Implementasi K-Means Clustering Untuk Mengelompokkan Hasil Pertanian Kacang Kedelai (Ha) Berdasarkan Provinsi

Masitha Masitha, S Solikhun, Dedi Suhendro, Irfan Sudahri Damanik, M. Fauzan

Abstract


Soybeans are one of the types of legumes which are the basic ingredients of many foods that are useful for body health, this plant has also been cultivated since 3500 years ago. Judging from the data yield of soybean (Ha) obtained from various provinces, the yield varies from year to year. But at this time the government is still lacking information in getting an information about the grouping of agricultural yield data from various provinces in Indonesia, therefore, the authors conducted a study aimed at grouping the harvested area of soybean (Ha) in each province in Indonesia with using the K-Means Clustering algorithm. The data will be divided or clustered into 3 clusters where cluster 1 is a group of provinces with high potential for agricultural output with a yield of 1 province, cluster 2 is a province with medium agricultural yield with a yield of 5 provinces, while cluster 3 is a province with low agricultural yield potential with yields of 27 provinces. The results of this study are as a way to assist the government in establishing soybean farming development areas (Ha) which is an opportunity for the government to develop and improve the provincial economy. And it is hoped that this research can be used as a material for policy making to increase soybean yields in each province in the future so that it can help maximize government programs in soybean farming.

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References


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DOI: http://dx.doi.org/10.30645/senaris.v2i0.161

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