Klasifikasi Penyakit Infeksi Saluran Pernapasan Akut (ISPA) Di RSUD Undata Kota Palu Menggunakan Probabilistic Neural Network

Acute Respiratory Infection (ARI) is an acute respiratory disease caused by infectious agents that are transmitted from human to human. Factors that affect ARI include age, temperature, respiration, pulse, blood pressure, leukocyte count and length of stay. ARI can be the cause of someone's death if not treated seriously. This study aims to determine the factors that influence ARI and find the best accuracy of the PNN method in classifying ARI disease. This study uses the Probabilistic Neural Network (PNN) to classify acute respiratory infections (ARI) in Undata Hospital, Palu City. The accuracy of the PNN classification on the training data is 100%, while the testing data has the same accuracy of 90%.

Keywords: Acute Respiratory Infection, Probabilistic Neural Network, Classification, Best accuracy