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Open access Jurnal SINTA 2

Recommendation System for Thesis Topics Using Content-based Filtering

IJCCS (Indonesian Journal of Computing and Cybernetics Systems) · Vol. 15 No. 1 (2021) · pp. 65–74

DOI
10.22146/ijccs.62716
ISSN
2460-7258, 1978-1520
Published
2021-01-31
Publisher
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

When pursuing their bachelor degree, every students are required to pursue a thesis in order to graduate from the major that they take. However, during the process, students got several difficulty regarding chosing their thesis topics. Therefore, a recommendation system is needed to classify thesis topics based on the students’ interest and abilities. This study developed a recommendation system for thesis topics using content-based filtering where the students will be asked to choose the course that they interested in along with their grades. After getting all the required data, the recommendation system will process the data and then it’ll show the title and the abstract of publication that fits the criteria.In this research, there are 2 datasets that is used, there are lecturer publication within 3 years and syllabus data of Computer Science UGM course. After running this research, it was found that the recommendation system has an average 7.46 seconds running time. It was also found that the recommendation system got an average 83% of the recommendation system objectives. The recommendation system objectives consist of relevance, novelty, serendipity, and increasing recommendation diversity.

Keywords

Collaboration network of the authors

28 authors · 46 co-authorship links · 8 across different organisations

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

  • Universitas Gadjah Mada
  • Politeknik Negeri Ketapang
  • National Central University
  • Muria Kudus University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Retantyo WardoyoUniversitas Gadjah Mada4
Anny Kartika SariUniversitas Gadjah Mada3
Sri T. HartatiUniversitas Gadjah Mada2
Rahmat BudiarsaUniversitas Gadjah Mada2
Fajar Ibnu TufeilAffiliation unknown1
Mujiono MujionoAffiliation unknown1
Annisa MaulianiUniversitas Gadjah Mada1
Ria AstriratmaUniversitas Gadjah Mada1
Agus HarjokoUniversitas Gadjah Mada1
Nelson RumuiPoliteknik Negeri Ketapang1
Maulida Ayu FitrianiUniversitas Gadjah Mada1
Damar RiyadiUniversitas Gadjah Mada1
Ilham UnggaraUniversitas Gadjah Mada1
Yessi YunitasariUniversitas Gadjah Mada1
Dias Aziz PramuditaUniversitas Gadjah Mada1
Abidah ElcholiqiUniversitas Gadjah Mada1
Wahyu SrimulyaniUniversitas Gadjah Mada1
Yunita SariUniversitas Gadjah Mada1
Rayhan Naufal RamadhanUniversitas Gadjah Mada1
Faisal RamadhanUniversitas Gadjah Mada1
Muhammad Bintang BahyUniversitas Gadjah Mada1
Muhammad Fawwaz MaydaUniversitas Gadjah Mada1
Aditya PermanaUniversitas Gadjah Mada1
Timothy K. ShihNational Central University1
Anastasya LatubessyMuria Kudus University1
Sri KusrohmaniahUniversitas 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">Recommendation System for Thesis Topics Using Content-based Filtering</dc:title>
	<dc:creator>Kusuma, Hans Satria</dc:creator>
	<dc:creator>Musdholifah, Aina</dc:creator>
	<dc:subject xml:lang="en-US"></dc:subject>
	<dc:subject xml:lang="en-US">Recommendation System;Content-based Filtering;Euclidean Distance</dc:subject>
	<dc:description xml:lang="en-US"> When pursuing their bachelor degree, every students are required to pursue a thesis in order to graduate from the major that they take. However, during the process, students got several difficulty regarding chosing their thesis topics. Therefore, a recommendation system is needed to classify thesis topics based on the students’ interest and abilities. This study developed a recommendation system for thesis topics using content-based filtering where the students will be asked to choose the course that they interested in along with their grades. After getting all the required data, the recommendation system will process the data and then it’ll show the title and the abstract of publication that fits the criteria.In this research, there are 2 datasets that is used, there are lecturer publication within 3 years and syllabus data of Computer Science UGM course. After running this research, it was found that the recommendation system has an average 7.46 seconds running time. It was also found that the recommendation system got an average 83% of the recommendation system objectives. The recommendation system objectives consist of relevance, novelty, serendipity, and increasing recommendation diversity.</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>2021-01-31</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
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	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.ugm.ac.id/ijccs/article/view/62716</dc:identifier>
	<dc:identifier>10.22146/ijccs.62716</dc:identifier>
	<dc:source xml:lang="en-US">IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 15, No 1 (2021): January; 65-74</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/62716/30559</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2021 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>