Prediction of Dengue Fever in Coastal Areas of North Sumatera (Kuala Namu and Belawan) With Random Forest and Support Vector Machine (SVM) Methods

Suzi Surbakti; Hayatunnufus Hayatunnufus; T. Henny Febriana

doi:10.32734/jocai.v7.i2-14355

Prediction of Dengue Fever in Coastal Areas of North Sumatera (Kuala Namu and Belawan) With Random Forest and Support Vector Machine (SVM) Methods

Authors

Suzi Surbakti University of Sumatera Utara
Hayatunnufus Hayatunnufus University of Sumatera Utara https://orcid.org/0000-0003-2883-6179
T. Henny Febriana University of Sumatera Utara https://orcid.org/0000-0003-1504-5570

DOI:

https://doi.org/10.32734/jocai.v7.i2-14355

Keywords:

Dengue Fever, Marchine Learning, Random Forest, Support Vector Machine

Abstract

Dengue Fever is a really infectious disease. This disease may cause death. The lack of health facilities in several regions can increase the number of cases and death. Thus, a proper prevention is needed so the number of cases can be decreased and the spread of the fever can be prevented especially in remote area like the coast area of North Sumatera. Because of this, a system that can predict the number of cases based on several parameters is needed to prevent the spread of fever in several areas, using Random Forest dan Support Vector Machine method. Both methods have different forecast results but the number is close to the actual number of cases. Random Forest can predict more accurate with MSE value at 43.

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Published

2023-07-31

How to Cite

Surbakti, S., Hayatunnufus, H., & T. Henny Febriana. (2023). Prediction of Dengue Fever in Coastal Areas of North Sumatera (Kuala Namu and Belawan) With Random Forest and Support Vector Machine (SVM) Methods. Data Science: Journal of Computing and Applied Informatics, 7(2), 103-110. https://doi.org/10.32734/jocai.v7.i2-14355

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Issue

Vol. 7 No. 2 (2023): Data Science: Journal of Computing and Applied Informatics (JoCAI)

Section

Articles

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