Open AccessPenerapan Data Mining Dalam Clustering Produksi Daging Sapi Di Indonesia Menggunakan Algoritma K-Means
Author(s) -
Henri Pandiangan
Publication year - 2019
Publication title -
journal of computer networks, architecture and high performance computing
Language(s) - English
Resource type - Journals
ISSN - 2655-9102
DOI - 10.47709/cnapc.v1i2.239
Subject(s) - cluster analysis , production (economics) , business , agency (philosophy) , government (linguistics) , agricultural science , geography , biology , mathematics , statistics , economics , philosophy , linguistics , macroeconomics , epistemology
Cows are animals that are found in Indonesia, cattle provide many benefits for humans ranging from milk that is rich in nutrients to meat as a source of high animal protein for humans. Beef production in Indonesia is not sufficient to meet domestic needs, so the government needs to ask for other meat and most still need beef to meet the daily protein needs of the community. The discussion of this study about the Application of Data Mining in the Cluster of Beef Production in Indonesia Using the K-Means Algorithm. The data source of this study was collected based on documents about beef production produced by the National Statistics Agency. The data used in this study are data from 2009-2016 consisting of 34 provinces. This study clustered in 3 groups, namely medium and low. The results of this study were 9 provinces included in the high group, 3 provinces included in the middle group and 22 provinces entered the low group.