DIAGNOSA INFEKSI SALURAN PERNAPASAN AKUT MENGGUNAKAN ALGORITMA NAIVE BAYES CLASSIFIERS

RAMADHAN, BAYU CATUR WANGSA and Rini, Dian Palupi and Rodiah, Desty (2022) DIAGNOSA INFEKSI SALURAN PERNAPASAN AKUT MENGGUNAKAN ALGORITMA NAIVE BAYES CLASSIFIERS. Undergraduate thesis, Sriwijaya University.

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Abstract

ARI is a disease that attacks the respiratory tract which can be caused by a viral infection or can also be caused by other diseases or other conditions, under certain conditions ARI can cause complications if not immediately examined and treated. Diagnosing ARI is not easy for the general public. In this case an expert system can help deal with the problem by building a system that people can use to find a solution. To diagnose the disease, a method of uncertainty is needed in diagnosing ARI. The Naïve Bayes method is a method of uncertainty that is suitable to be applied in the problem of classifying the types of ARI. The implementation of the Naïve Bayes method in the application is to calculate the probability of the disease suffered by the patient based on the weight of the expert's level of confidence for each symptom that has been entered by the patient. The total number of data tested amounted to 110 data. The accuracy rate of the test results reached 87,27%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Expert System, Naive Bayes, ARI
Subjects:	Q Science > Q Science (General) > Q300-390 Cybernetics > Q325.5 Machine learning
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Bayu Catur Wangsa Ramadhan
Date Deposited:	25 Jan 2023 05:49
Last Modified:	25 Jan 2023 05:49
URI:	http://repository.unsri.ac.id/id/eprint/87441

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