Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Vol 2 No 12 (2018): Desember 2018

Penerapan Algoritme Particle Swarm Optimization-Learning Vector Quantization (PSO-LVQ) Pada Klasifikasi Data Iris

Ilham Romadhona (Fakultas Ilmu Komputer, Universitas Brawijaya)
Imam Cholisoddin (Fakultas Ilmu Komputer, Universitas Brawijaya)
Marji Marji (Fakultas Ilmu Komputer, Universitas Brawijaya)

Article Info

Publish Date
07 Aug 2018

Abstract

Currently Iris flowers are easily found in around the world with various species. In Greek Iris mean the goddess of the rainbow because Iris species has reached 260 to 300 various species with colorful and light flowers. Because of the large number of Iris species, it is necessary to classify the Iris species. To solve the problem, used the Learning Vector Quantization (LVQ) algorithm which will be optimization using the Particle Swarm Optimization (PSO) algorithm was used to classify species into Sentosa Iris, Virginica Iris and Versicolor Iris category where the species previously recorded on Iris dataset. Then the result of this study was compared with the classification using LVQ algorithm. The average accuracy obtained with PSO-LVQ algorithm is 93.334%, whereas the average accuracy with LVQ algorithm is 84.268%. The differece in accuracy is 9.066% it is mean PSO-LVQ algorithm give more a good provides result than LVQ algorithm.

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Journal Info
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Website

Abbrev

j-ptiik

Publisher

Universitas Brawijaya

Subject

Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

Description

Jurnal Pengembangan Teknlogi Informasi dan Ilmu Komputer (J-PTIIK) Universitas Brawijaya merupakan jurnal keilmuan dibidang komputer yang memuat tulisan ilmiah hasil dari penelitian mahasiswa-mahasiswa Fakultas Ilmu Komputer Universitas Brawijaya. Jurnal ini diharapkan dapat mengembangkan penelitian ...