AERI RACHMAD, NUR CHAMIDAH* AND RIRIES RULANINGTYAS
Department of Mathematics, Faculty of Science and Technology, Airlangga University, Surabaya, Indonesia
*(e-mail : nur-c@fst.unair.ac.id; Contact : +62315936501)
ABSTRACT
Tuberculosis (TB) is one of the infectious diseases infecting the respiratory tract caused by Mycobacterium Tuberculosis. In this paper, expert system to classify TB bacteria was explored. The expert system such as decision tree and random forest was a simple machine learning which was trained using a large collection of diverse images. In this paper, it combined adaptive boosting and expert system for classification of TB bacteria. This research used 1266 image data that consisted two classes. The results of the experiments have been conducted using random forest classifier showing an accuracy of 85%.
Key words : Tuberculosis, convensional microscopes, expert system, random forest, adaptive boosting