Penerapan K-Nearest Neighbor Berbasis Genetic Algorithm Untuk Penentuan Pemberian Kredit
Abstract: 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.
Penulis: Ester Arisawati
Kode Jurnal: jptinformatikadd170398
