FILTER-BASED FEATURE SELECTION PADA KATEGORISASI ARTIKEL BERITA BERBAHASA INDONESIA

Puspitarani, Yan

FILTER-BASED FEATURE SELECTION PADA KATEGORISASI ARTIKEL BERITA BERBAHASA INDONESIA

dc.contributor.author	Puspitarani, Yan
dc.date.accessioned	2014-12-27T04:25:42Z
dc.date.accessioned	2019-10-21T12:28:11Z
dc.date.available	2014-12-27T04:25:42Z
dc.date.available	2019-10-21T12:28:11Z
dc.date.issued	2013-04-06
dc.description.abstract	With the technology development, a large amount of information such as news articles are available over the internet. Hence, text categorization, such as applying classification as one of data mining task, is needed. The major issue in text categorization is the high dimensionality of data. Therefore, we need to select some representative attributes to improve the performance of text categorization. One of techniques to complete this task is feature selection. Feature selection can reduce high dimensionality. Thus, the classifier effectiveness can improve. Among many method, is a filterbased feature selection. This research examined and compared some feature selection techniques toward Indonesian news articles by applying filter model. These models are discussed: Gini Index for text categorization, CHI, Information Gain, Expected Cross Entropy, Weight Of Evidence and Orthogonal Centroid Feature Selection (OCFS).	en_US
dc.identifier.isbn	978-602-17488-0-0
dc.identifier.uri	http://repository.widyatama.ac.id/handle/123456789/4289
dc.publisher	Seminar Teknik Informatika dan Sistem Informasi 2013,Universitas Kristen Maranatha	en_US
dc.relation.ispartofseries	;KIN.CD.058
dc.subject	filter-based feature selection	en_US
dc.subject	measurement function	en_US
dc.title	FILTER-BASED FEATURE SELECTION PADA KATEGORISASI ARTIKEL BERITA BERBAHASA INDONESIA	en_US
dc.type	Presentation	en_US