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Parallelization of Hybrid Content Based and Collaborative Filtering Method in Recommendation System with Apache Spark

IJCCS (Indonesian Journal of Computing and Cybernetics Systems) · Vol. 13 No. 2 (2019) · pp. 149–158

DOI
10.22146/ijccs.38596
ISSN
2460-7258, 1978-1520
Published
2019-04-30
Publisher
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Collaborative Filtering as a popular method that used for recommendation system. Improvisation is done in purpose of improving the accuracy of the recommendation. A way to do this is to combine with content based method. But the hybrid method has a lack in terms of scalability. The main aim of this research is to solve problem that faced by recommendation system with hybrid collaborative filtering and content based method by applying parallelization on the Apache Spark platform.Based on the test results, the value of hybrid collaborative filtering method and content based on Apache Spark cluster with 2 node worker is 1,003 which then increased to 2,913 on cluster having 4 node worker. The speedup got more increased to 5,85 on the cluster that containing 7 node worker.

Keywords

Collaboration network of the authors

28 authors · 28 co-authorship links · 7 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Universitas Gadjah Mada
  • Indonesia University of Education
  • Universitas Airlangga
  • Instituto Profissional de Canossa - IPDC
  • Universitas Halu Oleo
  • Institut Teknologi Telkom Purwokerto
  • Universitas Widya Dharma Klaten
  • Other organisations
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Sandi Fajar RodiyansyahIndonesia University of Education2
Mardi Siswo UtomoUniversitas Gadjah Mada1
Badrus ZamanUniversitas Airlangga1
Agustinus JacobusUniversitas Gadjah Mada1
Sulistyowati SulistyowatiAffiliation unknown1
Noviah Dwi PutrantiUniversitas Gadjah Mada1
Ambarwati AmbarwatiInstituto Profissional de Canossa - IPDC1
Agus Sasmito AriwibowoAffiliation unknown1
Eka KaryawatiUniversitas Gadjah Mada1
Robynson AmsekeAffiliation unknown1
Natalis RansiUniversitas Halu Oleo1
Sumarni AdiUniversitas Gadjah Mada1
Lutfi Budi IlmawanUniversitas Gadjah Mada1
Wayan Gede Suka ParwitaUniversitas Gadjah Mada1
Fadhila Tangguh AdmojoUniversitas Gadjah Mada1
Siti KhomsahInstitut Teknologi Telkom Purwokerto1
Doni SetyawanUniversitas Widya Dharma Klaten1
Fajar RatnawatiPoliteknik Negeri Bengkalis1
Ira ZulfaUniversitas Gadjah Mada1
Junanda PatihullahUniversitas Gadjah Mada1
Wafda RifaiUniversitas Gadjah Mada1
Sigit PriyantaUniversitas Gadjah Mada1
Sholikin Ady ChandraUniversitas Gadjah Mada1
Putri Rizki AmaliaUniversitas Gadjah Mada1
Angel Berta Desi SuryantiUniversitas Gadjah Mada1
Fahmi Reza PrasastioUniversitas Gadjah Mada1

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://journal.ugm.ac.id/ijccs/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">Parallelization of Hybrid Content Based and Collaborative Filtering Method in Recommendation System with Apache Spark</dc:title>
	<dc:creator>Ikhsanudin, Rakhmad</dc:creator>
	<dc:creator>Winarko, Edi</dc:creator>
	<dc:subject xml:lang="en-US">Computer Science</dc:subject>
	<dc:subject xml:lang="en-US">recomendation system; hybrid content based and collaborative filtering method; Apache Spark</dc:subject>
	<dc:description xml:lang="en-US">Collaborative Filtering as a popular method that used for recommendation system. Improvisation is done in purpose of improving the accuracy of the recommendation. A way to do this is to combine with content based method. But the hybrid method has a lack in terms of scalability. The main aim of this research is to solve problem that faced by recommendation system with hybrid collaborative filtering and content based method by applying parallelization on the Apache Spark platform.Based on the test results, the value of hybrid collaborative filtering method and content based on Apache Spark cluster with 2 node worker is 1,003 which then increased to 2,913 on cluster having 4 node worker. The speedup got more increased to 5,85 on the cluster that containing 7 node worker.</dc:description>
	<dc:publisher xml:lang="en-US">IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.</dc:publisher>
	<dc:contributor xml:lang="en-US"></dc:contributor>
	<dc:date>2019-04-30</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US"></dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.ugm.ac.id/ijccs/article/view/38596</dc:identifier>
	<dc:identifier>10.22146/ijccs.38596</dc:identifier>
	<dc:source xml:lang="en-US">IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 2 (2019): April; 149-158</dc:source>
	<dc:source>2460-7258</dc:source>
	<dc:source>1978-1520</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.ugm.ac.id/ijccs/article/view/38596/24370</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>