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

Rolly Maulana Awangga (Politeknik Pos Indonesia)
Syafrial Fachri Pane (Politeknik Pos Indonesia)
Khaera Tunnisa (Politeknik Pos Indonesia)
Iping Supriana Suwardi (Institut Teknologi Bandung)

TELKOMNIKA (Telecommunication Computing Electronics and Control)
Vol 16, No 3: June 2018

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.