Implementasi Algoritma K-Medoids pada Pengelompokkan Keragaman Kelompok Tani

Dina Andriana(1*), Eka Irawan(2), Rizky Khairunnisa Sormin(3),

(1) STIKOM Tunas Bangsa, Pematang Siantar, Indonesia
(2) STIKOM Tunas Bangsa, Pematang Siantar, Indonesia
(3) STIKOM Tunas Bangsa, Pematang Siantar, Indonesia
(*) Corresponding Author

Abstract


Farmer groups have a role in driving agricultural development in rural areas and are the main actors in agriculture-based economic empowerment. This study aims to create a clustering model using the K-Medoids algorithm. The K-Medoids algorithm or also known as PAM (Partitioning Around Medoids) uses the clustering partition method to group a set of n objects into a number of k clusters, by grouping farmer groups so that the level of development and farmer groups according to superior commodities is obtained. This research was conducted in Pematang Bandar Simalungun. The data in this study were sourced from BBP (Agricultural Extension Center). The data collected is calculated according to the data so that farmer groups are obtained according to the leading commodity. The grouping is done based on the number of farmer group data from 4 villages in Pematang Bandar. It is hoped that this research can be an illustration of the BPP in taking resource development policies for each farmer group so that in the future more farmer groups are included in the highest cluster and are expected to have an impact on increasing the productivity of these farmer groups.


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