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All Journal Prosiding Seminar Nasional Official Statistics PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS
Nofita Istiana
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Humanities Computer Science & IT Economics, Econometrics & Finance Social Sciences

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Application of Small Area Estimation for Estimating Households Living in Adequate Housing at the Subdistrict Level in DKI Muhammad Akbar; Nofita Istiana
Joint International Conference 2026: The 2nd Indonesia Forum on Labour and Productivity (IFLP) & The 4th International Conference on Data Science and Official Statistics (ICDSOS) Vol. 2025 No. 1 (2025): Proceedings of 2025 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2025i1.497

Abstract

Access to adequate housing is a right of all Indonesian citizens guaranteed by the 1945 Constitution and is part of the Sustainable Development Goals (SDGs), specifically Goal 11. DKI Jakarta is the province with the second-lowest percentage of households living in adequate housing in Indonesia. Estimation at the subdistrict level is needed to support the policy on affordable vertical housing development initiated by the DKI Jakarta Department of Public Housing and Settlement Areas. Direct estimation at the subdistrict level based on the Susenas sampling design would result in inaccurate estimators. To address this issue, this study applies the Small Area Estimation (SAE) method using the Empirical Best Linear Unbiased Prediction (EBLUP) model and the Hierarchical Bayes (HB) Beta model, which leverage auxiliary variables to improve precision. The findings reveal that the HB Beta model provides the best estimates in measuring the percentage of households living in adequate housing in DKI Jakarta in 2024, producing accurate estimates across all subdistricts
Pendugaan Tingkat Kemiskinan Disabilitas Jawa Tengah 2025: Perbandingan EBLUP Transformasi Logit dan HB Beta Wisnu Aimariyadi; Nofita Istiana
Seminar Nasional Official Statistics Vol 2026 No 1 (2026): Seminar Nasional Official Statistics 2026
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2026i1.2747

Abstract

Direct estimation of the percentage of poor persons with disabilities at the regency/city level often has low precision due to limited sample sizes. This study compares Small Area Estimation (SAE) using Empirical Best Linear Unbiased Prediction (EBLUP) with logit transformation and Hierarchical Bayes (HB) with a Beta distribution across 35 regencies/cities in Central Java in 2025. Direct estimation yielded an average RSE of 42.86%, with 22 areas classified as poor and one area without an estimate. The application of SAE improved precision and produced estimates for all areas. EBLUP with logit transformation yielded an average RSE of 20.02%, with 30 areas classified as good, while HB Beta yielded an average RSE of 18.99%, with 31 areas classified as good. However, the random effects and residuals of the EBLUP logit model did not satisfy the normality assumption. Overall, HB Beta demonstrated better performance in terms of estimation precision and model suitability for proportional data.
Co-Authors Muhammad Akbar Wisnu Aimariyadi