Eksponensial
Vol 12 No 2 (2021)

Model Geographically Weighted Weibull Regression pada Indikator Pencemaran Air Biochemical Oxygen Demand di Daerah Aliran Sungai Mahakam

Siti Mahmudatur Rahmah (Laboratorium Statistika Terapan FMIPA Universitas Mulawarman)
Suyitno Suyitno (Laboratorium Statistika Terapan FMIPA Universitas Mulawarman)
Meiliyani Siringoringo (Laboratorium Statistika Komputasi FMIPA Universitas Mulawarman)

Article Info

Publish Date
30 Dec 2021

Abstract

Geographically Weighted Weibull Regression (GWWR) Model is a Weibull regression model applied to spatial data. Estimation of the GWWR model is performed at every observation location using spatial weighting. The purpose of this study was to determine the GWWR model of water pollution indicator Biochemical Oxygen Demand (BOD) data and the factors that influence BOD in the Mahakam River. The estimating parameters method of the GWWR model was the Maximum Likelihood Estimation (MLE) and it’s estimator was obtained by Newton-Raphson Iterative method. Spatial weighting in parameter estimation was determined using the Adaptive Bisquare weighting function and bandwidth optimum was determined by using Generalized Cross-Validation (GCV) criteria. Based on the GWWR model parameters testing, the factors that influence BOD locally was nitrate concentrations, while the factors influence globally were temperature and nitrate concentration.

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Journal Info
Eksponensial
Website

Abbrev

exponensial

Publisher

Universitas Mulawarman

Subject

Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics Other

Description

Jurnal Eksponensial is a scientific journal that publishes articles of statistics and its application. This journal This journal is intended for researchers and readers who are interested of statistics and its ...