Agista, Hanna Mutia and Budiarto, Eka and Mahawan, Bagus (2019) Early Detection of Bank Under Special Surveillance Status Through Analysis of Financial Ratios and Bank Shareholders Ratios Using Data Mining for Rural Banks. Masters thesis, Swiss German University.

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Abstract

This study aims to determine the effect of 8 bank financial ratios such as BOPO (operational efficiency ratio), CAR (Capital Adequacy Ratio), NPL (Non Performing Loan), ROA (Return On Assets), CR (Cash Ratio), KAP (quality of productive assets), PPAP (provision for loan losses) and LDR (Loan Deposit Ratio) and another ratio, namely Bank‟s Shareholder ratio towards bank predictions whether a rural bank will be declared as bank under special surveillance or not. Bank under special surveillance status is the bank's status before being declared as a failed bank. Eight financial ratios and another ratio that comparing BOD and BOC to Bank's Shareholders can be obtained from quarterly rural bank‟s financial reports that have been published on the IFSA website during 2014-2017. The data in this research is approximately 1000 rural banks. The method to predict rural bank become bank under special surveillance is data mining. Before the data mining process, the 9 parameters used will be simplified into 5 parameters using the PCA (Principal Component Analysis). The PCA result shows that these 5 parameters are all the components that we need to consider because they are sufficient to explain 97% of the variance. The new dataset formed from PCA with these 5 parameters as attributes was then analyzed with the data mining process. The data mining process was done using one of the data mining tools called Rapidminer. Data mining method used are KNN and Naïve Bayes, both are classification method.

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	Data Mining ; Cross Validation ; PCA ; KNN ; Naïve Bayes
Subjects:	H Social Sciences > HG Finance > HG1501-3550 Banking T Technology > T Technology (General) > T58.6 Management information systems
Divisions:	Faculty of Engineering and Information Technology > Department of Information Technology
Depositing User:	Adityatama Ratangga
Date Deposited:	19 May 2020 04:23
Last Modified:	20 May 2020 03:35
URI:	http://repository.sgu.ac.id/id/eprint/496

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