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All Journal Jurnal Ketenagakerjaan Prosiding Seminar Nasional Official Statistics
Taly Purwa
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Humanities Computer Science & IT Economics, Econometrics & Finance Law, Crime, Criminology & Criminal Justice Social Sciences

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PENERAPAN MODEL SPATIAL LOGIT-NORMAL PADA SMALL AREA ESTIMATION DENGAN METODE HIERARCHICAL BAYES Taly Purwa
Seminar Nasional Official Statistics Vol 2019 No 1 (2019): Seminar Nasional Official Statistics 2019
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (364.034 KB) | DOI: 10.34123/semnasoffstat.v2019i1.42

Abstract

Penelitian ini menerapkan model Spatial Logit-normal pada Small Area Estimation (SAE) untuk estimasi proporsi penduduk dengan asupan kalori minimum di bawah 1.400 kkal/kapita/hari pada level kecamatan di Provinsi Bali Tahun 2014 yang merupakan indikator 2.1.2(A) pada tujuan ke-2 SDGs dalam rangka mengukur capaian dan mendukung tercapainya target SDGs pada level lebih tinggi. Terdapat tiga model SAE yang digunakan dengan spesifikasi random effect yang berbeda, yaitu model dengan random effect yang bersifat saling bebas (independen), spatial random effect (iCAR) serta model dengan kedua jenis random effect sekaligus (BYM). Penggunaan unsur spatial random effect diharapkan dapat meningkatkan efisiensi hasil estimasi. Metode estimasi menggunakan pendekatan Hierarchical Bayes (HB) dengan metode Markov Chain Monte Carlo (MCMC) algoritma Gibbs Sampling. Estimasi parameter pada ketiga model menunjukkan hasil yang relatif tidak berbeda dimana hanya ada satu variabel prediktor yang memiliki pengaruh signifikan, yaitu proporsi keluarga pertanian, pada model dengan random effect independen dan model BYM. Sedangkan pada model iCAR tidak ada satu pun variabel prediktor yang berpengaruh signifikan. Berdasarkan nilai Deviance Information Criterion (DIC), model terbaik adalah model BYM. Akan tetapi penambahan unsur spatial random effect bersamaan dengan random effect independen tidak secara signifikan dapat meningkatkan efisiensi hasil estimasi akibat dari minimnya nilai dependensi spasial Moran’s I. Secara visual, pemetaan hasil estimasi dengan model terbaik tidak menunjukkan adanya pola persebaran atau pengelompokan tertentu pada level kecamatan.
The Gig Economy in Different Engines of Growth: Understanding Regional Disparities in Gig Worker Quality in Bali and East Java Putri M, Mustika; Taly Purwa
Jurnal Ketenagakerjaan Vol 20 No 3 (2025): Gig Workers
Publisher : Pusat Pengembangan Kebijakan Ketenagakerjaan Kementerian Ketenagakerjaan Republik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47198/jnaker.v20i3.630

Abstract

Gig work, commonly defined as short-term, more flexible, and non-traditional employment that typically lacks formal contractual arrangements, has shaped the emergence of the gig economy and is gradually transforming labor market dynamics in Indonesia. However, research on gig workers remains limited, particularly in the context of cross-regional comparisons. This study compares the characteristics of gig workers in two regions in Indonesia with different economic structures, i.e., Bali-an economy predominantly driven by tourism-and East Java-an industry-based economy. Using data from the August 2024 National Labor Force Survey, this research employs cluster analysis to reveal the structure of gig workers in each province based on economic, socio-demographic, and technological factors, followed by multilevel regression to identify the odds for being gig workers at individual and regional levels. The findings reveal that gig workers in Bali experience relatively higher levels of wages compared to those in East Java. A similar pattern also exists for the coverage of social protection term. At the individual level, education and sector-industry and services-influence gig workers’ wages across both provinces. While at the regional level, disparities in labor market conditions and minimum wage policies contribute to differences in wage levels. These findings strengthen the understanding of gig economy dynamics across regions with different economic bases, providing valuable policy and strategic insights on expanding social protection and enhancing the use of technology to support the sustainability of labor markets in the digital era.
Co-Authors Putri M, Mustika