Accuracy Analysis of Bankruptcy Prediction Models for Food and Beverage Companies on the IDX in 2019-2023

This study aims to analyze and evaluate the performance of companies in the food and beverage sector using the Springate, Zmijewski, and Grover bankruptcy prediction models, and to test their accuracy levels. Secondary data used in this study were taken from the financial statements of companies listed on the Indonesia Stock Exchange (IDX) in the period 2019 to 2023. The study population included 47 companies, from which 29 were selected through purposive sampling, resulting in 145 analysis units. The approach applied was a quantitative descriptive approach. The results of the study showed that the Grover model successfully identified three companies that had the potential to go bankrupt and 26 companies that were in a healthy condition, with the highest accuracy level reaching 95%. The Zmijewski model predicted 6 companies that went bankrupt and 23 companies that were healthy with an accuracy level of 91.7%. Meanwhile, the Springate model predicted 10 companies that had the potential to go bankrupt and 19 companies that were healthy with an accuracy level of 89.6%. The conclusion of this study is that the Grover model is the most appropriate model in predicting the potential for bankruptcy of companies in the food and beverage sector based on the data that has been analyzed.

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Publication Details

Journal
International Journal of Social Science and Business
Published
2025-08-10
DOI
https://doi.org/10.23887/ijssb.v9i2.92208
Primary Topic
Impact of AI and Big Data on Business and Society
Type
article
Field-Weighted Citation Impact
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article

Accuracy Analysis of Bankruptcy Prediction Models for Food and Beverage Companies on the IDX in 2019-2023

Muhammad Fajar, José Salvador, Ristati Ristati
International Journal of Social Science and Business
Impact of AI and Big Data on Business and Society
article

Accuracy Analysis of Bankruptcy Prediction Models for Food and Beverage Companies on the IDX in 2019-2023

Muhammad Fajar, José Salvador, Ristati Ristati
article en

Abstract

This study aims to analyze and evaluate the performance of companies in the food and beverage sector using the Springate, Zmijewski, and Grover bankruptcy prediction models, and to test their accuracy levels. Secondary data used in this study were taken from the financial statements of companies listed on the Indonesia Stock Exchange (IDX) in the period 2019 to 2023. The study population included 47 companies, from which 29 were selected through purposive sampling, resulting in 145 analysis units. The approach applied was a quantitative descriptive approach. The results of the study showed that the Grover model successfully identified three companies that had the potential to go bankrupt and 26 companies that were in a healthy condition, with the highest accuracy level reaching 95%. The Zmijewski model predicted 6 companies that went bankrupt and 23 companies that were healthy with an accuracy level of 91.7%. Meanwhile, the Springate model predicted 10 companies that had the potential to go bankrupt and 19 companies that were healthy with an accuracy level of 89.6%. The conclusion of this study is that the Grover model is the most appropriate model in predicting the potential for bankruptcy of companies in the food and beverage sector based on the data that has been analyzed.

International Journal of Social Science and BusinessVol. 9(2)
Malikussaleh University (ID), University of Santo Tomas (PH)
Openalex Percentile: Top 66%
Impact of AI and Big Data on Business and Society
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