Open AccessAn Identification of Tuberculosis (Tb) Disease in Humans using Na�ve Bayesian Method
Author(s) -
S Agustin Trihartati,
Cyprianus Kuntoro Adi
Publication year - 2016
Publication title -
scientific journal of informatics/scientific journal of informatics
Language(s) - English
Resource type - Journals
eISSN - 2460-0040
pISSN - 2407-7658
DOI - 10.15294/sji.v3i2.7918
Subject(s) - tuberculosis , bayes' theorem , bayesian probability , disease , identification (biology) , medicine , statistics , artificial intelligence , computer science , mathematics , pathology , biology , botany
Tuberculosis (TB) is a disease that can cause a death if not recognized or not treated properly. To reduce the death rate of tuberculosis patients, the health experts need to diagnose that disease as early as possible. Based on the main indication data, laboratory test results and the rontgen photo, Nave Bayesian approach in data mining techniques could be optimized to diagnose tuberculosis. Nave Bayes classifiers predict class membership probabilities with a class that has the highest probability value. The output of the system is an identification Tuberculosis type of the patients. Testing of the system using 237 data sample with variation of cross-validation in 3, 5, 7 and 9-fold cross validation gives an average accuracy 85,95%.