Comparison of K-Medoids and K-Means Result for Regional Clustering of Capture Fisheries in Aceh Province

This research aims to develop a web-based application that can categorize areas of capture fisheries in Aceh Province. The methods used in this research are K-Means and K-Medoids. The methods used in this research are K-Means and K-Medoids, a clustering technique used to group districts/cities based on high and low catch areas. This application will use data from the Marine and Fisheries Service (KKP) of Aceh Province, covering the period 2017 to 2023. This research will analyze variables such as production (tons), number of vessels, sub-districts, villages, and fish species. The system is developed using the PHP programming language to facilitate implementation and data access by stakeholders. Stakeholders. As an evaluation tool for clustering results, the Davies-Bouldin Index (DBI) is used to measure the quality of clustering results. The results of this study are expected to provide an overview of areas with high catches and assist policymakers in designing a more strategic approach to fishing—policymakers in developing more effective strategies to increase fishing, especially in districts with low fish catch. In addition, this application also provides an interactive platform for users to analyze fisheries data quickly and efficiently.