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Model-Model Regresi Weibull Univariat pada Indikator Pencemaran Air Dissolved Oxygen di Daerah Aliran Sungai Lingkungan Hutan Hujan Tropis Kalimantan Timur Chairina, Puspa; Suyitno, Suyitno; Siringoringo, Meiliyani
EKSPONENSIAL Vol 11 No 1 (2020)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (897.131 KB) | DOI: 10.30872/eksponensial.v11i1.641

Abstract

A Univariate Weibull Regression is a model of regression developed from univariate Weibull distribution with the parameter scale is stated in parameter regression. There are some of univariate Weibull regression model, namely Weibull survival regression, Weibull hazard regression and mean model. Univariate Weibull regression model in this research is applied to the water pollution indicator dissolved oxygen (DO data at Mahakam river in East Kalimantan. The purpose of this study is to find out the model of univariate Weibull regression based on the parameter estimation by using maximum likelihood estimation method (MLE) and to find out the factors which affect to univariate Weibull regression in Mahakam river. The result shows that the closed form of the maximum likelihood estimator can not be found analytically, and it can be approximed by using the Newton-Raphson iterative method. Based on the result of partial hypothesis test for all the parameter regression, it was found that detergent concentration and nitrate concentration had significant influence to the DO in the water of Mahakam river.