Text Mining dengan K-Means Clustering pada Tema LGBT dalam Arsip Tweet Masyarakat Kota Bandung

  • Eko Yulian Pusdiklat Badan Pusat Statistik Jakarta Selatan
Keywords: K-Means Clustering; LGBT; Text Mining


The movement of LGBT is growing rapidly through social media so that LGBT ideas can be freely expressed. The tweeter is one of the media that is often used for that purpose. Comments or "cuitan" about LGBT on twitter certainly many in number. The amount of information available in cyberspace makes development efforts to extract information from online databases rapidly, one of which is text mining. One of the statistical techniques that can be used to utilize the results of text mining is clustering. Clustering used in this study is K-Means clustering. This study uses 5 clusters to group comments on The twitter associated with LGBT in the city of Bandung. Of the five clusters formed in the K-means process, it is found that the tendency of Tuet Tweeter users of LGBT related bands in general, is still related to the religious perspective which is marked by the emergence of the word religion very often.


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