SMALL AREA ESTIMATION DENGAN METODE EBLUP FAY-HERRIOT PADA TINGKAT KEMISKINAN DI PROVINSI SUMATERA UTARA
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Date
2021-07
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perpustakaan UR
Abstract
National socio-economic survey in March 2019 showed that the number of poor people
in North Sumatra Province was 1,282 million people or 8,83 percent of the total
population. The number of poor people and the percentage of poor people are obtained
by direct estimation based on the survey conducted. Direct estimation in a small area has
a poor accuracy because the estimator have a large variance. The method that can be used
to solve this problem is indirect estimation with Small Area Estimation (SAE). This study
uses SAE with the Empirical Best Linear Unbiased Prediction (EBLUP) Fay-Herriot
method to estimate the parameter of the poverty level in North Sumatra Province by city.
The data used is the poverty percentage of 33 cities using seven co-variables namely the
human development index, gross enrollment ratio for elementary, junior, high school, and
college, income per capita, and life expectancy in North Sumatra Province obtained from
the survey results from the BPS. This study shows that SAE with the EBLUP Fay-Herriot
method produces a better estimation value than the direct estimation
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Keywords
Direct estimation, small area estimation, empirical best linear unbiased prediction, Fay-Herriot model