Pemodelan Jumlah Kematian Bayi di Provinsi Nusa Tenggara Timur Tahun 2015 Dengan Regresi Poisson - Pratama Yuly Nugraha; Memi Nor Hayati; Desi Yuniarti (Program Studi Statistika FMIPA Universitas Mulawarman, 2017)
Poisson regression is one of the non-linear regression analysis whose response variable is modeled with Poisson distribution. The parameter estimation Poisson regression model using Maximum Likelihood Estimation (MLE). This study aims to model the number of infant mortality in East Nusa Tenggara Province in 2015 and what factors affect the occurrence of cases of infant mortality in East Nusa Tenggara Province using Poisson regression. The results of research with Poisson regression factors influencing the number of infant mortality is the number of deliveries assisted by health personnel (x1), the percentage of pregnant women receiving FE3 tablets (x2), the number of obstetric complications handled (x4), the percentage of low birth weight babies (x5), the number of exclusively breastfed babies (x6), the percentage of households Live clean and healthy (x7), and the number of deliveries is helped by non-medical personnel (x8).