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


Dedi Suhendro, S.E., M.Si, (2020) Implementasi K-Means Clustering Untuk Mengelompokkan Hasil Pertanian Kacang Kedelai (Ha) Berdasarkan Provinsi, Prosiding ,Prosiding Seminar Nasional Riset Dan Information Science (SENARIS)
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Dedi Suhendro, S.E., M.Si, | pdf
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Abstrak
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.