Journal of Computer System and Informatics (JoSYC)
Vol 3 No 4 (2022): August 2022

Pendeteksian Penyakit Limfadenopati dengan Menerapkan Metode Naive Bayes

Fifto Nugroho (Universitas Bung Karno, Jakarta)
Yoga Listi Prambodo (Universitas Bung Karno, Jakarta)



Article Info

Publish Date
30 Aug 2022

Abstract

Lymphadenopathy or often known as lymphatic disease is a disease that is very risky if not handled properly. There are so many signs or symptoms of this disease that have not been known to the public, some even consider it an ordinary lump that grows on the human body and do not know that they are experiencing lymphadenopathy in themselves [3]. Usually to find out the disease in the lump, do an examination to the hospital or consult a doctor. Based on these problems, a technique or method is needed that can facilitate the community in diagnosing the early symptoms of this lymphadenopathy, one of which is by using an expert system. An expert system that in solving problems with oral and nail diseases, one of them uses the Naïve Bayes method. Naïve Bayes is a probability method by predicting future opportunities based on past experience. With the aim of making it easier for ordinary people to take the first step in dealing with diseases that are experienced about lumps on the body. Based on the results of the application of the Naïve Bayes method, the results are based on the input of the user's symptoms, the accuracy of the results of lymphadenopathy in users with mild lymphadenopathy is 32% and acute lymphadenopathy is 68%. critical

Copyrights © 2022






Journal Info

Abbrev

josyc

Publisher

Subject

Computer Science & IT Decision Sciences, Operations Research & Management Industrial & Manufacturing Engineering

Description

Journal of Computer System and Informatics (JoSYC) covers the whole spectrum of Artificial Inteligent, Computer System, Informatics Technique which includes, but is not limited to: Soft Computing, Distributed Intelligent Systems, Database Management and Information Retrieval, Evolutionary ...