Ramadhan, Rajuliaddin (2013) Pemodelan Spatial Autoregressive With Autoregressive Disturbances Dengan Prosedur Generalized Spatial Two Stage Least Squares (GS2SLS). Sarjana thesis, Universitas Brawijaya.
Abstract
Data spasial adalah hasil pengukuran yang memuat informasi tentang lokasi yang berasal dari lokasi berbeda dan mengindikasikan dependensi antara hasil pengukuran dengan lokasi. Pengaruh dependensi spasial digambarkan dengan kemiripan sifat antar lokasi yang saling berdekatan. Beberapa model dependensi spasial yang dapat terbentuk berdasarkan dependensi yang terdapat pada model yaitu Spatial Autoregressive (SAR) dependensi nilai respon antar lokasi, Spatial Error (SEM) dependensi nilai galat antar lokasi dan model Spatial Autoregressive With Autoregressive Disturbances (SARAR) dependensi pada nilai respon dan nilai galat antar lokasi. Pemodelan didasarkan pada pengaruh dependensi spasial, sehingga sebelum dilakukan pemodelan perlu dilakukan pengujian pengaruh spasial yang terkandung dalam data menggunakan statistik uji Lagrange Multiplier (LM). Uji Lagrange Multiplier merupakan salah satu cara dalam pengujian pengaruh spasial. Dalam perkembangan, uji ini sering digunakan karena mudah (hanya memerlukan pendugaan di bawah kebenaran hipotesis nol). Pemodelan SARAR dalam penelitian ini dilakukan karena terdapat dependensi antar nilai respon dan galat. Pemodelan SARAR dilandasi pada prosedur Generalized Spatial Two Stage Least Squares (GS2SLS) sehingga dihasilkan penduga konsisten. Berdasarkan hasil pemodelan SARAR dengan prosedur GS2SLS diketahui bahwa faktor-faktor yang berpengaruh terhadap tingkat kemiskinan adalah rata-rata lama sekolah, angka buta huruf dan angka harapan hidup di kabupaten/kota tersebut serta tingkat kemiskinan di kabupaten/kota tetangga
English Abstract
Spatial data is obtained from measurement includes information about locations, originated from different locations and indicate dependencies between locations of the measurement results. Influence of spatial dependencies is described by the similarity between the nature of the location adjacent to each other. Some spatial dependencies models can be formulated based on the dependencies contained in the Spatial Autoregressive Model (SAR) response value dependencies between locations, Spatial Error (SEM) error dependencies between the location and the value of Spatial Autoregressive Model With Autoregressive Disturbances (SARAR) dependencies on the value of the response and error value between locations. Modeling is based on the influence of spatial dependencies, so that before modeling, it is necessary to test the influence of spatial data using Lagrange Multiplier (LM). Lagrange Multiplier test is used to indicate the spatial influence, this test is often used in its development because of its simplicity, where it requires estimation under the true null hypothesis. Modeling performed in this study based on SARAR dependencies between the value of response and error. SARAR modeling is done using Generalized Spatial Two Stage Least Squares (GS2SLS) procedure to obtain consistent estimator. Based on the results, SARAR with the GS2SLS procedure, the average length of the schooling, illiteracy and life expectancy in the district/city as well as the level of poverty in the district/city neighbors effect the poverty rate.
| Item Type: | Thesis (Sarjana) |
|---|---|
| Identification Number: | SKR/MIPA/2013/168/051307148 |
| Subjects: | 500 Natural sciences and mathematics > 519 Probabilities and applied mathematics > 519.5 Statistical mathematics |
| Divisions: | Fakultas Matematika dan Ilmu Pengetahuan Alam > Statistika |
| Depositing User: | Hasbi |
| Date Deposited: | 28 Aug 2013 15:14 |
| Last Modified: | 25 Oct 2021 02:00 |
| URI: | http://repository.ub.ac.id/id/eprint/153426 |
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