Analisis Perbandingan Model Altman Z-Score, Springate, Fulmer, dan Taffler Dalam Memprediksi Financial Distress

Abstract

This research is motivated by significant fluctuations and a decline in profits for companies in the clothing and luxury goods subsector listed on the IDX for the period 2021-2023, indicating potential financial difficulties. This research aims to evaluate the company's condition using four prediction models, namely Altman-ZScore, Springate, Fulmer, and Taffler, and to determine the most suitable model for the sector. The method applied is quantitative comparative with a purposive sample of 11 companies, using financial statement data from 2021-2023 and analyzed using the formulas for each predictive model. The research findings indicate that the four models produce different predictions regarding the company's financial condition. Additionally, there are differences in the accuracy levels of the four models. The Springate and Taffler models achieved the highest accuracy rate of 85%, followed by Altman at 67% and Fulmer at 64%. The findings of this study confirm that the Springate model is the most reliable tool for early warning for companies and stakeholders, enabling faster preventive measures to prevent bankruptcy.