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All Journal ILKOM Jurnal Ilmiah
Muhammad Nurfahmi
Universitas Malikussaleh
Computer Science & IT

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K-means algorithm for clustering system of plant seeds specialization areas in east Aceh Rozzi Kesuma Dinata; Novia Hasdyna; Sujacka Retno; Muhammad Nurfahmi
ILKOM Jurnal Ilmiah Vol 13, No 3 (2021)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v13i3.863.235-243

Abstract

The number of regions and types of plants in East Aceh Regency requires a data clustering process in order to easily find out which areas are most in-demand based on the type of plants. This study applies the k-means algorithm to classify the data. The data used in this study were obtained from the Department of Agriculture, Food Crops and Horticulture, East Aceh Regency. Based on the test results with k-means, the average number of iterations in the 2015-2019 data is 8,7,6,4,3 iterations for each commodity. The test results can show areas of interest for plant seeds with clusters of high demand, attractive, and less desirable. The system in this study was built based on the web using the PHP programming language.
Co-Authors Novia Hasdyna Rozzi Kesuma Dinata Sujacka Retno