Perbandingan Analisis Tingkat Akurasi Menggunakan Metode Altman Z-Score, Springate, Grover, dan Zmijewski

This study aims to compare and analyze the accuracy levels of four financial distress prediction models—Altman Z-Score, Springate, Grover, and Zmijewski—in anticipating the potential bankruptcy of companies subjected to delisting from the Indonesian Stock Exchange (IDX). The delisting phenomenon, which is strongly linked to severe financial deterioration, provided the core motivation for identifying the most reliable predictive instrument, utilizing secondary data from the annual financial reports of delisted companies during the 2019-2023 observation period. Descriptive analysis techniques were employed to calculate the accuracy rate and Type Error for each model. The comparative results consistently indicate that the Springate Model is the most effective, consistent, and accurate model for predicting financial distress in delisted firms, achieving an accuracy rate of 89% in both the first and second years prior to delisting, while the Altman Z-Score model exhibited lower accuracy (68.75% and 62.50%). This key finding emphasizes the superiority of the Springate Model as a crucial diagnostic tool for investors and regulatory bodies in assessing corporate bankruptcy risk.