Teknik Data Mining Dalam Clustering Produksi Susu Segar Di Indonesia Dengan Algoritma K-Means

Ilham Safitra Damanik (Mahasiswa Program Studi Sistem Informasi, STIKOM Tunas Bangsa, Pematangsiantar)
Sundari Retno Andani (AMIK Tunas Bangsa, Pematangsiantar, Indonesia)
Dedi Sehendro (AMIK Tunas Bangsa, Pematangsiantar, Indonesia)

Brahmana : Jurnal Penerapan Kecerdasan Buatan
Vol 1, No 1 (2019): Edisi Desember

Milk is an important intake to meet nutritional needs. Both consumed by children, and adults. Indonesia has many producers of fresh milk, but it is not sufficient for national milk needs. Data mining is a science in the field of computers that is widely used in research. one of the data mining techniques is Clustering. Clustering is a method by grouping data. The Clustering method will be more optimal if you use a lot of data. Data to be used are provincial data in Indonesia from 2000 to 2017 obtained from the Central Statistics Agency. The results of this study are in Clusters based on 2 milk-producing groups, namely high-dairy producers and low-milk producing regions. From 27 data on fresh milk production in Indonesia, two high-level provinces can be obtained, namely: West Java and East Java. And 25 others were added in 7 provinces which did not follow the calculation of the K-Means Clustering Algorithm, including in the low level cluster.