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

Alvin Subastian; Wahyu Hidayat Riyanto; FX Gugus Febri Putranto; Muhammad Firmansyah

doi:10.22437/ppd.v13i4.43213

Authors

Alvin Subastian Department of Economic Development, Faculty of Economics and Business, Universitas Muhammadiyah Malang, Indonesia
Wahyu Hidayat Riyanto Department of Economic Development, Faculty of Economics and Business, Universitas Muhammadiyah Malang, Indonesia
FX Gugus Febri Putranto Statistics Indonesia (Badan Pusat Statistik) – Batu Municipality, Indonesia
Muhammad Firmansyah Department of Economic Development, Faculty of Economics and Business, Universitas Muhammadiyah Malang, Indonesia

DOI:

https://doi.org/10.22437/ppd.v13i4.43213

Keywords:

Binary logistic regression, Blue-collar employment, Labor market segmentation

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.

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