PREDIKSI FINANCIAL DISTRESS MENGGUNAKAN MODEL TAFFLER DAN GROVER PADA PERUSAHAAN YANG TERDAMPAK PANDEMI COVID-19

Abstract

This study aims to predict and analyze financial distress using the Taffler and Grover prediction model in the companies affected by the Covid-19 pandemic. The data used is the company's quarterly listed in the Indonesia Stock Exchange for 2018-2020, which had positive profit in 2019 and suffered a decline in profits or losses in 2020. The technique used in the data sampling process is a purposive sampling technique of 46 companies. The study results depicts that the Taffler and Grover models can predict financial distress conditions in companies affected by the Covid-19 pandemic. The Taffler model has a greater accuracy rate than the Grover model, which is 73.19%, while the Grover model has an accuracy rate of 71,01%. Prediction results are less accurate due to the Covid-19 pandemic. Pearson's correlation test results showed a correlation between the Taffler model and Grover model that the relationship between variables is strong and unidirectional.

Keywords: Covid-19, Financial Distress, Taffler, Grover, Pearson Correlation.