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Utami, Krisdiana Nur
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PEMODELAN JUMLAH KASUS PNEUMONIA PADA BALITA DI JAWA TIMUR MENGGUNAKAN METODE REGRESI POISSON INVERSE GAUSSIAN DILENGKAPI GUI-R Utami, Krisdiana Nur; Sugito, Sugito; Santoso, Rukun
Jurnal Gaussian Vol 12, No 4 (2023): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.12.4.539-548

Abstract

Reducing toddler mortality is one of the desire of sustainable development programs.Modeling count data may be analyzed the usage of Poisson regression.The assumption that must be met in Poisson regression is that the mean and variance values must be equal, often in count data there is a violation of this assumption. This is indicated by the variance value which is greater than the mean value (overdispersion). Poisson Inverse Gaussian (PIG) regression is one form of mixed Poisson regression to model data that experience overdispersion cases. The MLE method is used to estimate the PIG regression parameters and hypothesis testing using the MLTR method. The best model of the PIG regression form is based on the smallest AIC value. The results of hypothesis testing concluded that the percentage of under-fives who received exclusive breast feeding had a significant effect on the number of pneumonia cases among toddler. Data modeling using the PIG regression method in this study is complemented by the creation of a Graphical User Interface (GUI) that can facilitate the process of selecting the best model.
Co-Authors Rukun Santoso Sugito -