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Rodliyah, Ratih
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Humanities Computer Science & IT Economics, Econometrics & Finance Social Sciences

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Pendugaan Angka Partisipasi Kasar Pendidikan Anak Usia Dini Berdasarkan Jenis Kelamin dan Level Kabupaten/Kota di Provinsi Jawa Tengah Tahun 2022 dengan Pendekatan Model Hierarchical Bayes Berdistribusi Beta dengan Measurement Error Rodliyah, Ratih; Ubaidillah, Azka
Seminar Nasional Official Statistics Vol 2023 No 1 (2023): Seminar Nasional Official Statistics 2023
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2023i1.1906

Abstract

Quality education is one of the goals of the 2030 Sustainable Development Goals (SDGs). Services to education can be provided from an early age to prepare for further formal education. Susenas produced an estimator of the Gross Enrollment Rate (APK) for Early Childhood Education (PAUD) to describe the capacity of the country's education system to accommodate students in the early age group. Small area statistics urgently needed to create policies that are more right on target. Central Java province has APK PAUD based on sex which is still inadequate for all districts/cities based on the Relative Standard Error (RSE). Therefore, this study applies indirect estimation to improve the precision of the direct estimator using Small Area Estimation (SAE) with measurement error (ME) using Hierarchical Bayes (HB) Normal distribution and Hierarchical Bayes (HB) Beta distribution. The results of this study indicate that the estimated value using the HB ME Beta method is more precise than direct estimation and SAE HB ME Norm estimation.
Implementasi Small Area Estimation Hierarchical Bayes - Beta Difference Benchmark dalam Estimasi NEET Lulusan Perguruan Tinggi Salis, Dian Rahmawati; Japany, Adham Malay; Rodliyah, Ratih; Ibad, Syaikhul; Pulungan, Ridson Al farizal; Ramadhan, Yogi
Seminar Nasional Official Statistics Vol 2024 No 1 (2024): Seminar Nasional Official Statistics 2024
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2024i1.2285

Abstract

The survey data generated by BPS serves as the primary data source for calculating various SDGs indicators. However, not all indicators can be reliably estimated, particularly at detailed disaggregation levels. Some indicators face issues due to sample inadequacy, resulting in high Relative Standard Errors (RSEs) if estimated directly. One such indicator is the percentage of young college graduates who are neither in education, employment, nor training (NEET). This indicator is only available at the provincial level, with disaggregation based on other characteristics only available at national level. Therefore, this study aims to estimate NEET among college graduates at the regency/city level in Sumatra Island for the year 2023 using the SAE HB Beta model. To maintain consistency with direct estimates at the provincial level, which have shown sufficiently low RSEs, a benchmarking process will be conducted using the difference benchmark method. Based on the findings, the difference benchmark method enhances the validity of the estimation results using the SAE HB Beta model.
Co-Authors Ibad, Syaikhul Japany, Adham Malay Pulungan, Ridson Al farizal Salis, Dian Rahmawati Ubaidillah, Azka Yogi Ramadhan