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APLIKASI DATA MINING UNTUK PENILAIAN KREDIT MENGGUNAKAN DECISION TREE ALGORITMA ID3 STUDI KASUS PT. MANDALA MULTI FINANCE CABANG KENDARI

SemanTIK: Teknik Informasi · Vol. 4 No. 1 (2018) · pp. 65–76

DOI
10.55679/semantik.v4i1.4251
ISSN
2502-8928, 2460-1446
Published
2018-07-11
Publisher
Informatics Engineering Department of Halu Oleo University
Language
eng

Abstract

Credit is one of the most common payment mechanisms in the community. Data mining can search the pattern and new knowledge of these data so that it can facilitate in determination of debtor candidate. For that required a data mining applications that can process and provide the decision of the prospective debtor's eligibility status automatically. One method of data mining used for the classification of prospective borrowers is the decision tree using Iterative Algorithm Dichotomiser 3 (ID3).ID3 is one of the most popular types of Decision trees that attempt to build a decision tree top-down, starting with the first attribute to be checked and placed as root. The ID3 or Iterative Dichotomiser 3 algorithm is a method used to produce decision trees that are able to classify an object. Attributes used are file, job, character, address, pay slip, and motor price.Based on the test results, ID3 method can be implemented in credit appraisal application for the determination of eligibility with 100% accuracy value for 10 data testing from 100 training data and 30 data testing from 60 training data.Keywords—Credit, Data Mining, Decision Tree, ID3 DOI: 10.5281/zenodo.1402830

Collaboration network of the authors

40 authors · 119 co-authorship links · 4 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 Halu Oleo
  • 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
Natalis RansiUniversitas Halu Oleo8
Adha Mashur SajiahUniversitas Halu Oleo7
La SurimiUniversitas Halu Oleo5
Sutardi SutardiUniversitas Halu Oleo5
Bambang PramonoUniversitas Halu Oleo4
LM. Fid AksaraUniversitas Halu Oleo4
ARMAN FASLIHAffiliation unknown4
Isnawaty IsnawatyAffiliation unknown2
Arman ArmanUniversitas Halu Oleo2
Rahmat RamadhanUniversitas Halu Oleo2
Halim HalimUniversitas Halu Oleo2
L.M. Fid AksaraUniversitas Halu Oleo2
Muhammad Zakaria UmarAffiliation unknown2
Andi TenriawaruUniversitas Halu Oleo1
Wa Ode IrmayadaniUniversitas Halu Oleo1
Nurul Hajra Hadijah HajraUniversitas Halu Oleo1
Asri SamsudinUniversitas Halu Oleo1
Rizal Adi SaputraUniversitas Halu Oleo1
Amaliya Nurani BasyarahAffiliation unknown1
Umar RamdaniUniversitas Halu Oleo1
LM Bahtiar AksaraAffiliation unknown1
Restu Hadi SaputraAffiliation unknown1
Feri FadlinAffiliation unknown1
Suparjo SuparjoAffiliation unknown1
Edi CahyonoUniversitas Halu Oleo1
Ayu Septiana SariAffiliation unknown1
Uun Amalia RamadhaniUniversitas Halu Oleo1
Muh Iskandar Z. AAffiliation unknown1
Wahyuddin AluddinUniversitas Halu Oleo1
Dewi Dessy SupraptiAffiliation unknown1
Adnan HidayatUniversitas Halu Oleo1
Muh. Ihsan SaritaUniversitas Halu Oleo1
Djafar DjafarAffiliation unknown1
Nurfanny La BennyAffiliation unknown1
Siti Hartinah IndriantiAffiliation unknown1
Rezki OktaviaAffiliation unknown1
Muh. SaifulUniversitas Halu Oleo1

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://ojs.uho.ac.id/index.php/semantik/oai, first harvested 29 Okt 2026, last seen 1 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">APLIKASI DATA MINING UNTUK PENILAIAN KREDIT MENGGUNAKAN DECISION TREE ALGORITMA ID3 STUDI KASUS PT. MANDALA MULTI FINANCE CABANG KENDARI</dc:title>
	<dc:creator>Ilayani, Ilayani</dc:creator>
	<dc:creator>Nangi, Jumadil</dc:creator>
	<dc:creator>Pasrun, Yuwanda Purnamasari</dc:creator>
	<dc:description xml:lang="en-US">Credit is one of the most common payment mechanisms in the community. Data mining can search the pattern and new knowledge of these data so that it can facilitate in determination of debtor candidate. For that required a data mining applications that can process and provide the decision of the prospective debtor's eligibility status automatically. One method of data mining used for the classification of prospective borrowers is the decision tree using Iterative Algorithm Dichotomiser 3 (ID3).ID3 is one of the most popular types of Decision trees that attempt to build a decision tree top-down, starting with the first attribute to be checked and placed as root. The ID3 or Iterative Dichotomiser 3 algorithm is a method used to produce decision trees that are able to classify an object. Attributes used are file, job, character, address, pay slip, and motor price.Based on the test results, ID3 method can be implemented in credit appraisal application for the determination of eligibility with 100% accuracy value for 10 data testing from 100 training data and 30 data testing from 60 training data.Keywords—Credit, Data Mining, Decision Tree, ID3 DOI : 10.5281/zenodo.1402830</dc:description>
	<dc:publisher xml:lang="en-US">Informatics Engineering Department of Halu Oleo University</dc:publisher>
	<dc:contributor xml:lang="en-US"></dc:contributor>
	<dc:date>2018-07-11</dc:date>
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	<dc:identifier>https://ojs.uho.ac.id/index.php/semantik/article/view/4251</dc:identifier>
	<dc:identifier>10.55679/semantik.v4i1.4251</dc:identifier>
	<dc:source xml:lang="en-US">SemanTIK : Teknik Informasi; Vol 4, No 1 (2018): semanTIK; 65-76</dc:source>
	<dc:source>2502-8928</dc:source>
	<dc:source>2460-1446</dc:source>
	<dc:source>10.55679/semantik.v4i1</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs.uho.ac.id/index.php/semantik/article/view/4251/3404</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2018 semanTIK</dc:rights>
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