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The Utility of Decision Tree and Analytics Hierarchy Process in Prioritizing of Social Aid Distribution due to Covid-19 Pandemic in Indonesia

Journal of ICT Research and Applications (JICTRA) · Vol. 17 No. 1 (2023) · pp. 82–98

DOI
10.5614/itbj.ict.res.appl.2023.17.1.6
ISSN
2338-5499, 2337-5787
Published
2023-04-30
Publisher
DRI - ITB
Language
eng

Abstract

The Indonesian government provided various social assistance programs to local governments during Covid-19. One of the difficulties for the local governments in determining candidates for social aid is ensuring that the number of candidates is in balance with the available quota. Therefore, the local governments must select the most eligible candidates. This study proposes a priority model that can provide recommendations for candidates who meet the criteria for social assistance. The six parameters used in this study were: number of dependents, occupation, income, age, Covid status, and citizen status. The model operates in two stages, namely classification followed by ranking. The classification stage is conducted using a decision tree, while the ranking stage is performed conducted using the Analytical Hierarchy Process (AHP) algorithm. The decision tree separates two classes, namely, eligible and non-eligible. In addition, the classification process is also used to determine the dominant attributes and played a role in the modeling. The proposed model generates a list of the most eligible candidates based on our research. These are sorted by weight from greatest to most eligible using five dominant parameters: number of dependents, income, age, Covid status, and citizen status.

Keywords

Collaboration network of the authors

26 authors · 65 co-authorship links · 35 across different organisations

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

  • Mulawarman University
  • Universitas Gadjah Mada
  • Universitas Teknologi Yogyakarta
  • Sunan Kalijaga State Islamic University Yogyakarta
  • Musamus Merauke University
  • Universitas Respati Yogyakarta
  • STMIK Banjarbaru
  • Other organisations
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Hamdani HamdaniMulawarman University5
Dyna Marisa KhairinaMulawarman University2
Agus Qomaruddin MunirUniversitas Respati Yogyakarta2
Budi RahmaniSTMIK Banjarbaru2
Heru IsmantoMusamus Merauke University2
Andri SyafriantoSTMIK El Rahma Yogyakarta2
Didit SuprihantoMulawarman University2
M IhsanAffiliation unknown1
Ahmad Tri HidayatUniversitas Teknologi Yogyakarta1
Adhistya Erna PermanasariUniversitas Gadjah Mada1
Indriana HidayahUniversitas Gadjah Mada1
Tundo TundoSunan Kalijaga State Islamic University Yogyakarta1
Riolandi AkbarSunan Kalijaga State Islamic University Yogyakarta1
Agus HarjokoUniversitas Gadjah Mada1
Retantyo WardoyoUniversitas Gadjah Mada1
Sri T. HartatiUniversitas Gadjah Mada1
Munakhir MudjosemediUniversitas Gadjah Mada1
Ummul HairahMulawarman University1
Novianti PuspitasariMulawarman University1
Andi TejawatiMulawarman University1
Surya Eka PriyatnaUniversitas Islam Negeri Antasari Banjarmasin1

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://journals.itb.ac.id/index.php/jictra/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">The Utility of Decision Tree and Analytics Hierarchy Process in Prioritizing of Social Aid Distribution due to Covid-19 Pandemic in Indonesia</dc:title>
	<dc:creator>Diwandari, Saucha</dc:creator>
	<dc:creator>Sela, Enny Itje</dc:creator>
	<dc:creator>Syahputra, Briyan Efflin</dc:creator>
	<dc:creator>Parama, Nathaniela Aptanta</dc:creator>
	<dc:creator>Septiarini, Anindita</dc:creator>
	<dc:subject xml:lang="en-US">analytical hierarchy process</dc:subject>
	<dc:subject xml:lang="en-US">classification</dc:subject>
	<dc:subject xml:lang="en-US">decision tree</dc:subject>
	<dc:subject xml:lang="en-US">ranking</dc:subject>
	<dc:subject xml:lang="en-US">social aid</dc:subject>
	<dc:description xml:lang="en-US">The Indonesian government provided various social assistance programs to local governments during Covid-19. One of the difficulties for the local governments in determining candidates for social aid is ensuring that the number of candidates is in balance with the available quota. Therefore, the local governments must select the most eligible candidates. This study proposes a priority model that can provide recommendations for candidates who meet the criteria for social assistance. The six parameters used in this study were: number of dependents, occupation, income, age, Covid status, and citizen status. The model operates in two stages, namely classification followed by ranking. The classification stage is conducted using a decision tree, while the ranking stage is performed conducted using the Analytical Hierarchy Process (AHP) algorithm. The decision tree separates two classes, namely, eligible and non-eligible. In addition, the classification process is also used to determine the dominant attributes and played a role in the modeling. The proposed model generates a list of the most eligible candidates based on our research. These are sorted by weight from greatest to most eligible using five dominant parameters: number of dependents, income, age, Covid status, and citizen status.</dc:description>
	<dc:publisher xml:lang="en-US">DRI - ITB</dc:publisher>
	<dc:date>2023-04-30</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:type xml:lang="en-US">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journals.itb.ac.id/index.php/jictra/article/view/18893</dc:identifier>
	<dc:identifier>10.5614/itbj.ict.res.appl.2023.17.1.6</dc:identifier>
	<dc:source xml:lang="en-US">Journal of ICT Research and Applications; Vol. 17 No. 1 (2023); 82-98</dc:source>
	<dc:source>2338-5499</dc:source>
	<dc:source>2337-5787</dc:source>
	<dc:source>10.5614/itbj.ict.res.appl.2022.17.1</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journals.itb.ac.id/index.php/jictra/article/view/18893/6172</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2023 Journal of ICT Research and Applications</dc:rights>
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