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ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI NON PERFORMING LOAN (Studi pada Bank Umum Konvensional yang Go Public di Indonesia periode 2008-2012)


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Abstract

Conventional commercial bank is vulnerable hit by Non Performing Loans (NPL) because
credit as the main source of income comes from a conventional bank and the risk that might occur
should be handled without involving the customer. Although the bank’s management had made
efforts based on the credit rating of 5C+1C but still the banks potentially exposed tho tb he credit
risk. The purpose of this research was to know how big the influence of variable CAR, LDR, SIZE,
KAP and BOPO, against Non Performing Loan (NPL) in a banking company that listed on BEI.
The population in this research are 121 banks in Indonesia period 2008-2012. The
sampling technique used was purposive sampling on criteria: (1) conventional commercial banks
listed on BEI period 2008-2012, and (2) conventional commercial banks in their financial reports
contained the required data in the research period 2008-2012. The data is obtained from annual
report of each bank period 2008-2012. This sample gained amount of 23 banks from 121 banks
public listed in Indonesia. Analytical techniques used was multiple linear regression and
hypothesis test using t-statisctic to examine partial regression with level of significance 0,05.
Before tested with a multiple linear regression test, testified with classical assumptions test first.
The results showed that there were no deviations from the classical assumption. Those
things indicate the data which avaible in this study has been qualified for use in linear regression
model. From the analysis shows that in partially CAR haven’t significant negative effect on NPL
and LDR haven’t significant positive affect on NPL, while SIZE, KAP and BOPO have positively
and significantly effect on NPL. The result of regression estimation show the ability of model
prediction is 35% while the remaining 65% influenced by other factors outside the model that has
not been includeed in the study.

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Keywords: CAR, LDR, SIZE, KAP, BOPO, NPL, multiple linear regression

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