Article Per Year (5 Year)
p-Index From 2019 - 2024
0
P-Index
This Author published in this journals
All Journal Teknik dan Ilmu Komputer
Kholis, Ikhwannul
Universitas 17 Agustus 1945 – Jakarta
Computer Science & IT

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Paramenter Variation Analysis of Learning Vector Quantization Artificial Neural Network For Odor Data Pattern Recognition Kholis, Ikhwannul
Teknik dan Ilmu Komputer vol. 05 no. 17 januari-maret 2016
Publisher : Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Abstrak Pengenalan pola data odor dapat dilakukan dengan menggunakan metode Learning Vector Quantization (LVQ) Artificial Neural Network (ANN). ANN dibuat menyerupai sistem syaraf manusia, disebut juga Jaringan Syaraf Tiruan (JST). Dengan beberapa parameter pada LVQ, dapat diketahui karakteristik LVQ sehingga dapat memperkecil error dan epoch, serta memperbesar Recognition Rate. Hasil percobaan menunjukkan hubungan antara parameter alpha, konstanta laju pembelajaran, jumlah epoch, dan inisialisasi vector pewakil terhadap error dan Recognition Rate yang diperoleh. Kata Kunci: ANN, Learning Vector Quantization, epoch, error, JST, Recognition Rate.Abstract Pattern recognition of odor data can be done by using Learning Vector Quantization Artificial Neural Network (ANN). ANN is made to resemble the human neural system. By varying some parameters on Learning Vector Quantization, Learning Vector Quantization characteristics can be identified to minimize errors and epoch and to enlarge Recognition Rate. The experimental results showed the relationship between the alpha parameter, coefficient alpha, the number of epoch, and vector initialization against error and the Recognition Rate obtained. Keywords: ANN, Learning Vector Quantization, epoch, error, JST, Recognition Rate. 
Co-Authors