K Means Clustering and Meanshift Analysis for Grouping the Data of Coal Term in Puslitbang tekMIRA

Abstract

Indonesian government agencies under the Ministry of Energy and Mineral Resources have problems in classifying data dictionary of coal. This research conduct grouping coal dictionary using K-Means and MeanShift algorithm. K-means algorithm is used to get cluster value on character and word criteria. The last iteration of Euclidian distance calculation data on k-means combine with Meanshift algorithm. The meanshift calculates centroid by selecting different bandwidths. The result of grouping using k-means and meanshift algorithm shows different centroid to find optimum bandwidth value. The data dictionary of this research has sorted in alphabetically.