Modeling Infant Mortality Rate with Multivariate Adaptive Regression Spline Approach

  • Hendra H Dukalang Politeknik Gorontalo

Abstract

The most important thing in human life is health, because of it is the rights of national foundation that should be fullfiled. This contains on Millenium Development Goals (MDGs) which had elapsed on December 2015, and was replaced by Sustainable Development Goals (SDGs). SDGs in the aspect of Mother and Child’s Health mentioned in its third purpose namely: ensuring the health life and supporting welfare for all ages. Kota Gorontalo is the capital of Gorontalo Province which has become the center ofactivities either in the part of economics or all sectors including health development, as one of them is to reduce the Infant Mortality Rate. The  Infant  Mortality Rate can be defined as the number of  babies  who  died since the birth phase until the approximately age of one year of babies in the area at a certain period, then  divided with the total per 1000  successful birth  in that year. This research is aimed to analyze the relationship between infant mortality and its affecting factors by using MARS Method. The result of this research showed that the best MARS MODEL is a combination of BF = 16, MI = 3, MO = 3, with with a GVC value of 0,732. Therefore, the variable that have significant effect towards infant mortality in Gorontalo City is the percentage of childbirth which was helped by the healthcare provider (X1), the percentage of giving Vitamin A to the babies (X5), the percentage of pregnant mother who received TT2(X7), the percentage of basic inclusive imunitation on babies (X4) and the percentage of babies which was given breast milk exclusively at the age of 0-5 months (X2).

Published
2017-12-17
How to Cite
DUKALANG, Hendra H. Modeling Infant Mortality Rate with Multivariate Adaptive Regression Spline Approach. JOURNAL OF APPLIED INFORMATICS AND COMPUTING, [S.l.], v. 1, n. 1, p. 19-28, dec. 2017. ISSN 2548-6861. Available at: <http://jurnal.polibatam.ac.id/index.php/JAIC/article/view/524>. Date accessed: 24 feb. 2018.
Section
Articles