KARYADI, SYAIFUDIN (2016) ANALISIS KECENDERUNGAN INFORMASI DENGAN MENGGUNAKAN METODE TEXT MINING (Studi Kasus: Akun twitter @detikcom). Undergraduate thesis, Fakultas Sains dan Matematika, Undip.
ABSTRACT The Internet is an extraordinary phenomenon. Starting from a military experiment in the United States, the Internet has evolved into a 'need' for more than tens of millions of people worldwide. The number of internet users is large and growing, has been creating internet culture. One of the fast growing social media twitter. Twitter is a microblogging service that stores text database called tweets. To make it easier to obtain information that is dominant discussed, then sought the topic of twitter tweet using clustering. In this research, grouping 500 tweets from twitter account @detikcom using k-means clustering. The results of this study indicate that the maximum index Dunn, the best grouping K-means clustering to obtain the dominant topic as many as three clusters, namely the government, Jakarta, and politics. Keywords: text mining, clustering,, k-means , dunn index, and twitter.
|Item Type:||Thesis (Undergraduate)|
|Subjects:||H Social Sciences > HA Statistics|
|Divisions:||Faculty of Science and Mathematics > Department of Statistics|
|Deposited By:||Mr Hasbi Yasin|
|Deposited On:||25 Jul 2017 14:21|
|Last Modified:||25 Jul 2017 14:21|
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