Please use this identifier to cite or link to this item: http://paper.sci.ui.ac.id/jspui/handle/2808.28/47
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dc.contributor.authorWidyaningsih, Yekti-
dc.date.accessioned2016-02-25T05:25:48Z-
dc.date.available2016-02-25T05:25:48Z-
dc.date.issued2010-02-06-
dc.identifier.issn1907-2562-
dc.identifier.urihttp://paper.sci.ui.ac.id/jspui/handle/2808.28/47-
dc.description.abstractThis paper presents a Bayesian approach for the analysis of spatial count data. A demonstration involving incidence rates of dengue fever in Beji sub-district, Depok City is used highlight the methodology. The model allows us to make probability statements on the incidence rates around point sources with making any parametric assumptions about the nature of the influence between the sources and the surrounding location. The objective of this paper is to estimate the rate dengue cases using Bayesian modeling and compute the standardized morbidity ratio (SMR) of the disease through Maximum Likelihood. The results show that some sub sub-districts are statistically significant as the high dengue cases; the are Beji and Tanah Baru sub sub-district.en_US
dc.language.isoen_USen_US
dc.publisherDepartemen Matematika Universitas Indonesia dan Universitas Padjadjaranen_US
dc.relation.ispartofseriesVolume 1;Tahun 2010-
dc.sourceProsiding SNM-2010 (Seminar Nasional Matematika Tahun 2010, Depok, 6 Febuari 2010, FMIPA UI & UNPADen_US
dc.subjectBayesian modelingen_US
dc.subjectDengue fever caseen_US
dc.subjectThe standardized morbidity ratio (SMR)en_US
dc.subjectSpatial count dataen_US
dc.titlePemodelan Bayesian untuk Pemetaan kasus Penyakiten_US
dc.title.alternativeBayesian Modelling for Diseases mappingen_US
dc.typeArticleen_US
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