CD Tesis
Pemodelan Pencemaran Udara Di Pekanbaru Dengan Menggunakan Distribusi Dagum
This study uses air pollution data with particulate matter 10 (PM10 ) pollutants in the Pekanbaru city in 2009 2015. Air pollution data was analyzed to obtain probability model for air pollution in the Pekanbaru city by using the Dagum distribution. This distribution is a special form of generalized beta II distribution with 3 parameters, namely b as a scale parameter and a, p as shape parameters. The maximum likelihood (MLE ) method and the L-moment method (LME ) were used to obtain the estimated parameter of the air pollution model with the PM10 pollutant used. Based on the smallest Akaike information criterion (AIC ) value of the two distribution models it can be concluded that the model of the Dagum distribution probability density function with the estimated maximum likelihood method is better then in describing air pollution patterns with particulate matter 10 pollutants (PM10 ) which occurred in the Pekanbaru city in 2009−2015.
Keywords: Air pollution, Dagum distribution, maximum likelihood estimation
(MLE ), L-moment estimation (LME ), Akaike information criterion (AIC )
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