Text Mining dengan K-Means Clustering pada Tema LGBT dalam Arsip Tweet Masyarakat Kota Bandung
AbstractThe 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.
Sinyo, Anakku Bertanya Tentang LGBT, PT Elex Media Komputindo, (2014).
Gatra, Melawan Aksi LGBT di Kampus, (2016).
Alim, S, Analysis of Tweets Related to Cyberbullying: Exploring Information Diffusion and Advice Available for Cyberbullying Victims. International
Journal of Cyber Behavior, Psychology and Learning, (2015).
Prasetyo, Eko, Data Mining Konsep dan Aplikasi menggunakan Matlab, Penerbit Andi Yogyakarta (2012).
Srihari, Retrieval by Content, diambil darihttp://www.cedar.buffalo.edu/~srihari/CSE626/Lecture-Slides, pada tanggal 6 Februari 2018
Hastuti, N. F., Saptono, R., &Suryani, E., Pemanfaatan Metode K-Means Clustering Dalam Penentuan Penerima Beasiswa,Jurnal Informatika, (2012).
Febrianti, F., Hafiyusholeh, M., & Asyhar, A.H., Perbandingan Pengklusteran Data Iris Menggunakan Metode K-Means dan Fuzzy C-Means, Jurnal Matematika MANTIK, 2 (1), pp. 7-13 (2016)
Copyright (c) 2018 Eko Yulian
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.