Model Geographically Weighted Univariate Weibull Regression (Studi Kasus : Indikator Pencemaran Sungai Di Surabaya)

Santoso, Fitriarma Putri (2015) Model Geographically Weighted Univariate Weibull Regression (Studi Kasus : Indikator Pencemaran Sungai Di Surabaya). Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Metode yang digunakan dalam memodelkan hubungan antara variabel respon dan variabel prediktor adalah analisis regresi. Suatu model regresi dimana variabel respon (Y) berdistribusi weibul dengan variabel prediktor X , X ,..., X k 1 2 adalah model regresi weibul. Seperti hal nya analisis regresi linier, hubungan antara variabel prediktor dan variabel respon pada analisis regresi weibul dianggap konstan untuk setiap lokasi geografis, sehingga penaksir parameter yang didapat juga bersifat global untuk setiap lokasi. Geographically Weighted Univariate Weibull Regression (GWUWR) merupakan bentuk lokal dari regresi weibul dan merupakan metode statistik yang digunakan untuk menganalisis data spasial. Univariat berarti jumlah variabel respon adalah satu. Penelitian ini bertujuan untuk menaksir parameter model GWUWR, mendapatkan statistik uji GWUWR dan menerapkannya pada kasus riil. Data yang digunakan merupakan data konsentrasi Chemical Oxygen Demand (COD) sungai di Surabaya dan faktor yang mempengaruhinya. Dalam menaksir parameter menggunakan metode Maximum Likelihood Estimation (MLE) dengan dibantu metode iterasi Newton Raphson, sedangkan untuk mendapatkan statistik uji menggunakan Maximum Likelihood Ratio Test (MLRT). Faktor lokasi tidak berpengaruh terhadap pemodelan COD sehingga faktor-faktor yang berpengaruh di setiap lokasi hampir sama. Faktor-faktor yang berpengaruh terhadap Chemical Oxygen Demand (COD) di sungai Surabaya berdasarkan model GWUWR antara lain lebar sungai (X1), kedalaman sungai (X2), kecepatan air (X3) dan debit sungai (X4). ===================================================================================================== The method used to modelling the relationship between the response variable and the predictor variable is regression analysis. Response variable (Y), weibull distribution, with the predictors variable X , X ,..., X k 1 2 is weibull regression model. Such as linear regression analysis, the relationship between predictor variables and response variable in weibull regression assumed to be constant for each geographical location, then the parameter estimation is also obtained global for each location. GWUWR is a statistical method for analyzing spatial data and a local form of weibull regression. Univariate means the number of the response variable is only one. This study aims to estimate the parameters of GWUWR model, getting a test statistic of GWUWR and applying it to the real case. The data that used is data of concentration of Chemical Oxygen Demand (COD) in Surabaya river and their the factors that influence. Estimate parameters are use Maximum Likelihood Estimation (MLE) with helped by Newton Raphson iteration method, whereas to get the test statistic using Maximum Likelihood Ratio Test (MLRT). Location factors have not given influence to COD modelling, hence every factors influenced in every location are almost the same. Factors influence in Chemical Oxygen Demand (COD) in Surabaya river based on GWUWR models are the wide of the river (X1), the depth of the river (X2), the speed of the water (X3) and river discharge (X4).

Item Type: Thesis (Undergraduate)
Additional Information: RTSt 519.536 San m
Uncontrolled Keywords: Distribusi weibul, Geographically Weighted Univariate Weibull Regression (GWUWR), Chemical Oxygen Demand (COD)
Subjects: Q Science > QA Mathematics > QA278.2 Regression Analysis
Divisions: Faculty of Mathematics and Science > Statistics > 49101-(S2) Master Thesis
Depositing User: Mr. Marsudiyana -
Date Deposited: 06 Dec 2019 07:18
Last Modified: 06 Dec 2019 07:18
URI: https://repository.its.ac.id/id/eprint/72258

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