![](bg1.png)
Modeling of Infant Mortality Rate in East Java Province Using Mixed
Geographically Weighted Regression Approach for Improving
Quality of Health Services
Ninda Ayu Puspitasari
1
, Nadia Murbarani
1
, Nopiyanti
1
, Sartika Aprilia
1
, Nur Chamidah
2
1
Student of Program Study of Statistics, Department of Mathematics, Universitas Airlangga, Surabaya, Indonesia
2
Department of Mathematics, Faculty of Sciences and Technology, Universitas Airlangga, Surabaya, Indonesia
Keywords: East Java Province , Infant Mortality Rate, Mixed Geographically Weighted Regression
Abstract: Infant mortality is defined as the death of a baby aged less than one year old. Sustainable Development
Goals (SDG) program is a sustainable development program in which there are 17 goals and 169
measurable targets with specified deadlines. One of the targets to be achieved by the year 2030 is to be able
to reduce infant mortality at least up to 12 every 1,000 live births. Infant Mortality Rate in East Java
Province still shows a high number of 5,196 babies die every year. It shows that as many as 13 babies die
every day. The mixed geographically weighted regression (MGWR) model is a combination between global
regression and local regression models where some predictor variables affect globally and the others affect
locally to the response. This study aims to select the best model based on the smallest AICc (Akaike
Information Criterion corrected) value using fixed Gaussian weighted. The variable that affect globally is
percentage of pregnant mothers visit. While other predictor variables that affect locally are percentage of
Integrated Health Services (Posyandu), percentage of number of households with decent sanitation, and
percentage of low birth weight infants.
1 INTRODUCTION
Infant mortality is the death of a baby aged less than
one year old. Infant mortality is measured as the
infant mortality rate, which is the number of child
deaths under one year per 1000 births in one year
(Central Bureau of Statistics, 2012). SDGs is a
sustainable development program in which there are
17 goals with 169 measurable targets with specified
deadlines. SDGs is a world development agenda
aimed at human and planetary welfare. One of the
goals of SDGs is good health, which ensures a
healthy life and promotes well-being for all people
of all ages. The goal has 13 targets, one of which is
by 2030 ending preventable infant and toddler
deaths with all countries trying to reduce infant
mortality by at least 12 per 1,000 live births (Annisa,
2013). The condition of Infant Mortality Rate (IMR)
and Neonatal Mortality Rate in East Java Province is
relatively small, however, the absolute mortality rate
still shows a high number of 5,196 toddlers per year.
It shows that as many as 13 babies died and 14
toddlers die every day. The Mixed Geographically
Weighted Regression (MGWR) model is a
combination model of global regression with Global
Weighted Regression (GWR) considering the
situation where some predictor variables affecting
the response are global and other predictor variables
are localized according to the location of the data
observation (Asih et al, 2013).
2 LITERATURE REVIEW
2.1. Infant Mortality Rate
Infant Mortality Rate (IMR) describes the number of
infant mortality of less than one year per 1000 live
births in a given year. IMR is one indicator of health
development successes that has been declared in
National Health System and even used as a central
indicator of success of health development in
Indonesia (Azizah, 2013). Besides, IMR also reflects
the level of maternal health, environmental health,
and general level of socio-economic development of
the community because the IMR is very sensitive to
Puspitasari, N., Murbani, N., Nopriyanti, ., Aprilia, S. and Chamidah, N.
Modeling of Infant Mortality Rate in East Java Province Using Mixed Geographically Weighted Regression Approach for Improving Quality of Health Services.
DOI: 10.5220/0007546105150519
In Proceedings of the 2nd International Conference Postgraduate School (ICPS 2018), pages 515-519
ISBN: 978-989-758-348-3
Copyright
c
2018 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved
515