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Estimasi Parameter Model Geographically Temporally Weighted Regression (GTWR) dengan fungsi Pembobot Adaptive Gaussian Kernel

Sari, Agustiningsih Indah (2018) Estimasi Parameter Model Geographically Temporally Weighted Regression (GTWR) dengan fungsi Pembobot Adaptive Gaussian Kernel. Undergraduate thesis, Universitas Islam Negeri Maulana Malik Ibrahim.

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Abstract

ABSTRAK

Geographically and Temporally Weighted Regression (GTWR) merupakan metode pengembangan dari Geographically Weighted Regression yang mengakomodasi adanya heterogenitas secara spatial (lokasi) dan secara temporal (waktu). Untuk mengestimasi parameter model GTWR yakni dengan metode Maximum Likelihood Estimator (MLE). Penelitian ini bertujuan untuk mengetahui estimasi parameter model Geographically Temporally Weighted Regression (GTWR) dengan fungsi pembobot adaptive gaussian kernel. Hasil penelitian diaplikasikan pada data Angka Kematian Bayi (AKB) di Provinsi Jawa Timur tahun 2012-2016. Variabel independent yang digunakan pada penelitian ini adalah persentase bayi berat badan lahir rendah (BBLR) (X_1), Persentase pelayanan kesehatan bayi (X_2), Persentase bayi yang diberi ASI ekslusif (X_3), Persentase persalinan ditolong tenaga kesehatan (X_4), dan Persentase imunisasi BCG (X_5). Hasil yang didapatkan dari penelitian ini adalah bentuk estimasi parameter model GTWR dengan fungsi pembobot adaptive gaussian kernel dan faktor yang mempengaruhi angka kematian bayi di Jawa Timur tahun 2012-2016 secara lokal beserta pemetaannya.

ABSTRACT

Geographically and Temporally Weighted Regression (GTWR) is development method from Geographically Weighted Regression that accommodated the heterogenety spatialy (place) and temporaly (time). To estimate the parameter model GTWR with Maximum Likelihood Estimator (MLE) method is used. This research is conducted to find out the parameter model estimation of GTWR with adaptive gaussian kernel function. The result of research applied in Data on Infant Mortality Rate (IMR) in East Java Province on 2012-2016. The variables independent that used in this research are the Percentage of Low Birth Weight (X_1), the percentage of infant health services (X_2), percentage of infants given exclusive breastfeeding (X_3), the percentage of deliveries assisted by health personnel (X_4), and the percentage BCG immunization (X_5). The result of research found in parameter model estimation GTWR with adaptive gaussian kernel weight function and the factor that is influenced which is applied in Data on Infant Mortality Rate (IMR) in East Java on 2012-2016 locally with the mapping.

Item Type: Thesis (Undergraduate)
Supervisor: Harini, Sri and Juhari, Juhari
Contributors:
ContributionNameEmail
UNSPECIFIEDHarini, SriUNSPECIFIED
UNSPECIFIEDJuhari, JuhariUNSPECIFIED
Keywords: GTWR; Adaptive Kernel Gaussian; MLE GTWR; Adaptive Kernel Gaussian; MLE
Departement: Fakultas Sains dan Teknologi > Jurusan Matematika
Depositing User: Moch. Nanda Indra Lexmana
Date Deposited: 17 Mar 2023 13:25
Last Modified: 17 Mar 2023 13:25
URI: http://etheses.uin-malang.ac.id/id/eprint/48566

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