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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Ilham Romadhona
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Penerapan Algoritme Particle Swarm Optimization-Learning Vector Quantization (PSO-LVQ) Pada Klasifikasi Data Iris Ilham Romadhona; Imam Cholisoddin; Marji Marji
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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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.
Co-Authors Imam Cholisoddin Marji Marji