The Effect of Capital Structure, Sales Growth, Firm Size, and Operational Efficiency on Financial Performance in Property and Real Estate Companies Listed on the Indonesia Stock Exchange for the Period 2021–2025

Dina Rahayu; Ima Andriyani; Veny Mayasari; Mariyam Zanariah

doi:10.61536/escalate.v4i02.634

Authors

Dina Rahayu Study Program of Management, Faculty of Economics and Business, Universitas Tridinanti
Ima Andriyani Study Program of Management, Faculty of Economics and Business, Universitas Tridinanti
Veny Mayasari Study Program of Management, Faculty of Economics and Business, Universitas Tridinanti
Mariyam Zanariah Study Program of Management, Faculty of Economics and Business, Universitas Tridinanti

DOI:

https://doi.org/10.61536/escalate.v4i02.634

Keywords:

Capital Structure, Sales Growth, Firm Size, Operational Efficiency, Financial Performance, Property and Real Estate

Abstract

Financial distress is a condition that needs to be detected early because it can increase the risk of delisting and reduce investor confidence. This study aims to analyze the financial distress conditions of raw materials companies at risk of delisting on the Indonesia Stock Exchange and compare the accuracy levels of the Altman Z-Score, Zmijewski, and Springate methods. This study uses a quantitative approach with descriptive methods. The study population consisted of 13 raw materials companies with the potential for delisting, while the sample was determined using a purposive sampling technique, resulting in five companies for the 2020–2024 period. The research data consisted of secondary financial reports collected through documentation techniques and literature studies. Data analysis was performed using the Altman Z-Score, Zmijewski, and Springate models, along with calculations of accuracy and error type. The results show that the three methods produced different financial distress classifications. The average accuracy rates were 80% for Altman Z-Score, 76% for Zmijewski, and 60% for Springate, with corresponding average error rates of 20%, 24%, and 40%. These findings indicate differences in the classification results and accuracy levels among the three methods in assessing financial distress

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