COMPARISON OF NAVE BAYES METHODS AND SUPPORT VECTOR MACHINE IN CLASSIFICATION OF TUBERCULOSIS DISEASE - Doli Reza Apriansyah; Sriani; Mhd Furqon (Sean Institute, 2022)
A hospital is a medical center that offers extensive care for patients, including in-patient stays and outpatient procedures. The Rantauprapat Regional General Hospital has received and treated various types of diseases from the community in the Labuhan Batu area and its surroundings. These diseases include typhoid fever, diabetes mellitus, dengue hemorrhagic fever (DHF), malaria, liver, and tuberculosis (TB). In some of the diseases above, Tuberculosis (TBC) is increasing the most from year to year, which is 30%.Tuberculosis (TB) spreads very quickly through the air. Patients are expected to always carry out examinations and treatment to completion. TB is transmitted through the air. Splashing saliva or phlegm that comes out is a very fast transmission medium in this world. Therefore, people are expected to use masks in public places and always behave in a clean and healthy life. Therefore, technological advances that encourage every agency in the world of health, namely hospitals. Improve the quality of service to patients by involving technological advances in the world of health. The purpose of this study to determine the method that has the most accurate level of accuracy for the classification of Tuberculosis disease between the NaÃ¯ve Bayes method and the Support Vectore Machine is the purpose of this study. And the benefit of this research is that researchers can understand the concept of data mining. Keywords: Data mining, Tbc, Support Vector Machine, Nave Bayes