<![CDATA[Child mortality is one focus of worldwide health issues, thus it becomes one of objectives of the Millennium Development Goals (MDGs). Child mortality is also included in the Sustainable Development Goals (SDGs), which is a continuation of MDGs enden in 2015. At 56 percent of infant deaths occur in the neonatal period and 46 percent of under-five deaths occur in neonatal period. This research aimerd to identify the determinants of neonatal mortality rate, so the infant mortality rate will decrease if neonatal mortality rate is lowered. This research is an observational study using quantitative approach. Source of data was derived from the East Java public health office. The analysis method used spatial analysis Moran’s index and LISA. Independent variable is K4 visit scopem percentage of low birth weight, maternity coverage assisted by healthcare workers, ful neonatal visit scope, neonatal complications handled scope, obstetric complications handled scope. The result showed that Gresik and Probolinggo were spatially significant realtionship on K4 visit, full neonatal visit, neonatal complications handled, maternity coverage assisted by healthcare workers with Low-Low and Low-High autocorrelation. In obstertic complication with High-Low and High-High autocorrelation. In percentage of low birth weight with Low-Low and High-High autocorrelation. The conclusion that can be drawn is that there are spatial relationship between Gresik with neighbours and Probolinggo with neighbours in K4 visit scope, percentage of low birth weight, maternity coverage assisted by healthcare workers, full neonatal visit scope, neonatal complications handled scope, obstetric complications handled scope variables against neoanatal mortality rate. Variables that had most dominant relation is K4 visit scope followed by percentage of low birth weight and full neonatal visit scope.Keywords: Neonatal Mortality Rate, Spatial Analysis, East Java]]>
