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

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

Blog Article

Conducting data Cutting Saddles 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 DRY WAX quality when compared to K-means.However, it takes more time to cluster.