Comparative Analysis of Financial Distress by Using the Bankruptcy Prediction Model

Gusganda Suria Manda, Rabhi Fathan Muhammad (), Angga Sanita Putra, Liya Megawati and Gabriela Prisy Anggraeni
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Gusganda Suria Manda: Universitas Singaperbangsa Karawang
Rabhi Fathan Muhammad: Universitas Singaperbangsa Karawang
Angga Sanita Putra: Universitas Singaperbangsa Karawang
Liya Megawati: Universitas Singaperbangsa Karawang
Gabriela Prisy Anggraeni: Universitas Singaperbangsa Karawang

A chapter in Proceedings of the 8th Global Conference on Business, Management, and Entrepreneurship (GCBME 2023), 2024, pp 193-199 from Springer

Abstract: Abstract This study aims to determine, describe, and analyze whether the Modified Alt- man Z-Score Model, Grover G-Score Model, Springate S-Score Model, and Zmijewski X-Score Model have a high level of accuracy in predicting financial distress in companies or not. The tourism sub-sector is listed on the Indonesia Stock Exchange for the 2017–2019 period. This study used secondary data in the form of the company’s annual financial reports. The population of this study consisted of 24 companies and 10 companies as samples using a purposive sampling technique. The research method used was the comparative quantitative method. The data were processed using Microsoft Excel software, and the results showed that the four bankruptcy prediction models used had a high degree of accuracy, where the Grover G-Score and Zmijewski X-Score models had the highest level, namely 100%, Modified Altman Z- Model Score 83% and Model Springate S-Score 33%. These results have been compared from one model to another. The results give a signal or sign that the company is in financial distress and must immediately implement the right strategy to solve this problem.

Keywords: Bankruptcy Prediction Model; Comparative; Financial Distress; Tourism (search for similar items in EconPapers)
Date: 2024
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DOI: 10.2991/978-94-6463-443-3_28

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