Implementation of Clustering on Tobacco Import Data By Country Of Destination Using The K-Means Algorithm

Abstract

Tobacco is a seasonal agricultural product which is not a food commodity, but a plantation commodity. This product is consumed not for food but as a spare time filler or "entertainment", namely as a raw material for cigarettes and cigars. Indonesia is currently one of the countries with the highest smoking rates in the world. The domestic tobacco industry is now growing rapidly, as well as making the types of cigarettes in the country more diverse. In this study, the authors used the k-means clustering data mining technique to classify copper import data according to their original purpose. The results of this study are copper import data clusters. The copper import cluster consists of two clusters, namely the high cluster and the low cluster.