Support Vector Machine

PENERAPAN METODE SVM UNTUK KLASIFIKASI  RESIKO KREDIT KEPEMILIKAN  
KENDARAAN (MOTOR) 

Abstract—Given Credit Risk in a lease is always there  , So  credit analysis should be done carefully .  if Consumer troubled in paying installment  payments  ,  so  would  be  detrimental  to  the  lease. Therefore, quantitative  and  qualitative  Credit  analyzing  will provide  clarity  for  decision makers  .To  achieve  this  goal,  credit preparations  should  be  done  by  collecting  information  and  data. The quality of   the result of the analysis depends on the quality of Human resources, the data, and analysis techniques . In this research  discussed  regarding the application using support vector machine  (  SVM  ) method  for  determination  of  the  Credit Risk of  Motor  Vehicle  ownership  .  The resulting model  is  then evaluated its performance by calculating accuracy model prediction using  Confusion  Matrix  and  ROC  curve,  obtained  9.78  % accuracy value and AUC value is 0.894. The classification is Good Enough because have  AUC values between from 0.8 to 0.9.

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Jurnal Sistem Informasi :oleh LPPM STMIK Antar Bangsa  (ISSN 2089-8711) Vol.IV No. 1, Februari 2015