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Penerapan Regresi Logistik Ordinal Proportional Odds Model pada Analisis Faktor-Faktor yang Mempengaruhi Kelengkapan Imunisasi Dasar Anak Balita di Provinsi Aceh Tahun 2015
Author(s) -
Budyanra Budyanra,
Ghaida Nasria Azzahra
Publication year - 2017
Publication title -
media statistika
Language(s) - English
Resource type - Journals
ISSN - 2477-0647
DOI - 10.14710/medstat.10.1.37-47
Subject(s) - logistic regression , ordinal regression , odds ratio , ordered logit , odds , demography , statistics , population , medicine , mathematics , environmental health , sociology
Province of Aceh has basic immunization coverage toddler lowest in Indonesia in 2015. even though, this province has Posyandu and Puskesmas ratio per population of the highest in the western region of Indonesia. This data their concerns regarding immunization coverage has not been handled well in Aceh Province. This papers aims to identify variables that affect the status of complete basic immunization of children aged 12-59 months in Aceh by using ordinal logistic regression analysis. Ordinal logistic regression model used is proportional odds models. Data are obtained from Susenas 2015 that was held in March 2015 by BPS-Statistic of Indonesia. Based on the results of processing data, known only 37.7% of children aged 12-59 months in the province of Aceh in 2015 which gets fully immunized, the remaining 50.6% receive primary immunization but is not complete, even about 11.7% have not received basic immunization at all. From the proportional odds model results showed that the number of children born to mothers (odds ratio = 0.88), maternal age at delivery (odds ratio = 1.03), the level of maternal education (odds ratio = 1.22), and the educational level of the household (odds ratio = 1,2) have a significant impact on the status of complete basic immunization of children. Future studies are expected to include the element of timeliness and add other variables and also with other models in ordinal logistic regression.Keywords:Immunization, Ordinal Logistic Regression, Proportional Odds, Susenas

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