SMALL AREA ESTIMATION PADA TINGKAT KEMISKINAN DI PROVINSI JAWA TENGAH DENGAN PENDEKATAN EMPIRICAL BEST LINIER UNBIASED PREDICTION
| Main Authors: | Wijaya, Arianto, Darsyah, Moh. Yamin, Suprayitno, Iswahyudi Joko |
|---|---|
| Format: | Article info application/pdf eJournal |
| Bahasa: | eng |
| Terbitan: |
Universitas Muhammadiyah Semarang
, 2017
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| Online Access: |
https://jurnal.unimus.ac.id/index.php/psn12012010/article/view/2978 https://jurnal.unimus.ac.id/index.php/psn12012010/article/view/2978/2897 |
Daftar Isi:
- Poverty is a complex problem for every country, similar to Indonesia. Poverty isone of the important measures to determine the level of welfare of a household.Factors that cause poverty include low income, the number of familydependents, health, and education levels that characterize poor families inIndonesia. The purpose of this research is to know the level of impact atdistricts level in Central Java Province by using Small Area Estimation (SAE)method with Empirical Best Linier Prediction (EBLUP) approach. The dataused in this research are poverty data obtained from SUSENAS of Central JavaProvince with the response variable that is the number of poor population,while as the participant variable is selected gross enrollment rate (X1), schoolparticipation rate (X2), health insurance (X3), goods per capita (X4) and lifeexpectancy (X5). The results of the MSE study of the SAE model were smallerthan the direct predicted MSE, indicating the SAE model was better than thedirect estimates in the estimated number of poor people in each district inCentral Java Province.Keywords : Poverty Rate, SAE and EBLUP.