Evaluation of Indonesian Marine and Fishery Product Exports by Commodity and Destination Country
DOI:
https://doi.org/10.55123/sosmaniora.v5i2.7525Keywords:
Clustering, Commodities, DBI, Destination Countries, Fisheries Export, K-MeansAbstract
This study aims to evaluate the performance of Indonesia's marine and fisheries export sector based on product commodities and destination countries during the period of 2019–2023. Utilizing an unsupervised learning approach through the K-Means Clustering algorithm, export data were classified into three main groups according to export volume and value: high, medium, and low. The dataset was obtained from the official portal of the Indonesian Ministry of Marine Affairs and Fisheries (KKP), covering export statistics for key commodities such as shrimp, tuna, seaweed, and other captured fishery products exported to major destinations including the United States, China, Japan, and other countries. Preprocessing included data cleaning and normalization using StandardScaler to ensure data quality and consistency. Cluster validation was conducted using the Davies-Bouldin Index (DBI), where lower DBI values indicate better clustering performance. The results revealed consistent export trends for Indonesia’s flagship commodities while identifying new opportunities for market expansion. This study provides strategic insights for policymakers and industry stakeholders in designing export development strategies and diversifying international markets. Furthermore, it contributes a methodological framework for data-driven export mapping of fisheries products that is both comprehensive and sustainable.
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