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Abstract

Optimizing the risk of bankruptcy is very important in efforts to maintain the company's financial stability. To avoid bankruptcy, it is necessary to have an analysis that can predict the potential bankruptcy of a company. In this research, the author uses two bankruptcy prediction analysis models, namely the Altman model (Z-Score) and the Grover model (G-Score). This research uses data from Samsung, Apple, Asus, Xiaomi and Lenovo, during the period 2013 - 2022. This research aims to compare the analysis results of the two models and determine which method is the most accurate in predict bankruptcy. Based on the results of calculations using the Altman Model, it was found that more of the companies studied were in the "Gray Area" category, while calculations using the Grover Model showed that more of the companies studied were in the "healthy" category. And the Altman model has the highest level of accuracy in calculating potential bankruptcy, namely 38% compared to the Grover model which has an accuracy level of 14 %. This research states that the Altman model is more accurate in predicting potential bankruptcy rather than the Grover model.

Keywords

Altman, Bankruptcy, Financial Distress, Grover , Risk

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite
Rahayu, Y., Zuhriatusobah, J. ., Abdurraafi, M. ., & Supyani, A. . (2025). Optimization Of Bankruptcy Risk Through The Altman And Grover Models: A Comparative Study. Amkop Management Accounting Review (AMAR), 5(1), 29–38. https://doi.org/10.37531/amar.v5i1.2399
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