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

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.

Authors

Institutions

Publication Details

Journal
Jurnal Ekonomi Bisnis dan Manajemen
Published
2025-08-19
DOI
https://doi.org/10.58192/ebismen.v4i3.3661
Primary Topic
Financial Analysis and Corporate Governance
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Trisnia Widuri, Ahmad Kamal Idris, Bella Ariani
1 links
Jurnal Ekonomi Bisnis dan Manajemen
Financial Analysis and Corporate Governance
article

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

Trisnia Widuri, Ahmad Kamal Idris, Bella Ariani
article en

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.

Jurnal Ekonomi Bisnis dan ManajemenVol. 4(3)
Universitas Islam Kadiri (ID)
Openalex Percentile: Top 69%
Financial Analysis and Corporate Governance
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.