PREDICTION OF THE ACCURACY LEVEL OF FINANCIAL DISTRESS IN TRANSPORTATION AND LOGISTICS SECTOR COMPANIES ON THE INDONESIA STOCK EXCHANGE
DOI:
https://doi.org/10.53067/ije3.v3i3.195Keywords:
Financial Distress, Grover, Zmijewski, Springate, Altman Z-Score modification, prediction modelAbstract
Financial distress is a financial difficulty characterized by reduced and even negative profits. This research analyzes the accuracy of the modified Altman Z-Score, Springate, Zmijewski, and Grover models in forecasting financial distress in transportation and logistics companies in Indonesia. This quantitative descriptive method research uses a population of all transportation and logistics companies listed on the Indonesia Stock Exchange for 2018-2022. The sample size was 23 companies, which were taken using the purposive sampling method. For data collection, the process is to analyze all records and data related to the research owned by the company selected as the object of research. The analysis compares the calculated prediction results with the actual conditions of the sample companies in 2022. The results of this study show that the Zmijewski method is the method with the highest level of accuracy in predicting financial distress in the transportation and logistics sector, followed by the Grover method, the Springate method, and the modified Altman Z-score method
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