Ermatita, Ermatita (2022) Similarity Classification of Treatment Tuberculosis History based on Machine Learning Techniques. Turnitin Universitas Sriwijaya. (Submitted)
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Abstract
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 treatmenthistory. 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.
| Item Type: | Other |
|---|---|
| Subjects: | #3 Repository of Lecturer Academic Credit Systems (TPAK) > Results of Ithenticate Plagiarism and Similarity Checker |
| Divisions: | 09-Faculty of Computer Science > 55101-Informatics (S2) |
| Depositing User: | Dr Ermatita zuhairi |
| Date Deposited: | 25 Jun 2024 06:08 |
| Last Modified: | 25 Jun 2024 06:08 |
| URI: | http://repository.unsri.ac.id/id/eprint/147745 |
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