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All Journal International Journal of Social Science and Business
Fajar, M. Syahrial
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Social Sciences

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Accuracy Analysis of Bankruptcy Prediction Models for Food and Beverage Companies on the IDX in 2019-2023 Ristati, Ristati; Fajar, M. Syahrial; Salvador, Jude Anne P.
International Journal of Social Science and Business Vol. 9 No. 2 (2025): May
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/ijssb.v9i2.92208

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.
Co-Authors Ristati, Ristati Salvador, Jude Anne P.