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ITS » Paper and Presentation » Teknik Elektro - Telematika S2
Posted by tondoindra@gmail.com at 22/12/2014 18:55:50  •  1238 Views


PENGELOMPOKAN OTOMATIS WALL FACEBOOK DAN DAMPAK STEMMING TERHADAP KINERJANYA

FACEBOOK WALL AUTOMATIC CLUSTERING AND IMPACT OF PRE-PROCESS STEM TO CLUSTER PERFORMANCE

Author :
SUNDIKA, I PUTU ( 2211206708 )




ABSTRAK

Pesatnya pengunaan dan adopsi Internet telah memacu pertumbuhan dan pertukaran informasi yang sangat pesat dibandingkan era sebelumnya. Perkembangan ini memungkinkan informasi untuk di akses penguna dengan mudah jumlah yang terkendalikan ini telah menimbulkan isu dan tantangan yang besar. Berita yang disampaikan melalui media elektronik khususnya yang disebarkan melalui situs jejaring sosial facebook sangat cepat dan banyak mendapatkan respon dari masyarakat. Begitu tingginya jumlah pengguna Facebook di Indonesia membuat media cetak nasional di Indonesia juga membuat Facebook page dengan isi wall adalah cuplikan dari berita yang ada di websitenya. Dengan menggunakan k-Means dan Farthest-First wall tersebut dapat dikelompokkan secara otomatis berdasarkan kesamaan topik bahasannya. Pre-proses dari pengelompokkan ini menggunakan Porter Stemmer Untuk Bahasa Indonesia dan Naizef Stemmer. Dari hasil uji coba 466 data wall facebook cluster terbaik didapatkan dengan k-Means k2 tanpa pre-proses stemming. Akurasi yang dicapai untuk pelabelan nasional dan non-nasional adalah 92.92. Clustering wall nasional terbaik juga dihasilkan menggunakan k-Means k2 dengan menerapkan pre-proses Nazief. Akurasi yang didapatkan dengan label korupsi dan non-korupsi adalah 77.78.


ABSTRACT

The rapid use and adoption of the Internet has spurred the growth and exchange of information very rapidly compared to the previous era. This situation allows user get information easily but it become difficult to control and may caused major issues and challenges.. News delivered through the electronic media in particular such as the social networking site facebook is spreading very fast and get a lot of response from the public. The number of Facebook users in Indonesia is very high. This condition is used as an opportunity by the online media like news portal by making a page on facebook. The content of their wall is a preview or short description about newsarticles which is posted on their official website. By using k-Means and Farthest-First the wall can be automatically grouped by similarity topics. Preliminary processes in this grouping or clustering is done by Indonesia Porter Stemmer and Naizef. amount of data to be tested in this study were 466 wall. The best clustering quality produced by the k-Means k 2 without pre-stemming process. Accuracy achieved for the labeling of national and non-national is 92.92. Clustering wall labeled national into the label of corruption and non-corruption produced 77.78 accuracy. This result was achieved by the k-means clustering with k 2 pre-process Stemming Nazief.



KeywordsPengelompokan; k-Means; Farthest-First; Porter Stemmer Bahasa Indonesia; Nazief Stemmer;
 
Subject:  Jaringan informasi; Internet; pengolahan data elektronis
Contributor
  1. Prof. Dr. Ir. Mauridhi Hery Purnomo, M.Eng
  2. Dr. Surya Sumpeno, ST, MSc
Date Create: 30/01/2013
Type: Text
Format: PDF
Language: Indonesian
Identifier: ITS-paper-22121140006665
Collection ID: 22121140006665
Call Number: RTE 006.312 Sun p


Source
Paper And Presentation of Electrical Engineeing RTE 006.312 Sun p, 2014

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