Nurhasyifa, Riza (2024) Sistem Klasifikasi Penderita Ispa Menggunakan Metode NaÏve Bayes (Studi Kasus : Klinik Harapan Medika Pekanbaru). Other thesis, Universitas Islam Riau.

Text 193510282_compressed.pdf - Submitted Version Download (2MB)

Abstract

Acute Respiratory Infection is an infectious disease that attacks the respiratory tract in individuals who have a lower immune system such as the elderly and children whose immune system has not been fully formed. According to the Indonesian Ministry of Health in 2002, the severity of ARI is divided into three classes, namely mild ARI, moderate ARI, and severe ARI, each of which has several symptoms with different levels of severity. To assist doctors and medical personnel in classifying patients based on the level of ARI suffered so that patients get the right treatment, a classification system for patients with ARI is needed. The method in this study uses the naïve bayes method. The Naïve Bayes method is a probability classifier that calculates by summing the frequency and combination of values from a given dataset. The attributes used in this study are age, body temperature, length of hospitalization, cough, runny nose, nausea, nasal congestion, sore throat, and shortness of breath. The results of model testing using confusion matrix on the classification of ARI patients using the naïve bayes method with 135 test data resulted in an accuracy value of 96.3%, a precision value of 96.3%, a recall value of 97% and an F1-score value of 96.4%.

Actions (login required)

View Item