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PENGELOMPOKAN TOPIK DOKUMEN BERBASIS TEXT MINING DENGAN ALGORITME K-MEANS: STUDI KASUS PADA DOKUMEN KEDUTAAN BESAR AUSTRALIA JAKARTA

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Title PENGELOMPOKAN TOPIK DOKUMEN BERBASIS TEXT MINING DENGAN ALGORITME K-MEANS: STUDI KASUS PADA DOKUMEN KEDUTAAN BESAR AUSTRALIA JAKARTA
 
Creator Hardi, Wishnu
Kusuma, Wisnu Ananta
Basuki, Sulistyo
 
Subject text mining; content analysis; document clustering; K-Means algorithm
 
Description The Australian Embassy in Jakarta is storing a wide array of media release document. Analyzing particular and vital patterns of the documents collection is imperative as it will result in new insights and knowledge of significant topic groups of the documents. K-Means algorithm was used as a non- hierarchical clustering method which partitioning data objects into clusters. The method works through minimizing data variation within cluster and maximizing data variation between clusters. Of the documents issued between 2006 and 2016, 839 documents were examined in order to determine term frequencies and to generate clusters. Evaluation was conducted by nominating an expert to validate the cluster result. The result showed that there were 57 meaningful terms grouped into 3 clusters. “People to people links”, “economic cooperation”, and “human development” were chosen to represent topics of the Australian Embassy Jakarta media releases from 2006 to 2016. This research concluded that text mining can be used to cluster topic groups of documents. It provides a more systematic clustering process as the text analysis is conducted through a number of stages with specifically set parameters.
 
Publisher Perpustakaan Nasional RI
 
Contributor —
 
Date 2019-12-04
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
—
 
Format application/pdf
 
Identifier https://ejournal.perpusnas.go.id/vp/article/view/77
10.37014/visipustaka.v21i1.77
 
Source VISI PUSTAKA: Buletin Jaringan Informasi Antar Perpustakaan; Vol 21, No 1: April 2019; 67-76
2685-7138
1411-2256
 
Language eng
 
Relation https://ejournal.perpusnas.go.id/vp/article/view/77/pdf
 
Rights Copyright (c) 2019 VISI PUSTAKA: Jaringan Informasi Antar Perpustakaan
https://creativecommons.org/licenses/by-nc-sa/4.0
 


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