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Wulandari Wulandari
Badan Pusat Statistik Kabupaten Wonosobo, Indonesia
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PEMODELAN POISSON RIDGE REGRESSION (PRR) PADA BANYAK KEMATIAN BAYI DI JAWA TENGAH Wulandari Wulandari
Indonesian Journal of Statistics and Applications Vol 4 No 2 (2020)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v4i2.555

Abstract

The decline of infant mortality is one of the targets of the Indonesian government in the health sector, including the Government of Central Java. To achieve this goal, it is necessary to identify factors that affect many infant mortalities in the district/city of Central Java. Infant mortalities are count data, so Poisson regression is commonly used. The data in the study showed the existence of multicollinearity in several predictor variables, so an appropriate model was needed. Poisson Ridge Regression (PRR) is a Poisson modeling that accommodates multicollinearity. In this study, the PRR model was used to model infant mortality in Central Java district/city. The results showed that the parameter estimation of the PRR model was slightly different than the estimated Poisson regression model. Modeling infant mortality with the PRR model, out of five predictor variables, three variables harmed many infant deaths, while the other two variables had a positive effect on many infant deaths.
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