Open AccessSISTEM SEDERHANA UNTUK MEMPREDIKSI RISIKO PEMBERIAN KREDIT
Author(s) -
D Lusiyanti,
N Nacong
Publication year - 2018
Publication title -
jurnal ilmiah matematika dan terapan/jurnal ilmiah matematika dan terapan
Language(s) - English
Resource type - Journals
eISSN - 2540-766X
pISSN - 1829-8133
DOI - 10.22487/2540766x.2018.v15.i2.11360
Subject(s) - business , actuarial science , decision maker , finance , credit risk , institution , economics , management science , political science , law
Credit risk prediction is very beneficial for the bank or financing institution in making credit decisions. In the decisionmaking, a decision maker in a banking must be able to take the right decision to accept or reject the credit application. If the decision maker is right in making a decision, then the bank will get customers who support the health and sustainability of the banking business, and vice versa. In this study, Support Vector Machien (SVM) is implemented to predict the crediting risk. The data used is data obtained from one of the financing institutions. By using different activation functions, 80.9524% accuracy is obtained or there are 51 precisely predictable data from 63 existing data