<![CDATA[The study aims to conduct a predictive test and analysis on the financial distress of companies in the consumer non-cyclicals sector during the COVID-19 pandemic and the Russia-Ukraine geopolitical conflict. This study utilizes three predictive models: the Taffler model, the Fulmer model, and the Grover model. The population of this study consists of consumer non-cyclicals companies listed on the Indonesia Stock Exchange from 2020 to 2022. The research sample consists of 62 companies selected using purposive sampling technique. The Kruskal-Wallis test method is employed and analyzed using SPSS 22. The result of this study indicate a significant difference among the three models in predicting financial distress in companies. Based on the accuracy test conducted, the Fulmer model achieved the highest accuracy rate of 87% with a type I error rate of 3% and type II error rate of 10%. Futhermore, the Grover model obtained an accuracy rate of 83% with a type I error of 16% and a type II error rate of 1%. The Taffler model achieved the lowest accuracy score compared to the three models used, at 77% with a type I error rate of 10% and a type II rate 13%.]]>
Copyrights © 2023
