Perbandingan Tingkat Akurasi Model Prediksi Financial Distress pada Perusahaan Sektor Property dan Real Estate - Linda Ariany Mahastanti; Astri Dian Utami (AFRE (Accounting and Financial Review), 2022)
This study aims to find the most accurate financial distress prediction model for use in the property and real estate sectors listed on the Indonesia Stock Exchange. The financial distress prediction models used in this study are the Altman model, the Springate model, the Zmijewski model, and the Grover model. The population in this study amounted to 79 of property and real estate sector companies listed on the IDX. There are 28 companies in this study that were used as research samples with a total of 112 observations for 4 periods. The sampling process used a purposive sampling technique. The data analysis method used is a different test using McNemar Test on SPSS version 26, the data from the model predictions are compares with sample category 1 (financial distress) and category 0 (non-financial distress). This study also uses robustness check to test the robustness of the first prediction results. The results showed that Grover model was the most accurate predictive model with an accuracy rate of 88 percent, then the Altman model at 76,8 percent, the Springate model at 55,3 percent, and the Zmijewski model at 68 percent.