Open AccessPenerapan K-Nearest Neighbor Berbasis Genetic Algorithm Untuk Penentuan Pemberian Kredit
Author(s) -
Ester Arisawati
Publication year - 2017
Publication title -
j-sakti (jurnal sains komputer dan informatika)
Language(s) - English
Resource type - Journals
eISSN - 2549-7200
pISSN - 2548-9771
DOI - 10.30645/j-sakti.v1i1.24
Subject(s) - k nearest neighbors algorithm , factoring , confusion matrix , genetic algorithm , algorithm , payment , finance , credit card , business , computer science , fast moving consumer goods , actuarial science , machine learning , marketing
Consumer financing is financing activities for the procurement of goods based on the needs of consumers with payment in installments. While the Financing Company is a business entity specifically set up to conduct leasing, factoring, consumer finance, or business credit card. The finance company will approve the proposed consumer credit after a credit analysis of the feasibility of providing consumer financing, if approved and not disetujui.Dalam analysis process for consumers, there are some that are not accurate, therefore consumers can not afford to pay in a timely manner resulting in bad debts , To solve the problem we need a model that is able to classify and predict consumer data is problematic and not problematic. In this research, testing ie k-Nearest Neighbor and k-Nearest Neighbor optimized genetic algorithm is applied to the data consumer that gets better the consumer credit financing is problematic or not. From the test results by measuring the performance of the three algorithms using Cross Validation testing methods, Confusion Matrix and ROC curves, it is known that the k-Nearest Neighbor algorithm optimized Genetic Algorithm has the AUC value and highest accuracy.