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Elin Darnela
Universitas Sriwijaya
Computer Science & IT

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Initial Centroid Determination Using Simulated Annealing Algorithm Osvari Arsalan; Rizki Kurniati; Elin Darnela
Generic Vol 13 No 1 (2021): Vol 12, No 1 (2021)
Publisher : Fakultas Ilmu Komputer, Universitas Sriwijaya

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Abstract

Initial randomly generated centroids are commonly used in k-Means clustering method. Random initial centroids k-Means to be trapped in optimum local solution which results in sub-optimal cluster quality. This study examines Simulated Annealing algorithm in determining initial centroids on k-Means. Each k-Means clustering will be tested on result of reduction and without dimension reduction. Based on the results evaluation of k-Means clustering results with initial centroid Simulated Annealing algorithm improve quality cluster with percentage change value 21.2% in the high dimensional data and 25.1% in the dimension reduction data, this shows that initial centroid calculated Simulated Annealing algorithm is able to obtain the best cluster with significant results.
Co-Authors Osvari Arsalan Rizki Kurniati