Analisis Financial Distress Pada Perusahaan Sektor Food And Beverage Yang Terdaftar Di Bursa Efek Indonesia Pada Masa Pandemi Covid-19

Abstract

Abstract

The purpose of this study is to find out and analyze companies experiencing financial distress. The financial distress analysis in this study used three predictive models, namely the Altman Model modification Z-Score, Grover Score and Zmijewski. In addition, this study aims to find out which prediction models have the highest accuracy rates of the three methods used. Samples in the study in the form of data from food and beverage companies registered with the IDX during the Covid-19 pandemic precisely per quarter of 2020. The analysis method used is an equation of the three models of financial distress prediction. The results of the analysis based on the Equation Altman Model Modification Z-Score showed that food and beverage companies predicted financial distress on average as many as 4 companies. The Grover Score model equation shows that food and beverage companies experienced financial distress on average as many as 3 companies. Zmijewski's model equation shows that food and beverage companies experienced financial distress on average as many as 2 companies. The results of the analysis of the accuracy test showed that the Grover Score Model is a prediction model that has the highest level of accuracy in predicting financial distress by obtaining an average accuracy rate of 76% with an average type I error rate of 22% and an average type II error rate of 19%.

 

Keywords: Financial Distress, Altman Modified Z-Score, Grover Score, Zmijewski.