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Adaptive Unified Differential Evolution for Clustering

IJCCS (Indonesian Journal of Computing and Cybernetics Systems) · Vol. 12 No. 1 (2018) · pp. 53–62

DOI
10.22146/ijccs.27871
ISSN
2460-7258, 1978-1520
Published
2018-01-31
Publisher
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Various clustering methods to obtain optimal information continues to evolve one of its development is Evolutionary Algorithm (EA). Adaptive Unified Differential Evolution (AuDE), is the development of Differential Evolution (DE) which is one of the EA techniques. AuDE has self adaptive scale factor control parameters (F) and crossover-rate (Cr).. It also has a single mutation strategy that represents the most commonly used standard mutation strategies from previous studies.The AuDE clustering method was tested using 4 datasets. Silhouette Index and CS Measure is a fitness function used as a measure of the quality of clustering results. The quality of the AuDE clustering results is then compared against the quality of clustering results using the DE method.The results show that the AuDE mutation strategy can expand the cluster central search produced by ED so that better clustering quality can be obtained. The comparison of the quality of AuDE and DE using Silhoutte Index is 1:0.816, whereas the use of CS Measure shows a comparison of 0.565:1. The execution time required AuDE shows better but Number significant results, aimed at the comparison of Silhoutte Index usage of 0.99:1, Whereas on the use of CS Measure obtained the comparison of 0.184:1.

Keywords

Collaboration network of the authors

40 authors · 52 co-authorship links · 6 across different organisations · showing the 40 most connected

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

  • Universitas Gadjah Mada
  • IPB University
  • Universitas Lamappapoleonro
  • Diponegoro University
  • Universitas 'Aisyiyah Surakarta
  • Politeknik Negeri Ketapang
  • 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
Annisa MaulianiUniversitas Gadjah Mada2
Agus HarjokoUniversitas Gadjah Mada2
Fajar Ibnu TufeilAffiliation unknown1
Sri NurdiatiIPB University1
Jati Sasongko WibowoAffiliation unknown1
Aridhanyati ArifinAffiliation unknown1
Jamila JamilaAffiliation unknown1
Rio KurniawanUniversitas Gadjah Mada1
Rita WiryasaputraUniversitas Gadjah Mada1
Sri Fitri WahyuniAffiliation unknown1
Sherly JayantiAffiliation unknown1
Salahuddin SalahuddinUniversitas Gadjah Mada1
Tedy RismawanUniversitas Gadjah Mada1
Muhammad Lhsan SaritaAffiliation unknown1
Rusdi EfendiAffiliation unknown1
Rukli RukliUniversitas Lamappapoleonro1
Khadijah KhadijahDiponegoro University1
Jani KusantiUniversitas 'Aisyiyah Surakarta1
Hence Beedwel LumentutAffiliation unknown1
Mujiono MujionoAffiliation unknown1
Eka WahyudiAffiliation unknown1
Ria AstriratmaUniversitas Gadjah Mada1
Ari Kusuma WardanaUniversitas Gadjah Mada1
Nelson RumuiPoliteknik Negeri Ketapang1
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
Achmad Siddik FathoniUniversitas Gadjah Mada1
Agus SihabuddinUniversitas Gadjah Mada1
Ainil MardiahUniversitas Gadjah Mada1
Hans Satria KusumaUniversitas Gadjah Mada1
Rayhan Naufal RamadhanUniversitas 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">Adaptive Unified Differential Evolution for Clustering</dc:title>
	<dc:creator>Fitriani, Maulida Ayu</dc:creator>
	<dc:creator>Musdholifah, Aina</dc:creator>
	<dc:creator>Hartati, Sri</dc:creator>
	<dc:subject xml:lang="en-US">Computer Science</dc:subject>
	<dc:subject xml:lang="en-US">AuDE; DE; Clustering</dc:subject>
	<dc:description xml:lang="en-US">Various clustering methods to obtain optimal information continues to evolve one of its development is Evolutionary Algorithm (EA). Adaptive Unified Differential Evolution (AuDE), is the development of Differential Evolution (DE) which is one of the EA techniques. AuDE has self adaptive scale factor control parameters (F) and crossover-rate (Cr).. It also has a single mutation strategy that represents the most commonly used standard mutation strategies from previous studies.The AuDE clustering method was tested using 4 datasets. Silhouette Index and CS Measure is a fitness function used as a measure of the quality of clustering results. The quality of the AuDE clustering results is then compared against the quality of clustering results using the DE method.The results show that the AuDE mutation strategy can expand the cluster central search produced by ED so that better clustering quality can be obtained. The comparison of the quality of AuDE and DE using Silhoutte Index is 1:0.816, whereas the use of CS Measure shows a comparison of 0.565:1. The execution time required AuDE shows better but Number significant results, aimed at the comparison of Silhoutte Index usage of 0.99:1 , Whereas on the use of CS Measure obtained the comparison of 0.184:1.</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>2018-01-31</dc:date>
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	<dc:identifier>https://journal.ugm.ac.id/ijccs/article/view/27871</dc:identifier>
	<dc:identifier>10.22146/ijccs.27871</dc:identifier>
	<dc:source xml:lang="en-US">IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 12, No 1 (2018): January; 53-62</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/27871/19935</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2018 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>
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