Article Per Year (5 Year)
p-Index From 2019 - 2024
0.23
P-Index
This Author published in this journals
All Journal Contemporary Mathematics and Applications (ConMathA)
N. A. Aprilianti
Universitas Airlangga
Materials Science & Nanotechnology Mathematics

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Modeling of Incident Status Dengue Fever in East Nusa Tenggara Using Geographically Weighted Logistic Regression Approach A Meylin; N. A. Aprilianti; D Lestari; Nur Chamidah
Contemporary Mathematics and Applications (ConMathA) Vol. 2 No. 2 (2020)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/conmatha.v2i2.23856

Abstract

Dengue fever is a disease caused by one of the four dengue viruses and this disease is an infectious disease that is spread through the bite of the Aedes Aegypti mosquito. When compared with the number of dengue cases in previous years, East Nusa Tenggara (NTT) was one of the provinces that experienced an increase in the number of dengue cases in the last three years. Previous research states that the transmission of dengue fever is caused by several factors, one of which is environmental factors of geographical location so that spatial aspects need to be involved in this study. A the statistical method that can be used to analyze spatial data in the form of a logistic regression equation that has a binary response variable is the Geographically Weighted Logistic Regression (GWLR) method. This study aims to analyze the factors that influence the high number of dengue fever cases in NTT in 2018 using GWLR approach by weighted the Gaussian kernel function. Based on the results of GWLR analysis, the number of rainy days and the number of health workers partially significantly influence the status of dengue fever events in each regency/city in NTT Province in 2018. Based on the calculation of Press’s Q value, the prediction in this study was accurate with the accuracy of classification was 0.8636 or 86.36%.
Co-Authors A Meylin D Lestari Nur Chamidah