Application of Data Mining for Tuberculosis Disease Classification Using K-Nearest Neighbor
This study aims to find out how much the application of the K-NN method and the accuracy value obtained by the K-NN method in clarifying data of Tuberculosis patients. This research focuses on improving public health and developing science to help people prevent and overcome tuberculosis. This type...
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| Format: | Article |
| Language: | English |
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LPPM ISB Atma Luhur
2024-11-01
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| Series: | Jurnal Sisfokom |
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| Online Access: | https://jurnal.atmaluhur.ac.id/index.php/sisfokom/article/view/2218 |
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| author | Delima Sitanggang lamria Simangunsong Geertruida Frederika Sundah Rani Hutahaean Indren Indren |
| author_facet | Delima Sitanggang lamria Simangunsong Geertruida Frederika Sundah Rani Hutahaean Indren Indren |
| author_sort | Delima Sitanggang |
| collection | DOAJ |
| description | This study aims to find out how much the application of the K-NN method and the accuracy value obtained by the K-NN method in clarifying data of Tuberculosis patients. This research focuses on improving public health and developing science to help people prevent and overcome tuberculosis. This type of research is quantitative. The literature study used is the documentation study. The method used by the K-Nearest Neighbor Algorithm. The results of the study showed that the process of applying data mining for the classification of tuberculosis disease using the K-Nearest Neighbor method obtained a final result of 80% accuracy. Thus, it can be concluded that the K-Nearest Neighbor algorithm is good. |
| format | Article |
| id | doaj-art-4d81baf8df8542ae90e6faeef61e78b0 |
| institution | OA Journals |
| issn | 2301-7988 2581-0588 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | LPPM ISB Atma Luhur |
| record_format | Article |
| series | Jurnal Sisfokom |
| spelling | doaj-art-4d81baf8df8542ae90e6faeef61e78b02025-08-20T01:53:22ZengLPPM ISB Atma LuhurJurnal Sisfokom2301-79882581-05882024-11-0113331832210.32736/sisfokom.v13i3.2218887Application of Data Mining for Tuberculosis Disease Classification Using K-Nearest NeighborDelima Sitanggang0lamria Simangunsong1Geertruida Frederika Sundah2Rani Hutahaean3Indren Indren4Information Systems Study Program, Faculty of Science and Technology, Prima Indonesia University, Medan, Indonesia,Information Systems Study Program, Faculty of Science and Technology, Prima Indonesia University, Medan, Indonesia,Information Systems Study Program, Faculty of Science and Technology, Prima Indonesia University, Medan, Indonesia,Information Systems Study Program, Faculty of Science and Technology, Prima Indonesia University, Medan, Indonesia,Information Systems Study Program, Faculty of Science and Technology, Prima Indonesia University, Medan, Indonesia,This study aims to find out how much the application of the K-NN method and the accuracy value obtained by the K-NN method in clarifying data of Tuberculosis patients. This research focuses on improving public health and developing science to help people prevent and overcome tuberculosis. This type of research is quantitative. The literature study used is the documentation study. The method used by the K-Nearest Neighbor Algorithm. The results of the study showed that the process of applying data mining for the classification of tuberculosis disease using the K-Nearest Neighbor method obtained a final result of 80% accuracy. Thus, it can be concluded that the K-Nearest Neighbor algorithm is good.https://jurnal.atmaluhur.ac.id/index.php/sisfokom/article/view/2218tuberculosisk-nearest neighborsclassification |
| spellingShingle | Delima Sitanggang lamria Simangunsong Geertruida Frederika Sundah Rani Hutahaean Indren Indren Application of Data Mining for Tuberculosis Disease Classification Using K-Nearest Neighbor Jurnal Sisfokom tuberculosis k-nearest neighbors classification |
| title | Application of Data Mining for Tuberculosis Disease Classification Using K-Nearest Neighbor |
| title_full | Application of Data Mining for Tuberculosis Disease Classification Using K-Nearest Neighbor |
| title_fullStr | Application of Data Mining for Tuberculosis Disease Classification Using K-Nearest Neighbor |
| title_full_unstemmed | Application of Data Mining for Tuberculosis Disease Classification Using K-Nearest Neighbor |
| title_short | Application of Data Mining for Tuberculosis Disease Classification Using K-Nearest Neighbor |
| title_sort | application of data mining for tuberculosis disease classification using k nearest neighbor |
| topic | tuberculosis k-nearest neighbors classification |
| url | https://jurnal.atmaluhur.ac.id/index.php/sisfokom/article/view/2218 |
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