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ANALISIS REGRESI POISSON INVERSE GAUSSIAN UNTUK MENENTUKAN FAKTOR-FAKTOR YANG MEMPENGARUHI JUMLAH KASUS DEMAM BERDARAH DENGUE (DBD)

Muhammad Marizal, Veny Alvionita

Abstract


One of the census data is the number of dengue cases where to model the data can be done using poisson regression. Poisson regression has an assumptions that must be met, namely the average value dan variance must be the same or colled (equidispersion). But, in this study, the data experienced a violation in ehich the variance value was greater than the average value or colled (overdispersion). To overcome thie problem by using the mixed poisson method, namely poisson inverse gaussian regression for count data that is overdispersed and has a likelihood function that is cloce form, that is the parameters are know, so many researchers use this model. The number of DBD cases in Riau Province is counting data that has overdispersion. So therefore, to model the number of cases of DBD using poisson inverse gaussian regression. Based on the model used, it shows the factors that influence the number of dengue cases in Riau Province in 2019, namely the number of health facilities.


Keywords


Dengue Fever. Overdispersion, Poisson Inverse Gaussian Regression

References


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DOI: 10.33751/ekologia.v23i1.6553

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