Mapping Indonesian potential fishing zone using hierarchical and non-hierarchical clustering

Abstract

Indonesia, a maritime nation whose ocean area exceeds its land area, has an abundance of ocean-based natural resources, such as fish, seaweed, coral reefs, and other marine organisms. The fisheries industry is one of the potential sources of extraordinary marine resources for the Indonesian economy. The annual increase or decrease in fish production in Indonesia can be attributed to several factors, including natural influences such as climate and ocean waves, inadequate management of marine resources, unequal distribution of facilities to support increased fish production in Indonesia, and the characteristics of areas that have a significant impact on the resulting fish production. Consequently, the objective of this research is to classify provinces in Indonesia using clustering analysis so that government policy programs can be more focused and directed according to the characteristics of the clusters formed. The application of cluster analysis was based on the development of fish production data for each province in Indonesia from 2017 to 2019 obtained from the website of the Central Statistics Agency (BPS). Clustering analysis using hierarchical and non-hierarchical methods produces a dendrogram using the average linkage DTW hierarchical method, indicating the formation of two optimal clusters. Non-hierarchical clustering with two clusters produces the same distribution of province members as group members in hierarchical clustering. The average silhouette coefficient value for the two clusters formed was 0.64, indicating that the clustering is classified as Good Classification.