ANALISIS MODEL RGEC DALAM MEMPREDIKSI FINANCIAL DISTRESS PADA BANK PEMERINTAH DAERAH DI INDONESIA
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Institusion
Sekolah Tinggi Ilmu Ekonomi Perbanas Surabaya
Author
EFENDI, FEBRIAN FREDIKA
Subject
657.9 - ACCOUNTING-BANK
Datestamp
2017-07-05 04:12:27
Abstract :
RGEC models used to predict the bank's financial distress prior to the bankruptcy. But few are predicting financial distress of local government bank (BPD). This study investigated the analytical models to predict financial distress RGEC in local government bank in Indonesia 2011-2014. Factors tested in this study is the change in the median value of equity, net interest margin and return on assets. Variables used in this study consists of NPL, LDR, GCG, ROA, NIM and CAR. The sample consists of 26 local government bank (BPD) in Indonesia 2011-2014, obtained by purposive sampling and after using a variety of criteria selected only the remaining 18 banks. The data analysis technique used is logistic regression. Results showed that of all the ratios used only NPL and NIM are significant and can be used to predict financial distress because of the significance level below 0.05 (5%). LDR side, GCG, ROA and CAR can not be used to predict financial distress due to the significance level above 0.05 (5%). Keywords: RGEC, financial distress and logistic regression
RGEC models used to predict the bank's financial distress prior to the bankruptcy. But few are predicting financial distress of local government bank (BPD). This study investigated the analytical models to predict financial distress RGEC in local government bank in Indonesia 2011-2014. Factors tested in this study is the change in the median value of equity, net interest margin and return on assets. Variables used in this study consists of NPL, LDR, GCG, ROA, NIM and CAR. The sample consists of 26 local government bank (BPD) in Indonesia 2011-2014, obtained by purposive sampling and after using a variety of criteria selected only the remaining 18 banks. The data analysis technique used is logistic regression. Results showed that of all the ratios used only NPL and NIM are significant and can be used to predict financial distress because of the significance level below 0.05 (5%). LDR side, GCG, ROA and CAR can not be used to predict financial distress due to the significance level above 0.05 (5%). Keywords: RGEC, financial distress and logistic regression
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