DARSYAH, MOH YAMIN (2013) Small Area Estimation Terhadap Pengeluaran Per Kapita Pada Level Kecamatan Di Kabupaten Sumenep Dengan Pendekatan Kernel–Bootstrap. Masters thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Pendugaan area kecil dengan teknik pendugaan tak langsung memerlukan
asumsi adanya hubungan linier antara rataan area kecil dengan variabel penyerta.
Jika tidak ada hubungan linier antara rataan area kecil dan variabel penyerta maka
tidak tepat ‘meminjam kekuatan’ dari area lain dengan menggunakan model linier
dalam pendugaan tak langsung. Untuk mengatasi hal tersebut dikembangkan
pendekatan nonparametrik. Salah satu pendekatan nonparametrik yang digunakan
adalah pendekatan Kernel-Bootstrap. Pendugaan tak langsung dengan pendekatan
SAE Kernel-Bootstrap digunakan untuk menduga pengeluaran per kapita pada
level kecamatan di Kabupaten Sumenep . Evaluasi hasil pendugaan dilakukan
dengan membandingkan nilai RRMSE (Relative Root Mean Square Error)
penduga langsung dengan nilai RRMSE (Relative Root Mean Square Error)
penduga SAE Kernel-Bootstrap. Hasil pendugaan SAE Kernel-Bootstrap lebih
presisi dibanding pendugaan langsung
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Small area estimation with indirect estimation techniques require the
assumption of linear relationship between the average small area with
concomitant variables. If there is no linear relationship between the average
small area and the concomitant variable is not appropriate to 'borrowing
strength' from other areas by using a linear model in the indirect estimation. To
overcome this nonparametric approach is developed. One approach is used the
nonparametric kernel-based approach. Indirect Estimation with SAE Kernel-
Booststrap in this study is applied to estimate per capita expenditure in several
districs in the sumenep regency. Evaluation of the estimation made by comparing
the value RRMSE (Relative Root Mean Square Error) estimator RRMSE directly
with the value RRMSE (Relative Root Mean Square Error) estimator RRMSE of
SAE Kernel-Bootstrap estimator. The result of SAE Kernel-Bootstrap estimation
is more precition than result of directly estimation.
| Item Type: | Thesis (Masters) |
|---|---|
| Additional Information: | RTSt 519.544 Dar s |
| Uncontrolled Keywords: | SAE, Kernel, Bootstrap, RRMSE |
| Subjects: | Q Science > QA Mathematics Q Science > QA Mathematics > QA278.2 Regression Analysis. Logistic regression Q Science > QA Mathematics > QA278 Cluster Analysis. Multivariate analysis. Correspondence analysis (Statistics) |
| Divisions: | Faculty of Mathematics and Science > Statistics > 49101-(S2) Master Thesis |
| Depositing User: | Mr. Tondo Indra Nyata |
| Date Deposited: | 05 Jan 2017 04:29 |
| Last Modified: | 14 Jun 2019 06:54 |
| URI: | http://repository.its.ac.id/id/eprint/1326 |
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