A Prediction System of Dengue Fever Using Monte Carlo Method

Dengue fever is an acute disease that clinically can cause death because there is no prediction system to estimate dengue fever cases so it resulted in the growing of dengue fever cases every year. Original data gathering in Jember area that uses technique of partial data gathering has caused data m...

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Bibliographic Details
Main Authors: Mochammad Choirur Roziqin, Achmad Basuki, Tri Harsono
Format: Article
Language:English
Published: Politeknik Elektronika Negeri Surabaya 2016-08-01
Series:Emitter: International Journal of Engineering Technology
Online Access:http://emitter2.pens.ac.id/ojs/index.php/emitter/article/view/111
Description
Summary:Dengue fever is an acute disease that clinically can cause death because there is no prediction system to estimate dengue fever cases so it resulted in the growing of dengue fever cases every year. Original data gathering in Jember area that uses technique of partial data gathering has caused data missing. To make this secondary data can be processed in prediction stage there is need to conduct missing imputation by using Monte Carlo method with four different randomization method, followed by data normality test with chi-square, then continued to regression stage. We use MSE (Mean Square Error) to measure prediction error. The smallest MSE result of regression is the best regression model for prediction.
ISSN:2355-391X
2443-1168