PENGEMBANGAN MODEL DETEKSI DINI KESULITAN KEUANGAN PERUSAHAAN (Studi Empiris Perusahaan Manufaktur Go Publik di Bursa Efek Indonesia)

Abstract

This paper performs an empirical investigation possibility of financial distress using the manufacture companies listed on the Indonesia Stock Exchange (BEI). The research relies on a sample of 130 financial distress and 419 non financial distress over 2003 - 2007 period, which include a period economy recovery and an economy crisis. The two well-know methods, logistic regression by stepwise and discriminant analysis. The models are found to have high classification power and predictive accuracy, over one years prior to financial distress. In this research logistic regression and discriminant models identify the same variables of significant predictor. The variables identifies NITA, WCTA, and EQTA. Net income/total assets (NITA) is the most important predictor of financial distress in both models. This can serve to make the methods important decision tools for managers and investors. Limitations of this research are contain industry bias and financial statement validity. This research may be extended to eliminate limitation by specific industry (e.g. banking industries).