Penggunaan Binary Logit untuk Prediksi Financial Distress Perusahaan Yang Tercatat Di Bursa Efek Jakarta

This study aimed to establish the financial distress prediction in a public company listed on the Jakarta Stock Exchange specifically incorporated in the trading industry. The samples used in research are all public companies incorporated in the trading industry 2002-2006 period. This study used six initial discriminator and 34 financial ratios as an operational variable. The analysis technique used is a binary logit regression. Empirical result shows that companies that do not create economic value-added, illiquid, low operational efficiency and high levels of financial leverage have a large probability of financial distress.