ANALISIS KOMPARATIF MODEL PREDIKSI FINANCIAL DISTRESS PADA PERUSAHAAN SUB-SEKTOR TEKSTIL DAN GARMEN YANG TERDAFTAR DI BURSA EFEK INDONESIA - M Indra Fauzi; Rahman Amrullah Suwaidi (JURNAL LENTERA BISNIS, 2025)
Financial distress is a condition in which a company experiences a decline in financial performance, marked by decreasing profits and even potential losses. This study aims to identify the most accurate model in predicting financial distress in the textile and garment sub-sector in Indonesia. This study uses secondary data, collected from the companies’ financial statements published on the Indonesia Stock Exchange website and the respective company websites. The population in this study includes textile and garment sub-sector companies listed on the Indonesia Stock Exchange for the period 2019–2023, totaling 23 issuers. The sample was selected using purposive sampling, resulting in 20 companies being used as the research sample. This study compares the scores of four financial distress prediction models using statistical techniques, and evaluates the models’ accuracy by considering both the level of accuracy and error rate. The results show that the Springate model is the most accurate prediction model, with an accuracy rate of 95% and an error rate of 5%. Therefore, companies—especially those in the textile and garment sub-sector listed on the Indonesia Stock Exchange—can use the Springate model to predict financial distress. The researcher suggests that future studies consider using other models such as Ohlson, Taffler, or Internal Growth to enrich perspectives.