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Penerapan Penduga Area Kecil untuk Menduga Pengeluaran Per Kapita di Provinsi Jawa Barat melalui Metode Empirical Best Linear Unbiased Prediction

Authors: Giatri Divianis; Nusar Hajarisman;

Penerapan Penduga Area Kecil untuk Menduga Pengeluaran Per Kapita di Provinsi Jawa Barat melalui Metode Empirical Best Linear Unbiased Prediction

Abstract

Abstract. A research small sample will lead to errors which gets unexpected stats and precision. So as be solved by direct estimation. However, direct estimation provides insufficient accuracy resulting in large variance. But, can be overcome by estimating small area using Empirical Best Linear Unbiased Prediction (EBLUP) method by borrowing information data from surrounding area. Output evaluation’s by comparing Relative Root Mean Square Error (RRMSE). It’s used in Per Capita Expenditure in West Java. Presentation of Expenditure Per Capita data by BPS still limited in district/city level. The data’s obtained from National Socio-Economic Survey (SUSENAS) of BPS 2021 with household-based information Expenditures as a response variable and companion variables from BPS West Java in Figures 2022, namely Health Facilities, Motorcycle Users, Education Participants, Beneficiary Families, Education Facilities , and Manpower in Micro and Small Industries. With analysis stage, normality test and homoscedasticity test of Per Capita Expenditure then Correlation Test of Per Capita Expenditure value with companion variables, estimating , random effect ( ) and random effect variance ( ), then normality test and homoscedasticity test of influence random ( ), estimates value of EBLUP ( ), calculate RRMSE of two estimators. The RRMSE results from EBLUP estimator are smaller, RRMSE average of 0.23566 compared Direct Estimator's RRMSE average of 0.27016. So, Small Area Estimator of the EBLUP method in Per Capita Expenditure in West Java is better than the result of the Direct Estimator. Abstrak. Suatu penelitian jika memiliki sampel sedikit akan menimbulkan kesalahan dimana memperoleh statistik dan presisi yang tidak diharapkan. Sehingga dapat diatasi dengan pendugaan secara langsung namun, pendugaan langsung memberikan ketelitian yang tidak cukup sehingga menghasilkan varian besar. Tetapi dapat diatasi dengan pendugaan area kecil metode Empirical Best Linear Unbiased Prediction (EBLUP) dengan meminjam data informasi di area sekitar. Evaluasi output dilakukan dengan membandingkan nilai Relative Root Mean Square Error (RRMSE). Hal ini dimanfaatkan pada Pengeluaran Per Kapita di Provinsi Jawa Barat. Penyajian data Pengeluaran Per Kapita oleh BPS masih terbatas pada level kabupaten/kota. Data yang diperoleh dari Survei Sosial Ekonomi Nasional (SUSENAS) BPS 2021 dengan variabel respon Pengeluaran,Per Kapita informasi berbasis Rumah Tangga serta variabel penyerta dari BPS Jawa Barat dalam Angka 2022 yakni Sarana Kesehatan, Pengguna Sepeda Motor, Penempuh Pendidikan, Keluarga Penerima Manfaat, Fasilitas Pendidikan, dan Tenaga Kerja pada Industri Mikro dan Kecil. Dengan tahapan analisis melakukan uji normalitas dan uji homoskedastis Pengeluaran Per Kapita lalu Uji Korelasi nilai Pengeluaran Per Kapita dengan variabel penyerta, pendugaan , pengaruh acak ( ) dan varian pengaruh acak ( ), kemudian uji normalitas dan uji homoskedastisitas pengaruh acak ( ), menduga nilai EBLUP ( ), menghitung RRMSE dari kedua penduga, lalu membandingkannya. Hasil RRMSE penduga EBLUP lebih kecil dengan rata-rata RRMSE sebesar 0,23566 dibandingkan Penduga Langsung diperoleh rata-rata RRMSE sebesar 0,27016. Maka, Penduga Area Kecil metode EBLUP dalam Pengeluaran Per Kapita di Provinsi Jawa Barat lebih baik dibandingkan hasil Penduga Langsung.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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