GDL

Journal from gdlhub / 2018-07-25 15:55:52
Oleh : Rolly Maulana Awangga, Syafrial Fachri Pane, Khaera Tunnisa, Iping Supriana Suwardi, Telkomnika
Dibuat : 2018-07-25, dengan 1 file

Keyword : Autocomplete; Clustering; K-Means Algorithm; predictions and suggestionn; Criteria of Characters
Url : http://journal.uad.ac.id/index.php/TELKOMNIKA/article/view/8910
Sumber pengambilan dokumen : WEB

he Autocomplete feature is used in the search interface to help Puslitbang TekMIRA staff looking for data from the coal term. Autocomplete queries help users create their queries to be declared in a query. Auto-completion can help resolve errors, especially on small devices. The proposed method for Autocompletion is the K-Means and Meanshift algorithm. The K-Means algorithm will classify data from coal terms based on character and word criteria. Graphs of grouped data will be displayed using the Meanshift algorithm. The results of a coal data grouping using the K - Means algorithm will be used for word prediction when the user enters the query. The K-Means Algorithm Method will provide predictions/suggestions of words according to the grouping results. A prediction/suggestion list is data grouped by user-entered queries. K-Means and Meanshift method can facilitate Puslitbang tekMIRA employees to classify data and be a list of predictions/suggestions in query completion on data search system of coal term.

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