Analisis dan Perbandingan Kualitas Pengelompokan Dokumen (Document Clustering) Dengan Menggunakan Metode K-Means Dan K-Medians

Bustami Bustami


Conducting data analysis on a large set of documents is not an easy task. The common stages are document filtering, document selection, and document clustering. Clustering is a technique used in data mining to find groups of data that do not have a natural grouping. There are many clustering algorithm have been introduced, and two of them are K-means and K-medians. Both methods classify documents based on the proximity of words weighting between documents. This study aims to compare the quality of the clusters produced by K-means and K-medians. The results show that K-medians obtain a better cluster quality when compared to K-means. However, it takes more time to cluster.


Data Mining, Clustering, K-means, and K-medians

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© Elkawnie : Journal of Islamic Science and Technology 2019. Published by Faculty of Science and Technology in cooperation with Center for Research and Community Service (LP2M), UIN Ar-Raniry Banda Aceh, Aceh, Indonesia.

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