Perancangan Sistem Model Penentu Pemberian Pinjaman Koperasi Karyawan Permata Bank Menggunakan SVM - Purwanti Purwanti; Tuti Handayani (STRING (Satuan Tulisan Riset dan Inovasi Teknologi), 2017)
Currently,a loan is one of profitable business with a high risk. Many classification methods have been suggested in the literature to overcome this problem. But most are not accepted by experts for various reasons. Therefore,it is necessary to identify and distinguish between good and bad members so that the interested parties can take anactionto prevent nonperforming loans. This study usesSupport Vector Machine (SVM)Model to process the data on cooperative loan members either those in trouble with the installment payment or not. The result of the test by measuring the performance of the algorithm using the test method confusio matrix and ROC curves shows that the Support Vector Machine algorithm has high accuracy. In conclusion, it can be applied to determine the feasibility of a cooperative loan.