Comparison of Data Mining Methods Using the Naïve Bayes Algorithm and K-Nearest Neighbor in Predicting Immunotherapy Success
| Main Authors: | Harto, Budi, Rino, Rino |
|---|---|
| Format: | Article info application/pdf Journal |
| Bahasa: | eng |
| Terbitan: |
BSTI
, 2019
|
| Online Access: |
https://jurnal.ubd.ac.id/index.php/te/article/view/139 https://jurnal.ubd.ac.id/index.php/te/article/view/139/160 |
Daftar Isi:
- tumor or cancer is a disease that is a problem for people who are increasing every year. This disease in both the early and final stages requires attention because in this disease sufferers have a large risk of death. along with the rapid development of technology, we can use the technology to facilitate in all fields one of which is to predict success in a therapy. Data mining is one of the techniques used by the author in testing the dataset used in this study to get the best algorithm between Naïve Bayes and the K-Nearest Neighbor algorithm by using the Rapid Miner S tudio application and applying the best algorithm into the expected application or expert system. can help users predict the success of a therapy.