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Performance Analysis of Data Mining Methods for Sexually Transmitted Disease Classification

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

DOI
10.11591/ijece.v8i5.pp3933-3939
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

According to health reports of Malang city, many people are exposed to sexually transmitted diseases and most sufferers are not aware of the symptoms. Malang city being known as a city of education so that every year the population number increases, it is at risk of increasing the spread of sexually transmitted diseases virus. This problem is important to be solved to treat earlier sufferers sexually transmitted diseases virus in order to reduce the burden of patient spending. In this research, authors conduct data mining methods to classifying sexually transmitted diseases. From the experiment result shows that K-NN is the best method for solve this problem with 90% accuracy.

Collaboration network of the authors

40 authors · 83 co-authorship links · 5 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.

  • University of Brawijaya
  • Institut Teknologi Sepuluh Nopember
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Yusuf Priyo AnggodoUniversity of Brawijaya4
Asyrofa RahmiUniversity of Brawijaya2
Syaiful AnamUniversity of Brawijaya2
Candra Fajri AnandaUniversity of Brawijaya2
Firnanda Al Islama Achyunda PutraUniversity of Brawijaya1
Fitri UtaminingrumUniversity of Brawijaya1
Ida WahyuniUniversity of Brawijaya1
Bilqis AmaliahInstitut Teknologi Sepuluh Nopember1
Ary Mazharuddin ShiddiqiInstitut Teknologi Sepuluh Nopember1
Ilham Gurat AdillionInstitut Teknologi Sepuluh Nopember1
Bagaskoro Kuncoro ArdiInstitut Teknologi Sepuluh Nopember1
I Komang Ari MogiInstitut Teknologi Sepuluh Nopember1
Bintang NuralamsyahInstitut Teknologi Sepuluh Nopember1
Moch. Nafkhan AlzamzamiInstitut Teknologi Sepuluh Nopember1
Ervin YohannesUniversity of Brawijaya1
Hilman Nuril HadiUniversity of Brawijaya1
Rizal Setya PerdanaUniversity of Brawijaya1
Ghenniy RachmansyahUniversity of Brawijaya1
Ria FebriyanaUniversity of Brawijaya1
Vitara Nindya Putri HasanUniversity of Brawijaya1
Mohammad Zoqi SarwaniUniversity of Brawijaya1
Luthfi HidayatUniversity of Brawijaya1
Rifki Setya ArmandaUniversity of Brawijaya1
Garsinia Ely RianiUniversity of Brawijaya1
Fita Lathifatul Mu’asyarohAffiliation unknown1
Agus Wahyu WidodoUniversity of Brawijaya1
Diva KurnianingtyasUniversity of Brawijaya1
Muchammad Chandra Cahyo UtomoUniversity of Brawijaya1
Farhanna Mar’iUniversity of Brawijaya1
Cleoputri YusainyUniversity of Brawijaya1
Qoirul KotimahUniversity of Brawijaya1
Vivi Nur WijayaningrumUniversity of Brawijaya1
Gayatri Dwi SantikaUniversity of Brawijaya1
Agus NabaUniversity of Brawijaya1

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 Data Mining Methods  for Sexually Transmitted Disease Classification</dc:title><dc:creator>Yuliastuti, Gusti E.</dc:creator><dc:creator>Alfiyatin, Adyan N.</dc:creator><dc:creator>Rizki, Agung M.</dc:creator><dc:creator>Hamdianah, A.</dc:creator><dc:creator>Taufiq, H.</dc:creator><dc:creator>Mahmudy, W. F.</dc:creator><dc:description>&lt;jats:p&gt;According to health reports of Malang city, many people are exposed to sexually transmitted diseases and most sufferers are not aware of the symptoms. Malang city being known as a city of education so that every year the population number increases, it is at risk of increasing the spread of sexually transmitted diseases virus. This problem is important to be solved to treat earlier sufferers sexually transmitted diseases virus in order to reduce the burden of patient spending. In this research, authors conduct data mining methods to classifying sexually transmitted diseases. From the experiment result shows that K-NN is the best method for solve this problem with 90% accuracy.&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.pp3933-3939</dc:identifier><dc:identifier>10.11591/ijece.v8i5.pp3933-3939</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 8 No 5 (2018); 3933</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/9579/9581</dc:relation><dc:rights>http://creativecommons.org/licenses/by-nc/4.0</dc:rights></oai_dc:dc>