Application of the K-Means Method for Clustering Capture Fisheries Products in North Aceh with A Data Mining Approach

Abstract

North Aceh is one of the districts that has great potential in the maritime and fisheries sector, because part of the North Aceh region is a supplier of captured fisheries products. The problem with this research is that there is no model of a clustering system for captured fisheries products in North Aceh District, so it will be difficult to determine which areas produce superior and non-superior types of fish. This research aims to classify captured fishery results for the 2021-2022 period using the K-Means algorithm with a Data Mining approach to determine superior and non-superior fish types. Therefore, this research can help a little in providing information about the types of fish that are superior and not superior or the types of fish that are most numerous and the types of fish that appear the least at fishing ports in North Aceh District. The stages carried out in this research started from compiling research instruments and literature review, data collection and analysis, designing a clustering system model and implementing the system. This research produces 2 clusters, namely cluster 1 is superior fish and cluster 2 is non-superior fish. The K-Means algorithm with a Data Mining approach can be used to group types of capture fishery products at fishing ports in North Aceh District.