companies. The type of data in this study uses quantitative data and uses secondary data sources obtained from company financial reports on the Indonesian Stock Exchange website. The sampling procedure used was purposive sampling with predetermined criteria. The samples in this study were 21 Retail Sub Sector companies listed on the Indonesia Stock Exchange for the 2019-2021 period. The data analysis method used was Altman's Modified Z-Score, Zmijewski and Grover methods. The results of this study indicate that the Altman Modified Z-Score method has an accuracy rate of 63%, the Zmijewski method is 62% and the Grover method is 54%. It can be concluded that the Altman modified (Z-Score) method is a method that has the highest level of accuracy for analyzing financial distress in Retail Sub Sector companies for the 2019-2021 period.
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