2019 ◽  
Vol 1317 ◽  
pp. 012006
Author(s):  
Ferra Yanuar ◽  
Nadya Cindy Eka Putri ◽  
Hazmira Yozza

2019 ◽  
Vol 8 (1) ◽  
pp. 120
Author(s):  
Nurmaylina Zaja ◽  
Hazmira Yozza ◽  
Ferra Yanuar

Penelitian ini bertujuan untuk menduga angka pengangguran di kabupaten/kota di Sumatea Barat dengan metode Small Area Estimation dengan pendekatan Empirical Bayes berbasis model Beta-Binomial. hal ini dilakukan karena informasi yang dikeluarkan oleh Badan pusat Statistik (BPS) tahun 2016 hanya angka pengangguran tingkat provinsi dan tidak tersedia data untuk tingkat kabupaten/kota. Penelitian ini menggunakan data BPS, yaitu jumlah pengangguran dan jumlah angkatan kerja di kabupaten/kota di Sumatera Barat. Penelitian ini menghasilkan nilai dugaan angka pengangguran kabupaten/kota di Sumatera Barat dengan metode langsung dan metode Empirical Bayes. Dengan demikian dapat disimpulkan bahwa penduga menggunakan metode Empirical Bayes lebih baik dari metode langsung.Diterima: Direvisi: Dipublikasikan :Kata Kunci: Small Area Estimation, Empirical Bayes, Angka Pengangguran.


2021 ◽  
Vol 10 (2) ◽  
pp. 81
Author(s):  
REYNALDO PANJI WICAKSONO ◽  
I KOMANG GDE SUKARSA ◽  
I PUTU EKA NILA KENCANA

Economic development are described by the unemployment rate. The higher unemployment rate, the weaker economic conditions. Nowadays more policies require information on small areas. The direct estimation does not provide accurate results in smaller areas. Thus the small area estimation becomes an alternative to estimate the parameters. The accuracy depends on the selection of the predictors. In 2019, the unemployment rate in Denpasar is 2,22%. The result shows that the unemployment rate in each district in Denpasar varies from 0,1% to 0,3%


2021 ◽  
Vol 3 (2) ◽  
pp. 78
Author(s):  
Husna Afanyn Khoirunissa

<p>Tuberculosis is an infectious disease that can attack human with a poor immune system. In 2017, there were 723 residents of Surakarta tested positive for tuberculosis. The spatial empirical Bayes method is a good method for mapping the risk of tuberculosis because this method includes spatial dependency information and can overcome small area problems. This method can help the prevention of tuberculosis in Surakarta. In the analysis, it was found that the number of cases of tuberculosis in Surakarta has a spatial dependency that has an impact of the spread of tuberculosis. Sub-district classification with the highest risk value is Jebres, Tegalharjo, Jajar, Laweyan, Sondakan, Purwosari, Mangkubumen, Keratonan, Timuran, and Punggawan.</p><p><strong>Keywords</strong> : tuberculosis, mapping, spatial empirical Bayes, Surakarta</p>


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