Sistem Klasterisasi Produktivitas Peternak Sapi dengan Metode Kmeans (Studi Kasus : KPSBU Lembang) - Fahrezi, Rizal Febrian; Witanti, Wina; Hadiana, Asep Id (Fakultas Teknik Universitas Wahid Hasyim, 2021)
Along with the rapid development of information technology, many information technologies are used to help facilitate human work. For example, in the field of animal husbandry, cattle are in great demand for breeding because they have many benefits, one of which is milk. Milk is a processed animal protein product produced by cows. The milk produced by the farmers is then sold to a cooperative called KPSBU Lembang which is a place to store milk for later processing. KPSBU can have many dairy farmers based on different levels of productivity so that a lot of data can be obtained. So a milk grouping system needs to be developed to assist KPSBU in classifying milk data based on similarity of data and provide information if new data is entered. The system was developed by utilizing the K-Means algorithm which is one of the clustering algorithms in data mining to perform a grouping. The grouping carried out in the maximum system is divided into 3 groups, with the variables used are high, medium and low. The result of this research is a clustering system that can help KPSBU in classifying milk based on the similarity of data using the K-Means algorithm so that the productivity data owned can be made into several clusters. These results are an illustration that shows the grouping of farmer areas based on dairy cattle production, namely 17 sub-districts that have high production (cluster1), 2 sub-districts that have medium production potential (cluster2), and 7 sub-districts that have low production (cluster3).