Analisis Prediksi Financial distress Menggunakan Model Altman Z-Score dan Springate pada Perusahaan Sub Sektor Pertambangan Batubara yang Terdaftar di BEI 2017-2022 - Feliana Danisha Cucu Ariyani; Ahmad Jarnuzi; Nur Indah Riwajanti (Dinamika Publik: Jurnal Manajemen dan Administrasi Bisnis, 2023)
This research was conducted by analyzing and comparing the level of accuracy for predicting bankruptcy (financial distress) through the Altman Z-Score and Springate models for companies. This study uses a data source for the annual financial statements of coal mining sub-sector companies listed on the IDX for the 2017-2022 period as secondary data. The research sample using purposive sampling was obtained by 11 samples. Testing the data using quantitative analysis techniques using the SPSS 26 program. The results of the research on the Altman Z-Score model found 3 companies with bankruptcy conditions and 2 companies with gray zone conditions. Meanwhile, in the Springate model, 4 companies went bankrupt. The results of the research test are that there is a significant difference in predicting bankruptcy conditions using the two prediction models. The accuracy level of the Springate model has a greater percentage than the Altman Z-Score model. Both models produce the same type I error percentage rate, while the type II error percentage rate in the Springate model is higher than the Altman Z-Score model. So, every company needs to predict bankruptcy every year and can be used as an early warning of the company's financial condition.