Estimasi Parameter Regresi Kuantil Pada Kasus Demam Berdarah Dengue Di Kota Surabaya

Balami, Abdul Malik (2017) Estimasi Parameter Regresi Kuantil Pada Kasus Demam Berdarah Dengue Di Kota Surabaya. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Metode regresi kuantil merupakan perluasan model regresi pada kuantil bersyarat dimana distribusi kuantil bersyarat dari variabel respon dinyatakan sebagai fungsi dari kovariat yang diamati. Estimasi parameter regresi kuantil didapatkan dengan metode pemrograman linier diantarnya menggunakan algoritma simpleks, interior-point, dan smoothing. Penelitian ini mengkaji dan memodelkan Regresi Kuantil pada kasus DBD di Kota Surabaya. Estimasi regeresi kuantil diperoleh koefisien determinasi sebesar 40% pada kuantil 0,95. Lebih lanjut diperoleh hasil bahwa faktor utama penyebab penyebaran DBD di Kota Surabaya adalah faktor persentase rumah/bangunan bebas jentik nyamuk Aedes Aegypti, faktor rasio tenaga medis, faktor rasio sarana kesehatan dan faktor persentase rumah tangga yang memiliki tempat sampah sehat.

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Quantile regression is an extension of regression model of conditional quantile which is the distribution of conditional quantile from a respons variable is stated as function of an observed covariats. Parameter estimation of quantile regression is obtained through linear programming method such as simplex algorithm, interior-point, and smoothing. This research is modeling quantile regression in dengue fever in Surabaya. In the modeling, it is acquired 40% of coefficient determination in quantile 0.95. Furthermore, it is revealed that the main factors of the spread of dengue fever in Surabaya are the percentage of houses free of Aedes Aegypti mosquito larvae, medical health ratio factor, health facility ratio factor and percentage factor of household that has healthy waste bin.

Item Type: Thesis (Masters)
Uncontrolled Keywords: parameter estimation, linear programming, simplex algorithm, quantile regression, dengue fever
Subjects: H Social Sciences > HA Statistics
T Technology > TX Home economics
Divisions: Faculty of Mathematics and Science > Statistics > 49101-(S2) Master Thesis
Depositing User: Abdul Malik Balami
Date Deposited: 22 Nov 2017 02:15
Last Modified: 08 Mar 2019 03:33
URI: http://repository.its.ac.id/id/eprint/45457

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