Prediksi Financial Distress Perusahaan Properti dan Real Estate di Bursa Efek Indonesia Periode 2019-2023 - Arifana, Cindy Dwi; Handayani, Anita (Entrepreneur: Jurnal Bisnis Manajemen dan Kewirausahaan, 2025)
This study aims to analyze the ability of four prediction models Altman, Springate, Zmijewski, and Grover in predicting financial distress in property and real estate companies. This study uses a descriptive quantitative method with a research population of property and real estate companies listed on the Indonesia Stock Exchange. Sampling was done using purposive sampling from the period 2019-2023, and 29 companies were obtained. The data analysis technique was carried out using descriptive techniques, including the calculation of four prediction models, namely Altman, Springate, Zmijewski, and Grover, and the ranking of prediction models. The results of the study show that the Springate Model is the most accurate model with an accuracy level of 93% in predicting financial distress in property and real estate companies on the Indonesia Stock Exchange. This model is proven to be more effective than the Altman, Grover, and Zmijewski models. Further research can be expanded with larger periods, samples, and macroeconomic factors.