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Journal : Variance : Journal of Statistics and Its Applications

PEMODELAN DEMAM BERDARAH DENGUE DENGAN METODE REGRESI LOGISTIK BINER DI KOTA TOBELO Trifena Punana Lesnussa; Samsul Bahri Loklomin
VARIANCE: Journal of Statistics and Its Applications Vol 3 No 1 (2021): VARIANCE: Journal of Statistics and Its Applications
Publisher : Statistics Study Programme, Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/variancevol3iss1page7-14

Abstract

One of the infectious diseases that is still a public health problem in Indonesia, especially in North Maluku, is Dengue Hemorrhagic Fever (DHF). This study aims to model DHF cases in Tobelo City, North Halmahera Regency. The results showed that in Tobelo City there were 103 DHF sufferers and 2 deaths occurred. The method used in this research is binary logistic regression to model DHF cases. Binary logistic regression is a data analysis method used to find the relationship between the binary response variable (y) and the predictor variable (x). In this study, the binary response variable used was DHF sufferers. The predictor variables used were gender, education level and access to health. The results of the analysis using the binary logistic regression method obtained a strong correlation between the response variable y and all the predictor variables x and the coefficient of determination obtained from the model was 52%.
ANALISIS ANGKA KEMATIAN BAYI KABUPATEN HALMAHERA UTARA DENGAN METODE REGRESI NONPARAMETRIK SPLINE TRUNCATED Samsul Bahri Loklomin; Meidy Kaseside
VARIANCE: Journal of Statistics and Its Applications Vol 3 No 1 (2021): VARIANCE: Journal of Statistics and Its Applications
Publisher : Statistics Study Programme, Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/variancevol3iss1page1-5

Abstract

Infant Mortality Rate is a reflection of infant survival which will determine the quality of life of human resources. North Maluku Province is an archipelago province with a relatively high infant mortality rate. The still high infant mortality rate in North Maluku is influenced by several factors, apart from the low equity and affordability of health services, socio-economic factors also greatly affect infant and under-five mortality rates. North Halmahera District is one of the highest IMR contributors in North Maluku Province. This study aims to mathematically analyze the infant mortality rate in North Halmahera. The results showed that all predictor variables had an effect on infant mortality. The analysis results found the best model with three point knots with a determination coefficient of 93% and a minimum GCV value of 1.52.