Data Mining Klasifikasi Penyakit TBC(Tuberkulosis) Menggunakan Metode Naive Bayes berbasis Web

Abstract

Tuberculosis is an infectious disease that can cause death to sufferers. Tuberculosis (TB) is caused by the Mycobacterium Tuberculosis virus, where the virus attacks an unhealthy part of a person's body. TB disease is divided into 2 types namely Lung TB, and Extra Lung TB.  Based on the Research Data Survey of the Ministry of Health of the Republic of Indonesia in 2009 there were 1.7 million people died due to tuberculosis. One of the causes of TB (Tuberculosis) in Indonesia is acute smokers, or people who are often associated with active TB patients (Tuberculosis) and the lack of public knowledge of the symptoms of TB (Tuberculosis). To check earlier, an examination is made at the Puskesmas first. Therefore, this study designed a system that can classify types of tuberculosis patients, based on general symptoms and to help health center workers, namely midwives / nurses who are experts in the field of tuberculosis more quickly and accurately in determining prediction results the. After testing, the results show that all system functionalities have been met. Based on the results of expert jugdement testing, that 83.3% of the prediction results are in accordance with medical science. The TB disease classification system that was built can help the health center staff predict general symptoms felt by the patient, before consulting a doctor. Whereas by using confusion matrix testing, obtained an accuracy of 53%.