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Socioeconomic determinants of blue-collar employment in West Java Province: A binary logistic regression approach

Jurnal Perspektif Pembiayaan dan Pembangunan Daerah · Vol. 13 No. 4 (2025) · pp. 398–413

DOI
10.22437/ppd.v13i4.43213
ISSN
2355-8520, 2338-4603
Published
2025-10-31
Publisher
Program Magister Ilmu Ekonomi Pascasarjana Universitas Jambi
Language
en
License
creativecommons.org/licenses/by/4.0

Abstract

Employment issues remain a persistent national challenge in Indonesia, particularly in West Java Province, which has a high concentration of blue-collar workers. These workers, typically engaged in manual and technical sectors, often face structural vulnerabilities, including low job security, limited social protection, wage stagnation, and restricted career advancement opportunities. This study aims to analyze the characteristics and determinants influencing individuals’ likelihood of becoming blue-collar workers in West Java Province. Using a quantitative approach, the research draws on microdata from the 2022 National Labor Force Survey (SAKERNAS) provided by Statistics Indonesia (BPS). A binary logistic regression model is employed to examine how individual and employment-related characteristics affect the probability of working in blue-collar occupations. The results show that gender, marital status, education level, job training, participation in the Pre-employment Card program, age group, regional minimum wage category, and area classification significantly influence this likelihood. Notably, individuals with lower educational attainment are 2.9 times more likely to become blue-collar workers. The findings underscore the critical role of education in shaping labor market segmentation. Strengthening the education, vocational training, and Pre-employment Card ecosystem is essential to reduce the vulnerability of blue-collar workers and expand their access to decent, inclusive employment opportunities.

Keywords

Collaboration network of the authors

15 authors · 28 co-authorship links · 1 across different organisations

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  • Universitas Stikubank
  • Universitas Gadjah Mada
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Co-authorOrganisationJoint articles
Sri Budi Cantika YuliAffiliation unknown2
Stanislaw FlejterskiAffiliation unknown2
Herny FebruariyantiUniversitas Stikubank1
Jati Sasongko WibowoAffiliation unknown1
Mardi Siswo UtomoUniversitas Gadjah Mada1
Immanuel Mu'ammalAffiliation unknown1
Arini Roro Anggun TsalasaAffiliation unknown1
Haryadi HaryadiAffiliation unknown1
Etik UmiyatiAffiliation unknown1
Zainal ArifinAffiliation unknown1
Fika FitriasariAffiliation 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://online-journal.unja.ac.id/index.php/JES/oai, first harvested 6 Nov 2026, last seen 8 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en">Socioeconomic determinants of blue-collar employment in West Java Province: A binary logistic regression approach</dc:title>
	<dc:creator xml:lang="en">Subastian, Alvin</dc:creator>
	<dc:creator xml:lang="en">Riyanto, Wahyu Hidayat</dc:creator>
	<dc:creator xml:lang="en">Putranto, FX Gugus Febri</dc:creator>
	<dc:creator xml:lang="en">Firmansyah, Muhammad</dc:creator>
	<dc:subject xml:lang="en">Binary logistic regression</dc:subject>
	<dc:subject xml:lang="en">Blue-collar employment</dc:subject>
	<dc:subject xml:lang="en">Labor market segmentation</dc:subject>
	<dc:description xml:lang="en">Employment issues remain a persistent national challenge in Indonesia, particularly in West Java Province, which has a high concentration of blue-collar workers. These workers, typically engaged in manual and technical sectors, often face structural vulnerabilities, including low job security, limited social protection, wage stagnation, and restricted career advancement opportunities. This study aims to analyze the characteristics and determinants influencing individuals’ likelihood of becoming blue-collar workers in West Java Province. Using a quantitative approach, the research draws on microdata from the 2022 National Labor Force Survey (SAKERNAS) provided by Statistics Indonesia (BPS). A binary logistic regression model is employed to examine how individual and employment-related characteristics affect the probability of working in blue-collar occupations. The results show that gender, marital status, education level, job training, participation in the Pre-employment Card program, age group, regional minimum wage category, and area classification significantly influence this likelihood. Notably, individuals with lower educational attainment are 2.9 times more likely to become blue-collar workers. The findings underscore the critical role of education in shaping labor market segmentation. Strengthening the education, vocational training, and Pre-employment Card ecosystem is essential to reduce the vulnerability of blue-collar workers and expand their access to decent, inclusive employment opportunities.</dc:description>
	<dc:publisher xml:lang="en">Program Magister Ilmu Ekonomi  Pascasarjana Universitas Jambi</dc:publisher>
	<dc:date>2025-10-31</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://online-journal.unja.ac.id/JES/article/view/43213</dc:identifier>
	<dc:identifier>10.22437/ppd.v13i4.43213</dc:identifier>
	<dc:source xml:lang="en">Jurnal Perspektif Pembiayaan dan Pembangunan Daerah; Vol. 13 No. 4 (2025): Jurnal Perspektif Pembiayaan dan Pembangunan Daerah; 398-413</dc:source>
	<dc:source>2355-8520</dc:source>
	<dc:source>2338-4603</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://online-journal.unja.ac.id/JES/article/view/43213/22360</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2025 Alvin Subastian, Wahyu Hidayat Riyanto, FX Gugus Febri Putranto, Muhammad Firmansyah</dc:rights>
	<dc:rights xml:lang="en">https://creativecommons.org/licenses/by/4.0</dc:rights>
</oai_dc:dc>