BANKRUPTCY PREDICTION ANALYSIS USING THE ALTMAN Z-SCORE AND SPRINGATE MODELS IN INSURANCE COMPANIES WHICH GO PUBLIC IN THE INDONESIA STOCK EXCHANGE

Authors

  • Bambang Mahmudi Universitas Sultan Ageng Tirtayasa
  • Enis Khaerunnisa

DOI:

https://doi.org/10.56548/msr.v2i1.45

Keywords:

Bankruptcy, Altman Z-Score, Springate model analysis

Abstract

The research aims to analyze the potential bankruptcy using Altman Z-Score and the Springate model also to find out the level of accuracy prediction model in insurance companies go public on the Indonesia Stock Exchange.  The population used in this research all insurance companies listed on the Indonesia Stock Exchange in the period 2016-2019 with sample of 12 companies.  The research method employs descriptive analysis using secondary data and Paired t test. The results of the research on the prediction of bankruptcy using the Altman Z-Score model showed that 11 insurance companies were in the healthy category and 1 company was in a condition of prone to bankruptcy (grey area).  Based on the average value of the Z-Score prediction compared to the reality value, 10 companies are in accordance with the prediction, and 2 companies are not match with the prediction whereas an Altman Z-Score model has accuracy rate of 83.33%.  The results of the Springate model bankruptcy prediction research showed 4 companies are in good health and 8 insurance companies have the potential to go bankrupt.  The average prediction score of the Springate model is compared with the reality value described 11 companies are in accordance with the predictions, but 1 company is not in accordance with the predictions, the accuracy rate was 91.67%. Based on the result of paired sample t test showed that there were significant differences Altman and Springate model in predicting bankruptcy

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Published

2023-02-09

How to Cite

Mahmudi, B., & Khaerunnisa, E. (2023). BANKRUPTCY PREDICTION ANALYSIS USING THE ALTMAN Z-SCORE AND SPRINGATE MODELS IN INSURANCE COMPANIES WHICH GO PUBLIC IN THE INDONESIA STOCK EXCHANGE. Management Science Research Journal, 2(1), 28–45. https://doi.org/10.56548/msr.v2i1.45

Issue

Section

Management Science Research Journal