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Identifikasi Provinsi Di Indonesia Berdasarkan Produksi Tanaman Pangan Menggunakan Algoritma K-means Clustering

Identifikasi Provinsi Di Indonesia Berdasarkan Produksi Tanaman Pangan Menggunakan Algoritma K-means Clustering
Titi Purwandari, Yuyun Hidayat
Universitas Padjadjaran, Prosiding Seminar nasional teknologi informasi 29 Oktober 2016, Vol. 13 No. 1 Tahun 2016, ISSN : 1829-9156 (Printed), ISSN : 2541-40X, Fakultas teknologi informasi universitas tarumanagara jakarta
Bahasa Indonesia, Bahasa Inggris
Universitas Padjadjaran, Prosiding Seminar nasional teknologi informasi 29 Oktober 2016, Vol. 13 No. 1 Tahun 2016, ISSN : 1829-9156 (Printed), ISSN : 2541-40X, Fakultas teknologi informasi universitas tarumanagara jakarta
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The agricultural sector plays an important role in national development. Contribution of the agricultural sector is reflected through the contribution in the establishment of the Gross Domestic Product (GDP), employment, exports of agricultural products, especially plantation. Based on these reasons, the government pays attention to the development of this sector. The purpose of this study was to obtain information on the province’s profile in the Indonesian based on the results of agricultural production with a way to classify province‚Äôs in Indonesia based on similarity characteristics as measured by 7 agricultural production. The usefulness of the results of this study provide a scientific reference for the government in making our decision. The analyzed data are secondary data collected by the Central Bureau of Statistics with the object of the study was 34 provinces in Indonesia and the variables studied are the result of agricultural production that is rice, maize, soybeans, green beans, peanuts, sweet potatoes, cassava. The methods used are K-Means Clustering algorithm. The results of analysis using k-means clustering algorithm, obtained three clusters namely klaster1 consists of 30 provinces, cluster 2 is composed of three provinces, and cluster 3 comprises one province based on seven food crops.

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