CLUSTERING SHRIMP DISTRIBUTION IN INDONESIA USING THE X-MEANS CLUSTERING ALGORITHM - Fadhilah, Rahmi; Matdoan, M. Y.; Safira, Dinda Ayu; Tahalea, Sylvert Prian (Statistics Study Programme, Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Pattimura, 2024)
Shrimp is one of the marine biological resources available in almost all Indonesian waters and is one of the mainstay export commodities from the fisheries sub-sector. This is expected to improve the welfare of the community, so it is necessary to cluster the distribution of shrimp in Indonesia. Clustering is a data mining technique used to group data or partition datasets into subsets. One of the best clustering algorithms is X-means. X-means clustering is used to solve one of the main disadvantages of K-means clustering, namely the need for prior knowledge of the number of clusters (K). The purpose of this research is to obtain the results of clustering the distribution of shrimp in Indonesia using the X-means clustering algorithm. The data used in this study comes from the publication of Marine and Coastal Resources Statistics 2022 by the Central Bureau of Statistics of the Republic of Indonesia. This study obtained the results that there are 3 clusters in the clusterization of shrimp distribution in Indonesia. Cluster 0 consists of 1 province, cluster 1 consists of 27 provinces, and cluster 2 consists of 6 provinces.