Implementasi Algoritma Naïve Bayes Dalam Mendiagnosa Penyakit Angin Duduk - Ahmad Turmudi Zy; Lutfi Adji Ardiansyah; Donny Maulana (Jurnal Pelita Teknologi, 2021)
Angina or wind sitting disease is chest pain caused by reduced blood flow to the heart, making it a severe pain in the left chest area and can radiate to the left shoulder and followed by breathless. The risk of a person experiencing sitting winds includes entering old age, having a family history of heart disease, hypertension, smoking and other medical conditions. Sitting wind disease can potentially lead to heart attacks if not treated properly. This study aims to determine the level of accuracy and the effect of the Naive Bayes algorithm on the sitting wind data used in this study. As well as getting information about accuracy, precision and recall that can be obtained when testing data using the Naïve Bayes algorithm. Data processing using the RapidMiner tool, the dataset used in this study is divided into 80% training data and 20% testing data. The results of this study stated that the accuracy rate is 87.50%, precision is 94.12%, and the recall is 80%. Based on the research conducted, it can be concluded that the process of determining the status of sitting wind patients using the Naïve Bayes algorithm has good accuracy in this study.