An Identification of Tuberculosis (Tb) Disease in Humans using Naïve Bayesian Method
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...
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| Format: | Article |
| Language: | English |
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Universitas Negeri Semarang
2016-11-01
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| Series: | Scientific Journal of Informatics |
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| Online Access: | https://journal.unnes.ac.id/nju/index.php/sji/article/view/7918 |
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| author | Agustin Trihartati S. C. Kuntoro Adi |
| author_facet | Agustin Trihartati S. C. Kuntoro Adi |
| author_sort | Agustin Trihartati S. |
| collection | DOAJ |
| description | 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, Naïve Bayesian approach in data mining techniques could be optimized to diagnose tuberculosis. Naïve 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%. |
| format | Article |
| id | doaj-art-ed596c14d8bf44f9932bb9159f5f7098 |
| institution | DOAJ |
| issn | 2407-7658 2460-0040 |
| language | English |
| publishDate | 2016-11-01 |
| publisher | Universitas Negeri Semarang |
| record_format | Article |
| series | Scientific Journal of Informatics |
| spelling | doaj-art-ed596c14d8bf44f9932bb9159f5f70982025-08-20T03:06:36ZengUniversitas Negeri SemarangScientific Journal of Informatics2407-76582460-00402016-11-01329910810.15294/sji.v3i2.79185187An Identification of Tuberculosis (Tb) Disease in Humans using Naïve Bayesian MethodAgustin Trihartati S.0C. Kuntoro Adi1Sanata Dharma University YogyakartaSanata Dharma University YogyakartaTuberculosis (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, Naïve Bayesian approach in data mining techniques could be optimized to diagnose tuberculosis. Naïve 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%.https://journal.unnes.ac.id/nju/index.php/sji/article/view/7918Naïve Bayesian, tuberculosis identification, cross-validation |
| spellingShingle | Agustin Trihartati S. C. Kuntoro Adi An Identification of Tuberculosis (Tb) Disease in Humans using Naïve Bayesian Method Scientific Journal of Informatics Naïve Bayesian, tuberculosis identification, cross-validation |
| title | An Identification of Tuberculosis (Tb) Disease in Humans using Naïve Bayesian Method |
| title_full | An Identification of Tuberculosis (Tb) Disease in Humans using Naïve Bayesian Method |
| title_fullStr | An Identification of Tuberculosis (Tb) Disease in Humans using Naïve Bayesian Method |
| title_full_unstemmed | An Identification of Tuberculosis (Tb) Disease in Humans using Naïve Bayesian Method |
| title_short | An Identification of Tuberculosis (Tb) Disease in Humans using Naïve Bayesian Method |
| title_sort | identification of tuberculosis tb disease in humans using naive bayesian method |
| topic | Naïve Bayesian, tuberculosis identification, cross-validation |
| url | https://journal.unnes.ac.id/nju/index.php/sji/article/view/7918 |
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