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All Journal Jurnal Statistika Universitas Muhammadiyah Semarang
Riski Tommi Mardoni
Politeknik Statistika STIS, Indonesia
Decision Sciences, Operations Research & Management

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Application of Empirical Best Linear Unbiased Prediction (EBLUP) in Estimating Labor Force Participation Rate at the Regency/City Level in Kalimantan Island, 2016 Izumi Citra Amelia; Riski Tommi Mardoni; Syofmarlianisyah Putri; Debby Cynthia Ningrum; Iftina Ika Rahmawati; Cucu Sumarni
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 13, No 2 (2025): Jurnal Statistika Universitas Muhammadiyah Semarang
Publisher : Department Statistics, Faculty Mathematics and Natural Science, UNIMUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jsunimus.13.2.2025.85-97

Abstract

The Labor Force Participation Rate (LFPR) serves as a vital indicator for labor market planning, particularly in Kalimantan, a region experiencing sustained economic growth. In 2016, however, regency- and city-level LFPR data were unavailable due to a reduced sample size in the National Labor Force Survey. This study employs Small Area Estimation (SAE) using the Empirical Best Linear Unbiased Prediction (EBLUP) method to estimate LFPR at the sub-provincial level. Auxiliary variables include the number of vocational high schools (SMK), the proportion of villages receiving foreign aid, the share of trade-related enterprises, and the number of villages with migrant workers. Findings indicate that SAE-EBLUP produces estimates with lower relative standard errors (RSE) than direct estimation, offering improved precision for small-area LFPR estimates.
Co-Authors Cucu Sumarni Debby Cynthia Ningrum Iftina Ika Rahmawati Izumi Citra Amelia Syofmarlianisyah Putri