Jurnal Aplikasi Statistika & Komputasi Statistik
Vol 17 No 2 (2025): Jurnal Aplikasi Statistika & Komputasi Statistik

Implementation of Twofold HB Beta SAE Model to Estimate Out-of-School Children with Disabilities in Indonesia

Maharani, Aisha (Unknown)
Ubaidillah, Azka (Unknown)
Adhi Kurniawan (Unknown)



Article Info

Publish Date
31 Dec 2025

Abstract

Introduction/Main Objectives: The high percentage of out-of-school children with disabilities in Indonesia reveals a significant gap in educational participation. Background Problems: Due to the absence of disability-focused surveys, accurate data are only available at the national level, which is insufficient to represent regional conditions. Novelty: With the increasing demand for small area data, this study estimates the percentage of out-of-school children with disabilities at the provincial and district levels simultaneously, using small area estimation (SAE). Research Methods: This study applies SAE using a twofold subarea-level model with a Hierarchical Bayes (HB) beta approach, covering all 34 provinces and 514 districts/cities in Indonesia. This model was developed using data from the National Socio-Economic Survey (Susenas) and the Village Potential Statistics (Podes). Finding/Results: The twofold HB beta SAE model achieves higher precision than direct estimation, as shown by lower relative standard errors (RSE) across regions. Furthermore, spatial patterns indicate that the percentage of out-of-school children with disabilities is mostly between 35.36% and 45.34%, with clusters concentrated in Kalimantan and Papua.

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Journal Info

Abbrev

jurnalasks

Publisher

Subject

Computer Science & IT Decision Sciences, Operations Research & Management Mathematics

Description

Redaksi menerima karya ilmiah atau artikel penelitian mengenai kajian teori statistika dan komputasi statistik pada bidang ekonomi dan sosial dan kependudukan, serta teknologi informasi. Redaksi berhak menyunting tulisan tanpa mengubah makna subtansi tulisan. Isi jurnal Aplikasi Statistika dan ...