Mapping System Model and Clustering of Fishery Products using K-Means Algorithm with Web GIS Approach

Authors

  • Nurdin Department of Information Technology, Universitas Malikussaleh, Lhokseumawe, Aceh, Indonesia
  • Taufiq Department of Electrical Engineering, Universitas Malikussaleh, Lhokseumawe, Aceh, Indonesia
  • Fajriana Department of Mathematics Education, Universitas Malikussaleh, Lhokseumawe, Aceh, Indonesia
  • Muhammad Zia Ulhaq Student Department of Information Technology, Universitas Malikussaleh, Lhokseumawe, Aceh, Indonesia

Keywords:

K-Means Algorithms, Web GIS, Fisheries Products, Mapping and Clustering Models, Implementation and Testing.

Abstract

Aceh is a province that is rich in fishery product resources, however, there are several districts/cities experiencing a shortage of fishery product supplies. Therefore, a model of fishery product mapping and clustering system is needed with the Web Geographic Information System (GIS) approach. This study aims to develop an information system model for mapping and clustering capture fisheries products from 10 fishing ports located on the north coast of Aceh Indonesia. The method used for clustering uses the K-Means algorithm and its mapping using the GIS web. The variables used in the fishery product type clustering system consist of catch weight, fish price, number of fishing ports and number of months to determine fish season. This research resulted in the output of 2 clusters, namely cluster 1 is a superior fish and cluster 2 is an ordinary fish. This K-Means algorithm can be used for clustering types of fishery products, while Web GIS can be applied to mapping fishing ports on the north coast of Aceh Indonesia. This system model is a combination of data mining and a website that is visualized in the form of a GIS. The contribution of this research is to help the community and the fisheries service to obtain information on types of fishery products (high-quality fish and common fish species) every month at fishing ports and information about their selling prices.

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Published

16.07.2023

How to Cite

Nurdin, Taufiq, Fajriana, & Ulhaq, M. Z. . (2023). Mapping System Model and Clustering of Fishery Products using K-Means Algorithm with Web GIS Approach . International Journal of Intelligent Systems and Applications in Engineering, 11(3), 738–749. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/3280

Issue

Vol. 11 No. 3 (2023)

Section

Research Article

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