Melola Discovery

← Melola Discovery

Jurnal SINTA 2

Face Recognition Using Complex Valued Backpropagation

Jurnal Ilmu Komputer dan Informasi (JIKI) · Vol. 11 No. 2 (2018) · pp. 103–109

DOI
10.21609/jiki.v11i2.617
ISSN
2502-9274, 2088-7051
Published
2018-06-29
Publisher
Faculty of Computer Science - Universitas Indonesia
Language
eng

Abstract

Face recognition is one of biometrical research area that is still interesting. This study discusses the Complex-Valued Backpropagation algorithm for face recognition. Complex-Valued Backpropagation is an algorithm modified from Real-Valued Backpropagation algorithm where the weights and activation functions used are complex. The dataset used in this study consist of 250 images that is classified in 5 classes. The performance of face recognition using Complex-Valued Backpropagation is also compared with Real-Valued Backpropagation algorithm. Experimental results have shown that Complex-Valued Backpropagation performance is better than Real-Valued Backpropagation.

Keywords

Collaboration network of the authors

29 authors · 71 co-authorship links · 45 across different organisations

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

  • University of Indonesia
  • Institut Teknologi Sepuluh Nopember
  • Universitas Negeri Surabaya
  • University of Edinburgh
  • Diponegoro University
  • Binus University
  • Tarumanagara University
  • Other organisations
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Muhammad Anwar Ma’SumUniversity of Indonesia3
Adi WibowoDiponegoro University2
Alexander Agung Santoso GunawanBinus University2
Mohammad Isa IrawanInstitut Teknologi Sepuluh Nopember2
Dwi Marhaendro Jati PurnomoUniversity of Indonesia2
Tjan BasaruddinUniversity of Indonesia1
Muhammad Syaeful FajarUniversity of Indonesia1
Fadhlurrahman AfifUniversity of Indonesia1
Ratna RustamadjiUniversity of Indonesia1
Miesje Karmiati PurwanegaraUniversity of Indonesia1
Sani Muhammad IsaTarumanagara University1
Benny HardjonoPelita Harapan University1
Diane FitriaUniversity of Indonesia1
Muhammad AthoillahInstitut Teknologi Sepuluh Nopember1
Umi MahdiyahInstitut Teknologi Sepuluh Nopember1
Sumarsih Condroayu PurbaraniUniversity of Indonesia1
Qurrotin Aâ€TMyuninaUniversity of Indonesia1
Muhammad Anwar Maâ€TMsumUniversity of Indonesia1
Novian HabibieUniversity of Indonesia1
Machmud Roby AlhamidiUniversity of Indonesia1
Arie Rachmad SyulistyoPoliteknik Negeri Malang1
Dewa Made Sri ArsaUniversity of Indonesia1
Grafika JatiUniversity of Indonesia1
Agung SantosoUniversity of Indonesia1
Rafli FilanoUniversity of Indonesia1
Nurul HanifahUniversity of Indonesia1

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) 
<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/  http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
	<dc:title xml:lang="en-US">Face Recognition Using Complex Valued Backpropagation</dc:title>
	<dc:creator>Nafisah, Zumrotun</dc:creator>
	<dc:creator>Rachmadi, Febrian</dc:creator>
	<dc:creator>Imah, Elly Matul</dc:creator>
	<dc:subject xml:lang="en-US">face recognition</dc:subject>
	<dc:subject xml:lang="en-US">complex valued backpropagation</dc:subject>
	<dc:description xml:lang="en-US">Face recognition is one of biometrical research area that is still interesting. This study discusses the Complex-Valued Backpropagation algorithm for face recognition. Complex-Valued Backpropagation is an algorithm modified from Real-Valued Backpropagation algorithm where the weights and activation functions used are complex. The dataset used in this study consist of 250 images that is classified in 5 classes. The performance of face recognition using Complex-Valued Backpropagation is also compared with Real-Valued Backpropagation algorithm. Experimental results have shown that Complex-Valued Backpropagation performance is better than Real-Valued Backpropagation.</dc:description>
	<dc:publisher xml:lang="en-US">Faculty of Computer Science  - Universitas Indonesia</dc:publisher>
	<dc:date>2018-06-29</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://jiki.cs.ui.ac.id/index.php/jiki/article/view/617</dc:identifier>
	<dc:identifier>10.21609/jiki.v11i2.617</dc:identifier>
	<dc:source xml:lang="en-US">Jurnal Ilmu Komputer dan Informasi; Vol. 11 No. 2 (2018): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information); 103-109</dc:source>
	<dc:source>2502-9274</dc:source>
	<dc:source>2088-7051</dc:source>
	<dc:source>10.21609/jiki.v11i2</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://jiki.cs.ui.ac.id/index.php/jiki/article/view/617/403</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2018 Jurnal Ilmu Komputer dan Informasi</dc:rights>
</oai_dc:dc>