Open AccessMachine Learning for Tubercolosis Classification Based on Treatment History
Author(s) -
Eva Darnila,
Mutamminul Ula,
Mauliza,
Iwan Pahendra,
Ermatita Ermatita
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1361/1/012064
Subject(s) - tuberculosis , support vector machine , machine learning , artificial intelligence , representation (politics) , computer science , series (stratigraphy) , active tuberculosis , medicine , political science , mycobacterium tuberculosis , pathology , biology , paleontology , politics , law
TAn important step in data Tuberculosis analysis is data exploration and representation. Tuberculosis treatment is crucial to protect the patients and it can lead to death in untreated in countries with low income. In this case, we use the machine learning technique by using Support Vector Machine for classification the tuberculosis time series to analysis and represented based on the treatment history. We use Tuberculosis dataset which employed from Province Aceh, Indonesia. The result indicated the performance of the designed system was successful and could be used in Tuberculosis treatment analysis based on the histories in Aceh Utara and Lhokseumawe.