Analysis of Method Used to Predict Financial Distress Potential in Pulp and Paper Companies of Indonesia

Abstract

This study aims to predict financial distress in pulp and paper companies in Indonesia. The data used are the financial statements of each pul and paper company listed on the Indonesia Stock Exchange in 2012-2017. Data analysis techniques used descriptive analysis with three methods of financial distress prediction, namely the Altman Z-Score, Springate, and Zmijewski methods. The results showed that the Zmijewski method is a prediction method with the highest accuracy rate of 100%, with an error type of 0%. The Altman Z-Score method has an accuracy rate of 28.6%, with an error type of 71.4%. While the Springate method has an accuracy rate of 14.3%, with an error type of 85.7%. Therefore an accurate prediction method to predict the potential for financial distress is the Zmijewski method.