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WEB NEWS DOCUMENTS CLUSTERING IN INDONESIAN LANGUAGE USING SINGULAR VALUE DECOMPOSITION-PRINCIPAL COMPONENT ANALYSIS (SVDPCA) AND ANT ALGORITHMS

Jurnal Ilmu Komputer dan Informasi (JIKI) · Vol. 9 No. 1 (2016) · pp. 17–25

DOI
10.21609/jiki.v9i1.362
ISSN
2502-9274, 2088-7051
Published
2016-02-15
Publisher
Faculty of Computer Science - Universitas Indonesia
Language
eng

Abstract

Ant-based document clustering is a cluster method of measuring text documents similarity based on the shortest path between nodes (trial phase) and determines the optimal clusters of sequence document similarity (dividing phase). The processing time of trial phase Ant algorithms to make document vectors is very long because of high dimensional Document-Term Matrix (DTM). In this paper, we proposed a document clustering method for optimizing dimension reduction using Singular Value Decomposition-Principal Component Analysis (SVDPCA) and Ant algorithms. SVDPCA reduces size of the DTM dimensions by converting freq-term of conventional DTM to score-pc of Document-PC Matrix (DPCM). Ant algorithms creates documents clustering using the vector space model based on the dimension reduction result of DPCM. The experimental results on 506 news documents in Indonesian language demonstrated that the proposed method worked well to optimize dimension reduction up to 99.7%. We could speed up execution time efficiently of the trial phase and maintain the best F-measure achieved from experiments was 0.88 (88%).

Keywords

Collaboration network of the authors

40 authors · 89 co-authorship links · 11 across different organisations · showing the 40 most connected

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  • Institut Teknologi Sepuluh Nopember
  • Lampung University
  • University of Brawijaya
  • Universitas Islam Negeri Raden Intan Lampung
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Chastine FatichahInstitut Teknologi Sepuluh Nopember8
Dini Adni NavastaraInstitut Teknologi Sepuluh Nopember4
Agus Budi RaharjoInstitut Teknologi Sepuluh Nopember4
Rarasmaya IndraswariInstitut Teknologi Sepuluh Nopember3
Khoirul UmamInstitut Teknologi Sepuluh Nopember3
Gulpi Qorik Oktagalu PratamasunuAffiliation unknown3
Rizka Wakhidatus SholikahInstitut Teknologi Sepuluh Nopember3
Munjiah Nur SaadahInstitut Teknologi Sepuluh Nopember2
Rigga Widar AtmagiInstitut Teknologi Sepuluh Nopember2
Dyah S. RahayuInstitut Teknologi Sepuluh Nopember2
Anny YuniartiInstitut Teknologi Sepuluh Nopember2
Darlis HerumurtiInstitut Teknologi Sepuluh Nopember2
Safri AdamInstitut Teknologi Sepuluh Nopember2
Yudhi PurwanantoInstitut Teknologi Sepuluh Nopember2
Fahrur RoziInstitut Teknologi Sepuluh Nopember2
Hilya TsaniyaInstitut Teknologi Sepuluh Nopember2
Nanik SuciatiInstitut Teknologi Sepuluh Nopember2
Apriantoni ApriantoniInstitut Teknologi Sepuluh Nopember2
Fidi Wincoko PutroInstitut Teknologi Sepuluh Nopember2
Khadijah Fahmi Hayati HolleInstitut Teknologi Sepuluh Nopember2
Christian Sri Kusuma AdityaInstitut Teknologi Sepuluh Nopember2
Wawan GunawanUniversitas Islam Negeri Raden Intan Lampung1
⁠Undang RosidinLampung University1
Nina KadaritnaLampung University1
Naser JawasInstitut Teknologi Sepuluh Nopember1
Randy Cahya WihandikaUniversity of Brawijaya1
Go Frendi GunawanInstitut Teknologi Sepuluh Nopember1
Sonny Christiano GosariaInstitut Teknologi Sepuluh Nopember1
Yuita Arum SariUniversity of Brawijaya1
Evy Kamilah RatnasariInstitut Teknologi Sepuluh Nopember1
Siti MutrofinInstitut Teknologi Sepuluh Nopember1
Mutmainnah MuchtarInstitut Teknologi Sepuluh Nopember1
Jayanti Yusmah SariInstitut Teknologi Sepuluh Nopember1
Mohammad ZarkasiInstitut Teknologi Sepuluh Nopember1
Andi Baso KaswarInstitut Teknologi Sepuluh Nopember1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://jiki.cs.ui.ac.id/index.php/jiki/oai, first harvested 26 Okt 2026, last seen 26 Okt 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">WEB NEWS DOCUMENTS CLUSTERING IN INDONESIAN LANGUAGE USING SINGULAR VALUE DECOMPOSITION-PRINCIPAL COMPONENT ANALYSIS (SVDPCA) AND ANT ALGORITHMS</dc:title>
	<dc:creator>Fadllullah, Arif</dc:creator>
	<dc:creator>Kamudi, Dasrit Debora</dc:creator>
	<dc:creator>Nasir, Muhamad</dc:creator>
	<dc:creator>Arifin, Agus Zainal</dc:creator>
	<dc:creator>Purwitasari, Diana</dc:creator>
	<dc:subject xml:lang="en-US">web news documents clustering</dc:subject>
	<dc:subject xml:lang="en-US">principal component analysis</dc:subject>
	<dc:subject xml:lang="en-US">singular value decomposition</dc:subject>
	<dc:subject xml:lang="en-US">dimension reduction</dc:subject>
	<dc:subject xml:lang="en-US">ant algorithms</dc:subject>
	<dc:description xml:lang="en-US">Ant-based document clustering is a cluster method of measuring text documents similarity based on the shortest path between nodes (trial phase) and determines the optimal clusters of sequence document similarity (dividing phase). The processing time of trial phase Ant algorithms to make document vectors is very long because of high dimensional Document-Term Matrix (DTM). In this paper, we proposed a document clustering method for optimizing dimension reduction using Singular Value Decomposition-Principal Component Analysis (SVDPCA) and Ant algorithms. SVDPCA reduces size of the DTM dimensions by converting freq-term of conventional DTM to score-pc of Document-PC Matrix (DPCM). Ant algorithms creates documents clustering using the vector space model based on the dimension reduction result of DPCM. The experimental results on 506 news documents in Indonesian language demonstrated that the proposed method worked well to optimize dimension reduction up to 99.7%. We could speed up execution time efficiently of the trial phase and maintain the best F-measure achieved from experiments was 0.88 (88%).</dc:description>
	<dc:publisher xml:lang="en-US">Faculty of Computer Science  - Universitas Indonesia</dc:publisher>
	<dc:date>2016-02-15</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://jiki.cs.ui.ac.id/index.php/jiki/article/view/362</dc:identifier>
	<dc:identifier>10.21609/jiki.v9i1.362</dc:identifier>
	<dc:source xml:lang="en-US">Jurnal Ilmu Komputer dan Informasi; Vol. 9 No. 1 (2016): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information); 17-25</dc:source>
	<dc:source>2502-9274</dc:source>
	<dc:source>2088-7051</dc:source>
	<dc:source>10.21609/jiki.v9i1</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://jiki.cs.ui.ac.id/index.php/jiki/article/view/362/233</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2016 Jurnal Ilmu Komputer dan Informasi</dc:rights>
</oai_dc:dc>