PREDIKSI KEBANGKRUTAN BANK-BANK YANG TERDAFTAR DI BURSA EFEK INDONESIA - Farida Titik Kristanti (University of Merdeka Malang, 2014)
The purpose of this study was to investigate whether CAMELS ratios could be used to predict Bank bankruptcy.This study used seven ratios that represented CAMELS ratios. Logic regression Model used showedthat model fit and prediction accuracy was as much as 81.2%. It led us to the conclusion that the CAMELSratios could be used to predict bank bankruptcy. The research showed that only CAR (Capital) negatively andsignificantly influenced the prediction of Bank bankruptcy. The other variables, NPL (Asset quality), ROA(Management), NIM (Earnings), LDR (Liquidity), Price/Earning (Sensitivity) and size (Sensitivity) did nothave any significant influence to predict bank bankruptcy. This model also showed us that variability of anindependent variable could be explained by the dependent variability as much as 43.5%.