Classification of treatment tuberculosis history based on machine learning techniques

An 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 Decision Tree and Random...

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Bibliographic Details
Published inIOP conference series. Materials Science and Engineering Vol. 725; no. 1; pp. 12102 - 12106
Main Authors Darnila, Eva, Ula, Mutamminul, Mauliza, Pahendra, Iwan, Ermatita
Format Journal Article
LanguageEnglish
Published Bristol IOP Publishing 01.01.2020
Subjects
Classification
Data analysis
Decision analysis
Decision trees
Machine learning
Tuberculosis
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Summary:An 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 Decision Tree and Random Forest for classification the tuberculosis 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 arrangement was successful and could be used in Tuberculosis treatment analysis based on the histories in Aceh Utara and Lhoksumawe.
ISSN:1757-8981
1757-899X
DOI:10.1088/1757-899X/725/1/012102