Analisis Tingkat Akurasi Model Prediksi Financial Distress Selama Masa Pandemi Covid-19 (Studi Pada Perusahaan Sektor Transportasi dan Pergudangan Bursa Efek Indonesia)

Abstract

The occurrence of the Covid-19 pandemic greatly shook the Indonesian economy. One of the most affected sectors of the company is the transportation and warehousing sector. This is due to reduced community mobilization during the pandemic. Therefore, there is a need for tools that can help company stakeholders in knowing the potential for bankruptcy early. One of them is the use of financial distress prediction models. This study seeks to determine the most accurate prediction model in predicting the potential for financial distress in transportation and warehousing companies during the pandemic. Some of the prediction models that will be used in this study are the Altman Model, Grover Model, Springate Model, Zmijewski Model, and Taffler Model. Meanwhile, the object of this study uses transportation and warehousing sector companies listed on the Indonesia Stock Exchange during 2020-2022. The determination of the most accurate model will use an accuracy test and a type of error test. The results of this study prove that the most accurate model in predicting transportation and warehousing sector companies listed on the Indonesia Stock Exchange is the Grover Model with an accuracy rate of 82.5%.