PENERAPAN ALGORITMA NAÏVE BAYES UNTUK PREDIKSI PENYAKIT TUBERCULOSIS (TB) - Rizal Amegia Saputra (Swabumi, 2014)
The disease Tuberculosis (TB) is a contagious and deadly diseases in the world, even the World Health Organization (WHO) declared as the world's emergency disease (global emergency), some research fields of health including one disease TB has been widely carried out to detect the disease early, but it is not yet known which algorithm is quite good in predicting disease TB. On this research will apply the Algorithm Naïve Bayes, in predicting diagnosis of TB disease to Naïve Bayes algorithm so that the destination is the most accurate algorithm in the prediction of the disease TUBERCULOSIS. The test results using the method of Confusion Matrix and the ROC Curve, the naïve bayes algorithm is known that has a value of 91,61%, accuracy and value of the AUC of 0,995. See the value of AUC, the naïve bayes methods including group classification is very good, because the results of his AUC values between 0.90-1.00.