Financial Distress Prediction on Agricultural Sector Companies in Indonesia Stock Exchange

Abstract

This study aims to prediction of financial distress in the agricultural sector companies in Indonesia used logistic regression analysis. The data used secondary data from resume financial report of companies at Indonesia Stock Exchange period of 2009-2018. The independent variable in this study are financial ratios and macroeconomic indicators. The independent variables in this study are financial ratios and macroeconomic indicators. Financial ratios consist of DER, CR, CLTA, ROA, ROE, NPM, TATO and WCTA, while the macroeconomic indicators used interest rate and exchange rate sensitivity. Financial distress status is used as the dependent variable. Independent variable such as ROA and WCTA significantly can be used in prediction model with accuration rate of 89,91%. The model also can be used as early warning signal of financial distress in the agricultural sector companies in Indonesia.