Analisis Financial Distress Menggunakan Rasio pada Model Altman (Z-Score), Springate (S-Score), Grover (G-Score) Pada Perusahaan Manufaktur

Bonita, Tasya (2024) Analisis Financial Distress Menggunakan Rasio pada Model Altman (Z-Score), Springate (S-Score), Grover (G-Score) Pada Perusahaan Manufaktur. Undergraduate thesis, Universitas Hayam Wuruk Perbanas.

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Abstract

One of the manufacturing companies, namely PT. Tri Banyan Tirta has closed and is no longer operating due to the global crisis and a decrease in orders, this has made PT. Tri Banyan Tirta suffered losses. The aims of this research is to determine the financial ratios in the Altman Z-Score, Springate S-Score, Grover G-Score models that can predict financial distress in manufacturing companies. The population in this study are manufacturing companies listed on the Indonesian Stock Exchange. The sampling method used a purposive sampling method, there were 151 companies with a total sample of 276 that met the criteria. The analysis technique used is logistic regression technique using SPSS 26. The results of this research show that: 1) The ratio in the Altman Z-Score model that can predict financial distress is the ratio of Earnings before interest and taxes to Total assets; 2) The ratios in the Grover G-Score model cannot predict; 3) The ratio in the Springate S-Score model that can predict financial distress is the ratio of Earnings before interest and taxes to Total assets; 4) The Altman model has an accuracy rate of 69.6%, the Grover model 68.5%, the Springate model 68.1%. So it can be concluded that the Altman model is the best predictive model in predicting financial distress for manufacturing companies listed on the IDX 2021-2022. Keywords : Financial distress, Altman Z-Score, Springate S-Score, and Grover G-Score

Item Type: Thesis (Undergraduate)
Subjects: 600 - TECHNOLOGY > 650 - 659 MANAGEMENT & PUBLIC RELATIONS > 657 - ACCOUNTING > 657.042 - FINANCIAL ACCOUNTING
Divisions: Bachelor of Accountancy
Depositing User: TASYA BONITA
Date Deposited: 08 Mar 2024 08:01
Last Modified: 08 Mar 2024 08:01
URI: http://eprints.perbanas.ac.id/id/eprint/12035

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