| dc.description.abstract | The performance of conventional commercial banks can be determined from several
parameters included in the RGEC analysis (Risk Profile, Good Corporate
Governance, Earnings, Capital). This is done to help all parties such as customers,
shareholders, and regulators understand the extent of the bank's stability, health and
capability in dealing with various economic situations. In addition, this analysis also
supports investment decision making, banking sector supervision and maintaining
public confidence in the banking industry. Indicators in the RGEC analysis used
include Capital Adequacy Ratio (CAR), Return on Assets (ROA), Net Interest Margin
(NIM), Non-Performing Loan (NPL), Loan to Deposit Ratio (LDR), Operating Costs
to Operating Income (BOPO), NPL Level, ROA Level and Bank Rating according to
the Indonesian Securities Rating Agency (PEFINDO). The decision tree method used
in this comparative analysis is QUEST (Quick, Unbiased, Efficient, and Statistical
Tree) which will produce a binary classification tree and CHAID (Chi-squared
Automatic Interaction Detection) which will produce a non binary classification tree.
The results showed that QUEST produces indicators of BOPO, ROA, NPL and Bank
Rating while CHAID produces indicators of NPL, ROA, LDR, and BOPO as the most
significant indicators in predicting the performance of conventional commercial
banks. The results of the indicator analysis produced by the two decision tree methods
will be compared and analyzed in detail using the confusion matrix. | en_US |
