ANALISIS DISKRIMINAN FISHER POPULASI GANDA UNTUK KLASIFIKASI NASABAH KREDIT

MAHARUNTI, UNGU SIWI (2016) ANALISIS DISKRIMINAN FISHER POPULASI GANDA UNTUK KLASIFIKASI NASABAH KREDIT. Undergraduate thesis, Fakultas Sains dan Matematika.

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Abstract

Credit is the biggest asset carried out by a bank and become the most dominant contributor to the bank income. However, the activity to distribute the credit takes a risk which can influence health and continuance of bank business. The credit risk which potentially occurs can be measured and controlled by analyzing directly whichever the credit client categorized to. The credit risk categorized to current credit, in specific concern credit, less current credit, doubtful credit and bad credit based on Bank Indonesia Regulation No.: 7/2/PBI/2005. The independent variables used in this research are nominal credit, principal balance, in time being bank client, time period, and bank interest. Fisher multiple discriminant analysis is a method whose assumption equality of covariance matrices. The result from using the Fisher multiple discriminant analysis in data of credit client from bank “X” in Pati shows that variable principal balance, in time being bank client, time period, and bank interest significant to measure credit risk. The classification using the Fisher multiple discriminant analysis in data of credit client from bank “X” in Pati gives the accurate 64,33%. Keywords: credit, classification, fisher multiple discriminant analysis

Item Type:Thesis (Undergraduate)
Subjects:H Social Sciences > HA Statistics
Divisions:Faculty of Science and Mathematics > Department of Statistics
ID Code:55022
Deposited By:Mr Hasbi Yasin
Deposited On:25 Jul 2017 09:31
Last Modified:25 Jul 2017 09:31

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