Article Per Year (5 Year)
p-Index From 2020 - 2025
0.778
P-Index
This Author published in this journals
All Journal Sistemasi: Jurnal Sistem Informasi HIGIENE: Jurnal Kesehatan Lingkungan Indonesian Journal of Artificial Intelligence and Data Mining Media Jurnal Informatika Jurnal Akuntansi, Ekonomi dan Manajemen Bisnis
Indriyanti Indriyanti
Unknown Affiliation
Computer Science & IT Economics, Econometrics & Finance Electrical & Electronics Engineering Environmental Science Public Health Other

Published : 5 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Indonesian Journal of Artificial Intelligence and Data Mining

 1 
Classifications Using Artificial Neural Network Method In Protecting Credit Fitness Elin Panca Saputra; Indriyanti Indriyanti; Supriatiningsih Supriatiningsih
Indonesian Journal of Artificial Intelligence and Data Mining Vol 3, No 1 (2020): March 2020
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v3i1.9442

Abstract

Classification is information that has the closest relationship with data, we make a prediction in providing customer eligibility to get a loan from a financial service institution. In this study, we use the Artificial Neural Network (NN) method in combination with the Particle Swarm Optimization method. It is known that the method has excellent generalizations to solve a problem in increasing accuracy. However, some of the attributes in the data can reduce accuracy and increase the complexity of the Artificial Neural Network (ANN) algorithm. Therefore, attribute selection is very necessary, the attribute selection method used in this study is the Particle swarm optimization (PSO) method. This method can be used for proper attribute selection in determining lending to customers, therefore the Particle Swarm Optimization (PSO) method can increase the value of higher accuracy weights in determining attribute selection.
Co-Authors Emmi Bujawati Erni Ermawati Erni Ernawati Fatah, Haerul Merintan Berliana Simbolon Nurul Ichsan Panca Saputra, Elin Sitti Raodhah Supriatiningsih Supriatiningsih Tri Wahyuni Tri Wahyuni