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Performance Analysis of Hashing Methods on the Employment of App

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 8 No. 5 (2018)

DOI
10.11591/ijece.v8i5.pp3512-3522
ISSN
2088-8708, 2088-8708
Published
2018-10-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc/4.0

Abstract

The administrative process carried out continuously produces large data. So the search process takes a long time. The search process by hashing methods can save time faster. Hashing is methods that directly access data in a table by making references to the key that hashing becomes the address in the table. The performance analysis of the hashing method is done by the number of 18 digit character values. The process of analysis is done on applications that have been implemented in the application. The algorithm of hashing method analyzed is progressive overflow (PO) and linear quotient (LQ). The main purpose of performance analysis of hashing method is to know how gig the performance of each method. The results analyzed showed the average value of collision with 15 keys in the analysis of 53.3% yield the same value, while 46.7% showed the linear quotient has better performance.

Collaboration network of the authors

36 authors · 78 co-authorship links · 7 across different organisations

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  • Universitas Ahmad Dahlan
  • AGH University of Krakow
  • Ajou University
  • Universiti Teknikal Malaysia Melaka
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Rusydi UmarUniversitas Ahmad Dahlan5
Imam RiadiUniversitas Ahmad Dahlan4
HermanUniversitas Ahmad Dahlan3
Sunardi SunardiUniversitas Ahmad Dahlan3
Muhammad Kunta BiddinikaUniversitas Ahmad Dahlan2
Frandika SeptaUniversitas Ahmad Dahlan2
Siti HelmiyahUniversitas Ahmad Dahlan2
Abdullah HanifUniversitas Ahmad Dahlan2
Kharis Hudaiby HanifUniversitas Ahmad Dahlan2
Dianda RifaldiUniversitas Ahmad Dahlan1
Asno Azzawagama FirdausUniversitas Ahmad Dahlan1
Muhajir YunusUniversitas Ahmad Dahlan1
Rio SubandiAffiliation unknown1
Maulana Muhammad Jogo SamodroUniversitas Ahmad Dahlan1
Yuminah yuminahUniversitas Ahmad Dahlan1
Suprianto SupriantoAffiliation unknown1
Deni MurdianiUniversitas Ahmad Dahlan1
W YunanriUniversitas Ahmad Dahlan1
Andi PrayudiUniversitas Ahmad Dahlan1
Musri Iskandar NasutionUniversitas Ahmad Dahlan1
Herman HermanUniversitas Ahmad Dahlan1
Satriya Dwi PutraUniversitas Ahmad Dahlan1
Fitri AnggrainiUniversitas Ahmad Dahlan1
Herman HermanUniversitas Ahmad Dahlan1
Wahid Alfaridsi Achmad ZeinAffiliation unknown1
Shoffan SaifullahAGH University of Krakow1
Sunardi SunardiUniversitas Ahmad Dahlan1
Muhammad Nur FaizUniversitas Ahmad Dahlan1
Tole SutiknoUniversitas Ahmad Dahlan1
Mohd Hatta JopriUniversiti Teknikal Malaysia Melaka1
Hendril Satrian PurnamaAffiliation unknown1
Anggit PamungkasAffiliation unknown1
Ibrahim Mohd AlsofyaniAjou University1

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.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Performance Analysis of Hashing Methods on the Employment of App</dc:title><dc:creator>Yudhana, Anton</dc:creator><dc:creator>Fadlil, Abdul</dc:creator><dc:creator>Prianto, Eko</dc:creator><dc:description>&lt;jats:p&gt;The administrative process carried out continuously produces large data. So the search process takes a long time. The search process by hashing methods can save time faster. Hashing is methods that directly access data in a table by making references to the key that hashing becomes the address in the table. The performance analysis of the hashing method is done by the number of 18 digit character values. The process of analysis is done on applications that have been implemented in the application. The algorithm of hashing method analyzed is progressive overflow (PO) and linear quotient (LQ). The main purpose of performance analysis of hashing method is to know how gig the performance of each method. The results analyzed showed the average value of collision with 15 keys in the analysis of 53.3% yield the same value, while 46.7% showed the linear quotient has better performance.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2018-10-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v8i5.pp3512-3522</dc:identifier><dc:identifier>10.11591/ijece.v8i5.pp3512-3522</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 8 No 5 (2018); 3512</dc:source><dc:source>2088-8708</dc:source><dc:source>2088-8708</dc:source><dc:relation>http://ijece.iaescore.com/index.php/IJECE/article/viewFile/8761/9532</dc:relation><dc:rights>http://creativecommons.org/licenses/by-nc/4.0</dc:rights></oai_dc:dc>