Jurnal Informatika dan Rekayasa Perangkat Lunak
Vol. 7 No. 1 (2025): Maret

Klasifikasi Tingkat Demam Berdarah menggunakan Metode Naive Bayes Classifier untuk Deteksi Dini

Akhmad Pandhu Wijaya (Universitas Wahid Hasyim)
Gilar Pandu Annanto (Universitas Wahid Hasyim)
Adek Saputra (Universitas Wahid Hasyim)



Article Info

Publish Date
31 Mar 2025

Abstract

Nowadays, the flow of information has experienced a significant increase every day, which results in the accumulation of data in the form of text documents both online and offline. The classification of Dengue Fever data in the medical field is an essential task in predicting the disease, it can even support doctors in establishing a diagnosis, so it is important to make a diagnosis quickly in order to reduce the risk of Dengue Fever spreading in the community. The classification of dengue fever level using Naïve Bayes Classifier for early detection is the Naïve Bayes Algorithm can be used to classify the level of DD (Dengue Fever), and DBD1 (Dengue Hemorrhagic Fever Level 1), DBD2 (Dengue Hemorrhagic Fever Level 2), DBD3 (Hemorrhagic Fever) Level 3), Dengue4 (Hemorrhagic Fever Level 4) for early detection, which is taken from the result of the largest Naïve Bayes probability value. In testing the Naïve Bayes method using test data as many as 60 data.

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Journal Info

Abbrev

JINRPL

Publisher

Subject

Computer Science & IT

Description

Journal of Informatics and Software Engineering accepts scientific articles in the focus of Informatics. The scope can be: Software Engineering, Information Systems, Artificial Intelligence, Computer Based Learning, Computer Networking and Data Communication, and ...