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All Journal JoDENS: Journal of Digital Ecosystem for Natural Sustainability
Eva Tesvara
Universitas Universal
Computer Science & IT Decision Sciences, Operations Research & Management

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Penerapan Metode Radial Basis Function (RBF) dalam Mengklasifikasikan Penyakit Demam Berdarah Steffany; Akhmad Rezki Purnajaya; Rika Jelita; Eva Tesvara; Milson Nestelrody; Joni Irwansyah
Journal of Digital Ecosystem for Natural Sustainability Vol 3 No 1 (2023): Juli 2023
Publisher : Fakultas Komputer - Universitas Universal

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Abstract

Dengue fever is an arbovirus disease caused by dengue virus infection through the bite of the Aedes mosquito, Aedes aegypti. Signs or symptoms of dengue usually resemble ordinary viral infections, but can become more severe and cause other symptoms that can paralyze the activities of the patient who suffers from it. The initial symptoms of someone who is infected with the dengue virus will experience a fever within 4–6 days after being infected. Therefore, early diagnosis is needed whether a person is infected or not with dengue fever. Because if someone is late getting treatment by medical personnel, then this can lead to death. Prevention can be done by making the right predictions. Dengue fever disease prediction research is needed to assist medical personnel in making a diagnosis. To get a good level of accuracy, research collected data and used the Radial Basis Function (RBF) approach method. The results of the RBF prediction evaluation obtained are that the RBF model gets 100% accuracy, 100% sensitivity, 100% specificity, and 100% AUC value.
Co-Authors Joni Irwansyah Milson Nestelrody Purnajaya, Akhmad Rezki Rika Jelita Steffany