Munich Personal RePEc Archive

MODEL PREDIKSI FINANCIAL DISTRESS DENGAN BINARY LOGIT (STUDI KASUS EMITEN JAKARTA ISLAMIC INDEX)

Iskandar, Azwar (2015): MODEL PREDIKSI FINANCIAL DISTRESS DENGAN BINARY LOGIT (STUDI KASUS EMITEN JAKARTA ISLAMIC INDEX). Published in: Jurnal BPPK (Badan Pendidikan dan Pelatihan Keuangan) Vol. 8 No. 1/2015 – ISSN 2085-3785 , Vol. 8, No. Kementerian Keuangan RI (Ministry of Finance) (1 June 2015): pp. 21-40.

[img]
Preview
PDF
MPRA_paper_82694.pdf

Download (1MB) | Preview

Abstract

The purposes of this research were to analyze: (i) financial ratios choosen as predictor for financial distress prediction; (ii) accuration rate of prediction model that formed from analysis. The data used was from resume of financial report of companies at Indonesia Stock Exchange period of 2012-2013. This research used 23 companies of JII as samples with purposive sampling method. This research used binary logit regression analysis. The empirical result shown that the financial ratios such as Current Ratio (CR), Operating Profit Margin (OPM), Return Of Asset (ROA), Return On Equity (ROE) and yield (YLD) can be used for comparing and classifying companies to distress and non-distress group. The financial ratios such as ROA and ROE significantly can be used in predition model with accuration rate of 90,9%. That model also can be used as early warning signal. For regulators such as BEI and Otoritas Jasa Keuangan can use it as tool for evaluating, reviewing and controlling of companies.

UB_LMU-Logo
MPRA is a RePEc service hosted by
the Munich University Library in Germany.