ACCURACY OF SPRINGATE, ZMIJEWSKY AND GROVER AS LOGISTIC MODELS IN FINDING FINANCIAL DIFFICULTY OF FINANCING COMPANIES - Munawarah Munawarah; Keumala Hayati (Sekolah Tinggi Ilmu Ekonomi Sutaatmadja, 2019)
This study aims to determine both the Springate model, Grover and Zmijewski able to predict the condition of financial distress in finance companies listed on the Indonesia Stock Exchange. And of the three models can be known which model is the most accurate in predicting financial distress. The population in this study are companies in the financing sector listed on the Indonesia Stock Exchange in the period 2013 to 2017 as many as 17 companies. By using purposive sampling technique, a total sample of 85 financing companies was obtained. The data used are secondary data sourced from the company's annual financial reports. The analysis model used is logistic regression. Simultaneously, all predictive models for Springate, Zmijewski, and Grover affect the probability of financial distress. While partially only Zmijewski can influence the prediction of financial distress conditions in Financing sub-sector companies listed on the Indonesia Stock Exchange. Nagelkerqe Square value shows 0.606 meaning that only 60.6% variation of the accuracy of these three models in predicting financial distress conditions of finance companies. While the remaining 39.4% can be explained by other models not examined in this study