Ray Sastri, . and Khairil Anwar Notodiputro, . and Indahwati, . (2015) AUTOLOGISTICS MODELS FOR MODELLING AND MAPPING INFANT MORTALITY IN INDONESIA. Proceeding of International Conference On Research, Implementation And Education Of Mathematics And Sciences 2015 (ICRIEMS 2015), Yogyakarta State University, 17-19 May 2015. ISSN 978-979-96880-8-8
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Abstract
According to Indonesia Demographic and Health Survey (IDHS) data, the highest child mortality occurred during the first year of age of infant. Infant mortality is an important indicator that must to be monitored seriously. The mortality is associated with several determinants, such as the infant’s characteristics, maternal and fertility factors, housing condition, and also geographical area. The aim of this research is to develop models that can be used to explain the effects of explanatory variables on infant mortality in Indonesia. It is also the aim of this research to develop a thematic map describing the distribution pattern of infant mortality probabilities at district level across the country. The response variable is a binary categorical variable with two outcomes, success and failure. The outcome is success if the infant died before achieving one year of age, and failed if the infant is still alive after one year of age. Modeling is using Logistic Regression model and Autologistics Regression model. The results showed that the Autologistics Regression model fitted the data reasonably well, all of the explanatory variable affect infant mortality, except infant’s sex. The results also showed that the probabiity of infant mortality was higher in Kalimantan island and Papua island. Keyword : Infant, mortality, autologistic, binary, IDHS
| Item Type: | Article |
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| Subjects: | Prosiding > ICRIEMS 2015 > Mathematics & Mathematics Education |
| Divisions: | Fakultas Matematika dan Ilmu Pengetahuan Alam (FMIPA) > Pendidikan Matematika > Matematika |
| Depositing User: | Administrator |
| Date Deposited: | 15 Jul 2015 21:40 |
| Last Modified: | 15 Jul 2015 21:40 |
| URI: | http://eprints.uny.ac.id/id/eprint/23641 |
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