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Danu Sasmita
Jurusan Ilmu Komputer, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Lampung
Computer Science & IT

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IMPLEMENTASI SUPPORT VECTOR MACHINE (SVM) DALAM MEMPREDIKSI JUMLAH PENYAKIT DEMAM BERDARAH (STUDI KASUS PENYEBARAN DEMAM BERDARAH DI SINGAPURA) Danu Sasmita; Favorisen Rosyking Lumbanraja; Kurnia Muludi; Astria Hijriani
Jurnal Pepadun Vol. 3 No. 2 (2022): August
Publisher : Department of Computer Science, Faculty of Mathematics and Natural Sciences, University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/pepadun.v3i2.123

Abstract

Dengue Hemorrhagic Fever (DHF) is an infectious disease caused by dengue virus infection and is transmitted through the bite of female mosquito species Aedes aegypti and Aedes albopictus. Environmental factors are one of the causes of the high prevalence of dengue fever, including the layout of buildings, water reservoirs, indentations in the soil, temperature and other things that can help the Aedes mosquito life cycle take place. The purpose of this study is to predict the spread of dengue disease using the SVM (Support Vector Machine) method with rainfall data in Singapore from 2014 to 2018, weather data and pain data, comparing this study with previous research by Adeline Ong in 2014 entitled " Predicting Dengue Cases in Singapore”, as well as knowing the results of predicting the distribution of DHF using the SVM method in the form of variance values (R2) with linear, gaussian and polynomial kernels. The results of the experiment found that the lowest error value was shown by the linear kernel with an error rate of 35.15%, with a variance value of 64.85%.
Co-Authors Astria Hijriani Favorisen R. Lumbanraja Kurnia Muludi