Analisis Potensi Financial Distress Menggunakan Metode Altman Z-Score, Springate, dan Zmijewski pada Perusahaan Nikel yang Terdaftar di Bursa Efek Indonesia Periode 2020-2024

This study aims to analyze the potential for financial distress in nickel companies listed on the Indonesia Stock Exchange (IDX) during the 2020–2024 period using three bankruptcy prediction models: Altman Z-Score, Springate, and Zmijewski. The primary focus is to identify nickel companies experiencing potential bankruptcy, compare the prediction outcomes among the three models, and determine which model demonstrates the highest level of accuracy in predicting financial distress. This research employs a quantitative approach with a comparative method, in which the sample consists of nine nickel companies selected through purposive sampling based on specific criteria. The analytical techniques used include the Wilcoxon Signed Rank Test to examine differences in prediction results between the models (Altman–Springate, Altman–Zmijewski, and Springate–Zmijewski) and an Accuracy Test to evaluate which model provides the most reliable predictions. The findings reveal significant differences among the models, indicating that Altman, Springate, and Zmijewski produce predictions that are not entirely consistent across companies, thereby reflecting the inherent strengths and limitations of each approach. Furthermore, the accuracy test results indicate that the Zmijewski model achieves the highest level of accuracy in predicting financial distress among nickel companies during the observation period, followed by the Altman model, while the Springate model demonstrates the lowest accuracy. These results highlight the importance of selecting the most appropriate predictive model when assessing corporate financial health, particularly within the nickel industry, which is characterized by high market volatility and business risks, thus providing valuable insights for companies, investors, and stakeholders in making strategic decisions to mitigate bankruptcy risk and ensure business sustainability.

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Publication Details

Journal
OPTIMAL Jurnal Ekonomi dan Manajemen
Published
2025-09-15
DOI
https://doi.org/10.55606/optimal.v5i4.8276
Primary Topic
Management and Optimization Techniques
Type
article
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article

Analisis Potensi Financial Distress Menggunakan Metode Altman Z-Score, Springate, dan Zmijewski pada Perusahaan Nikel yang Terdaftar di Bursa Efek Indonesia Periode 2020-2024

Annisa Paramaswary Aslam, Nurman Nurman, Ilma Wulansari Hasdiansa, Anwar Anwar et al.
OPTIMAL Jurnal Ekonomi dan Manajemen
Management and Optimization Techniques
article

Analisis Potensi Financial Distress Menggunakan Metode Altman Z-Score, Springate, dan Zmijewski pada Perusahaan Nikel yang Terdaftar di Bursa Efek Indonesia Periode 2020-2024

Annisa Paramaswary Aslam, Nurman Nurman, Ilma Wulansari Hasdiansa, Anwar Anwar, Aditya Fajri Mustakim
article en

Abstract

This study aims to analyze the potential for financial distress in nickel companies listed on the Indonesia Stock Exchange (IDX) during the 2020–2024 period using three bankruptcy prediction models: Altman Z-Score, Springate, and Zmijewski. The primary focus is to identify nickel companies experiencing potential bankruptcy, compare the prediction outcomes among the three models, and determine which model demonstrates the highest level of accuracy in predicting financial distress. This research employs a quantitative approach with a comparative method, in which the sample consists of nine nickel companies selected through purposive sampling based on specific criteria. The analytical techniques used include the Wilcoxon Signed Rank Test to examine differences in prediction results between the models (Altman–Springate, Altman–Zmijewski, and Springate–Zmijewski) and an Accuracy Test to evaluate which model provides the most reliable predictions. The findings reveal significant differences among the models, indicating that Altman, Springate, and Zmijewski produce predictions that are not entirely consistent across companies, thereby reflecting the inherent strengths and limitations of each approach. Furthermore, the accuracy test results indicate that the Zmijewski model achieves the highest level of accuracy in predicting financial distress among nickel companies during the observation period, followed by the Altman model, while the Springate model demonstrates the lowest accuracy. These results highlight the importance of selecting the most appropriate predictive model when assessing corporate financial health, particularly within the nickel industry, which is characterized by high market volatility and business risks, thus providing valuable insights for companies, investors, and stakeholders in making strategic decisions to mitigate bankruptcy risk and ensure business sustainability.

OPTIMAL Jurnal Ekonomi dan ManajemenVol. 5(4)
State University of Makassar (ID)
Openalex Percentile: Top 64%
Management and Optimization Techniques
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