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All Journal Jurnal Litbang Sukowati : Media Penelitian dan Pengembangan Inferensi
Erwin Tanur
Badan Pusat Statistik, Indonesia
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Mathematics Social Sciences

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DI BALIK ANGKA POU: MENGUNGKAP PERAN FAKTOR SOSIAL EKONOMI DALAM KETAHANAN PANGAN Dian Nahryah; Erwin Tanur
Jurnal Litbang Sukowati : Media Penelitian dan Pengembangan Vol 10 No 1 (2026): Vol. 10 No. 1, Mei 2026
Publisher : Badan Perencanaan Pembangunan, Riset dan Inovasi Daerah Kabupaten Sragen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32630/sukowati.v10i1.2297

Abstract

The Prevalence of Undernourishment (PoU) is an important indicator for assessing a region’s food security. PoU reflects not only food availability but also the population’s ability to access and consume nutritious food. Data from 2024 show considerable variation in PoU levels across districts and cities in Indonesia, indicating differences in socioeconomic conditions among regions. These disparities highlight the need to examine the socioeconomic factors influencing PoU at the regional level. This study aims to analyze the influence of socioeconomic factors on PoU levels in 514 districts and cities in Indonesia in 2024. The data were obtained from publications of Statistics Indonesia (BPS) and analyzed using binary logistic regression to identify variables that significantly affect the likelihood of undernourishment. The results show that poverty rate, Human Development Index (HDI), and access to improved drinking water have significant effects on PoU. Regions with better welfare and basic services tend to have lower PoU levels. These findings emphasize the importance of policies focusing on poverty reduction, human development improvement, and equitable access to basic services to strengthen regional food security sustainably. Keywords: Poverty, Human Development Index (HDI).
Small Area Estimation of Child Poverty on Java Island In 2021 (Comparison of EBLUP and Hierarchical Bayes) Nofita Istiana; Erwin Tanur; Azka Ubaidillah; Yuliana Ria Uli Sitanggang; Rosalinda Nainggolan
Inferensi Vol 8 No 3 (2025)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v8i3.23311

Abstract

Information about child poverty is very important to ensure that children get their rights. Indonesia's decentralized system requires child poverty data in each district/city. Data provision at this level is constrained by a non-specific sample design used for certain age groups, so the sample age group for children is not always sufficient for each district/city. Therefore, direct estimation produces a high relative standard error (RSE), so it requires small area estimation (SAE). SAE that is often used is EBLUP, which assumes that the variable of interest is normally distributed. Child poverty data does not meet the normality assumption, so SAE with Hierarchical Bayes with Beta distribution (HB Beta) is proposed in this study. The result is direct estimation, EBLUP, and HB Beta produce relatively similar estimated values, but HB Beta has the lowest RSE.
Co-Authors Azka Ubaidillah Dian Nahryah Nofita Istiana Rosalinda Nainggolan Yuliana Ria Uli Sitanggang