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All Journal Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika)
Nur Arminarahmah
Universitas Islam Kalimantan Muhammad Arsyad Al Banjari, Indonesia
Computer Science & IT Decision Sciences, Operations Research & Management

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Klusterisasi Impor Beras Di Indonesia Menurut Negara Asal Utama Menggunakan Algoritma K-Medoids Nur Arminarahmah; Achmad Daengs GS; Jaya Tata Hardinata
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 8, No 2 (2023): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v8i2.657

Abstract

This study aims to classify rice import data in Indonesia based on the main country of origin using the K-Medoids algorithm. The rice import data used in this study covers the last six years (2017-2022), which is quantitative data, namely rice import data in Indonesia quoted from the Indonesian Statistical Publication, and processed based on the customs archives of the Directorate General of Customs and Excise. The K-Medoids method was chosen because of its ability to handle outliers and provide more stable clustering results compared to other clustering algorithms. The results of the analysis show that there are three main clusters of rice-supplying countries in Indonesia. The first cluster consists of countries with high import volumes, the second includes countries with moderate import volumes, and the third comprises countries with low import volumes. These findings provide important insights for the government and industry players in formulating rice import strategies, particularly in choosing the country of origin of imports and determining tariff policies. In addition, the results of this clustering can be used as a basis for making decisions regarding the diversification of rice import sources to increase national food security.
Klusterisasi Impor Beras Di Indonesia Menurut Negara Asal Utama Menggunakan Algoritma K-Medoids Nur Arminarahmah; Achmad Daengs GS; Jaya Tata Hardinata
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 8, No 2 (2023): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v8i2.657

Abstract

This study aims to classify rice import data in Indonesia based on the main country of origin using the K-Medoids algorithm. The rice import data used in this study covers the last six years (2017-2022), which is quantitative data, namely rice import data in Indonesia quoted from the Indonesian Statistical Publication, and processed based on the customs archives of the Directorate General of Customs and Excise. The K-Medoids method was chosen because of its ability to handle outliers and provide more stable clustering results compared to other clustering algorithms. The results of the analysis show that there are three main clusters of rice-supplying countries in Indonesia. The first cluster consists of countries with high import volumes, the second includes countries with moderate import volumes, and the third comprises countries with low import volumes. These findings provide important insights for the government and industry players in formulating rice import strategies, particularly in choosing the country of origin of imports and determining tariff policies. In addition, the results of this clustering can be used as a basis for making decisions regarding the diversification of rice import sources to increase national food security.
Co-Authors GS , Achmad Daengs Jaya Tata Hardinata