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Journal : Journal of Applied Geospatial Information

Spatial Modeling of Infant Mortality Rate In Sampang Regency : An Ecological Study Saputra, Firman Firdauz; Nursia N, Lily Eky; Kusumawardani, Eva Flourentina; Syam, Nasrianti; Paradhiba, Meutia; Fadillah, Mardi; Ssekalembe, Geofrey
Journal of Applied Geospatial Information Vol 8 No 2 (2024): Journal of Applied Geospatial Information (JAGI)
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jagi.v8i2.7158

Abstract

Infant mortality rate (IMR) is one of the indicators to measure public health status and community welfare. In the last 3 years (2014-2016), the infant mortality rate in Sampang Regency has increased. The purpose of this study is to develop spatial-based modeling of factors affecting infant mortality rates in Sampang. Researchers used an ecological study design where secondary data came from the Health Office and the Central Bureau of Statistics in Sampang Regency. The dependent variable is infant mortality rate, while the independent variables are delivery assisted by health workers, exclusive breastfeeding coverage, neonatal complications handled, K4 visit coverage, LBW percentage, midwife to population ratio, percentage of clean and healthy household behavior. Data has been analyzed and processed using Geoda and Quantum GIS applications. Based on statistical tests, the spatial model is obtained: ŷi= -21.82+0.706 ∑(i=1,i≠j)^n wijyi-0.61* childbirth attended by health worker+0.10* neonatal complications attended by health worker+1.89* LBW babies. Each variable of childbirth assisted by health workers increased by 10, it can decrease the infant mortality rate by 6.1 cases. Each variable of neonatal complications not handled by health workers rises 10 units, it can increase the infant mortality rate by 1 case. each variable of LBW babies rises 1 unit and it can increase infant mortality cases by 1.89 cases. The results of this study can be used to reduce infant mortality rates that occur by intervening in existing factors.