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Open access Jurnal SINTA 3

TWOFOLD SUBAREA MODEL FOR ESTIMATING COMMUTER PROPORTION IN 10 METROPOLITAN AREAS

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 18 No. 2 (2024) · pp. 1009–1022

DOI
10.30598/barekengvol18iss2pp1009-1022
ISSN
2615-3017, 1978-7227
Published
2024-05-25
Publisher
PATTIMURA UNIVERSITY
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

The metropolitan area is a major contributor to national GDP. The metropolitan area is a center of attraction for many people who come to earn income as commuters. Commuters are people who carry out work activities in the center of the metropolitan area, which are carried out by residents who live in suburban areas around the center of the metropolitan area and commute regularly every day. The availability of commuter statistics from surveys for presentation level down to the smallest administrative level, such as regencies/municipalities, is unreliable. This happens because this level of presentation has poor precision due to insufficient samples due to the Statistics Indonesia survey design for making estimates at the national and provincial levels. It can be done using small area estimation (SAE) to meet increasing data needs, but existing SAE models can often estimate only at one level. To meet data requests more effectively, a model is needed that can estimate several small areas simultaneously. In SAE, one of the SAE models that can do this is the twofold subarea model. The twofold subarea model produces estimates of the proportion of commuters with good precision at the subarea level (regencies/municipalities) and area level (metropolitan area), with the RRMSE percentage value of the estimated proportion of commuters being below 25% for all regions. The results of this research can be used to present commuter data at the regencies/municipalities level and metropolitan area level where there is a lack of samples and become a new opportunity for Statistics Indonesia to increase statistical production in small areas, which is more effective compared to other SAE methods which have so far been used only to estimate one area level.

Collaboration network of the authors

40 authors · 118 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.

  • IPB University
  • Bandung Islamic University
  • Binus University
  • Universitas Halu Oleo
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Kusman SadikAffiliation unknown5
Erfiani ErfianiAffiliation unknown4
Khairil Anwar NotodiputroBandung Islamic University4
Anwar FitriantoAffiliation unknown4
Muhammad Nur AidiAffiliation unknown3
Aji Hamim WigenaAffiliation unknown3
Bagus SartonoIPB University3
Erwan SetiawanAffiliation unknown2
Asysta Amalia PasaribuBinus University2
Budi SusetyoAffiliation unknown2
Christiana Anggraeni PutriAffiliation unknown2
Zein Rizky SantosoAffiliation unknown1
Vera Maya SantiAffiliation unknown1
Andi Harismahyanti A.Affiliation unknown1
Agus Mohamad SolehIPB University1
Maulida Fajrining TyasAffiliation unknown1
Reni AmeliaAffiliation unknown1
Husnun NashirAffiliation unknown1
Khusnia Nurul KhikmahAffiliation unknown1
Nila LestariAffiliation unknown1
Elisa D JuliantiAffiliation unknown1
Irvanal HaqAffiliation unknown1
Efriwati EfriwatiAffiliation unknown1
Leli LatifahAffiliation unknown1
Titin YuniartyAffiliation unknown1
Dwi Agustin Nuriani SirodjAffiliation unknown1
Gusti Arviana RahmanUniversitas Halu Oleo1
Arie PurwantoAffiliation unknown1
Muhammad Aziz SuprayogiAffiliation unknown1
Joao Ferreira Rendes Bean LolyAffiliation unknown1
Muhammad Azis SuprayogiAffiliation unknown1
I Made SumertajayaAffiliation unknown1
Agus Sofian Eka HidayatAffiliation unknown1
Dian KusumaningrumAffiliation unknown1
Siskarossa Ika OktoraAffiliation unknown1
Dariani MatualageAffiliation unknown1
Asysta Amalia PasaribuAffiliation unknown1

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://ojs3.unpatti.ac.id/index.php/barekeng/oai, first harvested 5 Nov 2026, last seen 5 Nov 2026.
Original metadata (oai_dc)
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	<dc:title xml:lang="en-US">TWOFOLD SUBAREA MODEL FOR ESTIMATING COMMUTER PROPORTION IN 10 METROPOLITAN AREAS</dc:title>
	<dc:creator>Amin, Yudi Fathul</dc:creator>
	<dc:creator>Indahwati, Indahwati</dc:creator>
	<dc:creator>Kurnia, Anang</dc:creator>
	<dc:description xml:lang="en-US">The metropolitan area is a major contributor to national GDP. The metropolitan area is a center of attraction for many people who come to earn income as commuters. Commuters are people who carry out work activities in the center of the metropolitan area, which are carried out by residents who live in suburban areas around the center of the metropolitan area and commute regularly every day. The availability of commuter statistics from surveys for presentation level down to the smallest administrative level, such as regencies/municipalities, is unreliable. This happens because this level of presentation has poor precision due to insufficient samples due to the Statistics Indonesia survey design for making estimates at the national and provincial levels. It can be done using small area estimation (SAE) to meet increasing data needs, but existing SAE models can often estimate only at one level. To meet data requests more effectively, a model is needed that can estimate several small areas simultaneously. In SAE, one of the SAE models that can do this&amp;nbsp;is the twofold subarea model. The twofold subarea model&amp;nbsp;produces estimates of the proportion of commuters with good precision at the subarea level (regencies/municipalities) and area level (metropolitan area), with the RRMSE percentage value of the estimated proportion of commuters being below 25% for all regions. The results of this research can be used to present commuter data at the regencies/municipalities level and metropolitan area level where there is a lack of samples and become a new opportunity for Statistics Indonesia to increase statistical production in small areas, which is more effective compared to other SAE methods which have so far been used only to estimate one area level.</dc:description>
	<dc:publisher xml:lang="en-US">PATTIMURA UNIVERSITY</dc:publisher>
	<dc:date>2024-05-25</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://ojs3.unpatti.ac.id/index.php/barekeng/article/view/11509</dc:identifier>
	<dc:identifier>10.30598/barekengvol18iss2pp1009-1022</dc:identifier>
	<dc:source xml:lang="en-US">BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 18 No 2 (2024): BAREKENG: Journal of Mathematics and Its Application; 1009-1022</dc:source>
	<dc:source>2615-3017</dc:source>
	<dc:source>1978-7227</dc:source>
	<dc:source>10.30598/barekengvol18iss2year2024</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/11509/7850</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2024 Yudi Fathul Amin, Indahwati Indahwati, Anang Kurnia</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>