Determination of dengue hemorrhagic fever disease factors using neural network and genetic algorithms / Yuliant Sibaroni, Sri Suryani Prasetiyowati and Iqbal Bahari Sudrajat

Yuliant, Sibaroni and Sri Suryani, Prasetiyowati and Iqbal Bahari, Sudrajat (2020) Determination of dengue hemorrhagic fever disease factors using neural network and genetic algorithms / Yuliant Sibaroni, Sri Suryani Prasetiyowati and Iqbal Bahari Sudrajat. Mathematical Sciences and Informatics Journal (MIJ), 1 (2). pp. 77-86. ISSN 2735-0703

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Abstract

The Aedes aegypti mosquito and the Aedes albopictus mosquito are carriers of the virus that causes Dengue Hemorrhagic Fever (DHF). In Indonesia, the spread of DHF disease has taken place for 41 years. Within this period, there was an increase in the number of spreading areas by 97% and an increase in the number of cases by 99%. Based on the data from previous studies, further information is needed related to the factors that have the most influence on the level of DHF infection in a region. Based on the initial study conducted, there are 6 factors that have the potential to influence the number of DHF cases in an area, namely temperature (X1), rainfall (X2), population density (X3), altitude (X4), distribution of males (X5), and distribution of education level (X6). In this study, the problem of determination dengue disease factors was modeled using a neural network. The activation function in this neural network model then estimated using genetic algorithms. Determination of the best factor is carried out in a genetic algorithm by combining several parameters of the crossover probability (Pc) and mutation probability (Pm). This experiment show that the main factors that influence the spread of DHF in Bandung area are temperature, altitude, distribution of gender, and distribution of education levels. The best accuracy system obtained in this study using these 4 factors reached 72%.

Metadata

Item Type: Article
Creators:
Creators
Email
Yuliant, Sibaroni
yuliant@telkomuniversity.ac.id
Sri Suryani, Prasetiyowati
srisuryani@telkomuniversity.ac.id
Iqbal Bahari, Sudrajat
iqbalbaharisudrajat@student.telkomuniversity.ac.id
Subjects: Q Science > QA Mathematics > Analysis > Analytical methods used in the solution of physical problems
Q Science > QA Mathematics > Evolutionary programming (Computer science). Genetic algorithms
Divisions: Universiti Teknologi MARA, Perak > Tapah Campus
Journal or Publication Title: Mathematical Sciences and Informatics Journal (MIJ)
UiTM Journal Collections: Others > Mathematical Science and Information Journal
ISSN: 2735-0703
Volume: 1
Number: 2
Page Range: pp. 77-86
Official URL: https://www.mijuitmjournal.com/
Item ID: 38872
Uncontrolled Keywords: Dengue Hemorrhagic Fever; DHF factor; Neural Network; Genetic Algorithms
URI: https://ir.uitm.edu.my/id/eprint/38872

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38872

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