Sistem Pakar Diagnosa Penyakit Infeksi Saluran Pernafasan Akut Pada Anak Menggunakan Teorema Bayes: Sistem Pakar Diagnosa Penyakit Infeksi Saluran Pernafasan Akut Pada Anak Menggunakan Teorema Bayes - Bangkit Sasangka; Arita Witanti (JMAI (Jurnal Multimedia & Artificial Intelligence), 2019)
Acute Respiratory Infection (ARI) is the main cause of morbidity and morality of infectious diseases in children. ARI mainly occurs in countries with low and middle income per capita including Indonesia. At present there are still many parents who do not know about diseases, especially ARI, that afflict their baby. In this study, the Bayes Theorem method was used. Bayes theorem is the theorem used in statistics to calculate the probability of a hypothesis. For the variables used in the calculation, 17 symptoms and 4 diseases as well as symptom weights for each disease.Based on 30 data that have been tested against experts and systems, the system can detect 4 diseases, namely influenza like common, bronchitis, pharyngitis and tonsillitis. for patients suffering from ARI and according to the doctor's validation there were 25 patients and those who did not match were 5 patients. Based on the results of expert validation (doctors) and the system, an accuracy of 83.33% of the corresponding case data was obtained.