Designing an Expert System Application to Diagnose Dengue Fever Patients Using the Naïve Bayes Method

Fransisca  Angelia Sebayang

doi:10.47065/bit.v5i1.1210

Fransisca Angelia Sebayang * STMIK Kristen Neumann, Indonesia

DOI: https://doi.org/10.47065/bit.v5i1.1210

Keywords: Keywords: Naïve Bayes; Expert System; Dengue Fever Patients

Abstract

Dengue fever is an infectious disease caused by the dengue virus and transmitted through the bites of Aedes aegepty and Aedes albopictus mosquitoes. Naive Bayes is a simple probabilistic classifier that calculates a set of probabilities by summing the frequency and combination of values from a given dataset. In this study, we will analyze dengue hemorrhagic fever disease data using the naive bayes method using 9 variables. This expert system application to diagnose dengue disease is made with a web-based application, so that it can be accessed by the public at large, besides that this application can also help medics to make decisions in diagnosing dengue disease. From the results of the study, the use of the Naïve Bayes method in this application is due to the results of the probability of the accuracy value of the Naïve Bayes method which is close to the accuracy of the experts. In this study, 3 experiments were conducted using 4 test data and the results showed that based on the three experiments, the accuracy value ranged from 96% to 97%, indicating that the classification accuracy had a small error value. So that classification using Naïve Bayes in this study can be applied to determine the classification of dengue hemorrhagic fever incidence.

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