Classification Of Indonesian Frozen Shrimp Export Data Using K-Medoids Clustering

Authors

  • Ekka Pujo Ariesanto Akhmad Universitas Hang Tuah, Surabaya
  • Budi Priyono Universitas Hang Tuah, Surabaya

DOI:

https://doi.org/10.57185/jetbis.v3i5.106

Keywords:

Machine Learning, Frozen Shrimp Export, K-Medoids Clustering

Abstract

Indonesia is one of the countries exporting caught, cultivated, and frozen shrimp to both developed and developing countries. Previously, the frozen shrimp export data was categorized based on the countries it was exported to. However, the list of frozen shrimp exports did not include the export levels. This research aims to explore the application of machine learning to analyze the frozen shrimp export data from the main destination countries using the K-Medoids cluster. The data for this research was sourced from the Bulletin of Foreign Trade Export Statistics documents by Product Group and Country, January 2023. The data used in this study covers the period from 2022 to 2023 and includes research variables such as net weight of goods (in tons) and FOB value (free on board). The cluster analysis revealed the formation of two clusters: one with high export levels and another with medium and low export levels.

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Published

2024-06-07