Conventional banks are vulnerable to non-performing loans, because the credit is the main source income of a bank. Credit risk may still occur, even though the bank's management has made efforts based credit rating 5C. The purpose of this study was to determine how much influence the variable CAR, LAR, NIM, and ROE against Non-Performing Loans (NPL) in the banking companies listed on BEI. The sampling technique used is purposive sampling with criteria: (1) a conventional commercial bank listed on the BEI 2009-2013 period, (2) the bank that issued the annual financial statements in a row in the period from 2009 to 2013, and (3) bank which has a data completeness NPL, CAR, LAR, NIM, and ROE in the period 2009-2013. Data obtained from the annual report of each bank in 2009-2013. There are a total sample of 29 banks. The analysis technique used is multiple linear regression and hypothesis testing using t-statistic to test the partial regression coefficient and F-statistic to test the effect simultaneously with a significance level of 0.05. Before being tested by multiple linear regression, first performed classical assumption of normality test data. The results showed that there were no deviations from the classical assumption test. This indicates that the available data is normal or eligible to be used as a multiple linear regression model. From the analysis, CAR and ROE have significant negative effect on the NPL and LAR have not significant negative effect on the NPL, while variable NIM have significant positive effect on the NPL.
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