Comparison of Data Mining Methods Using the Naïve Bayes Algorithm and K-Nearest Neighbor in Predicting Immunotherapy Success

  • Budi Harto Universita Buddhi Dharma
  • Rino Rino Universitas Buddhi Dharma

Abstract

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.

Published
2019-02-20
How to Cite
HARTO, Budi; RINO, Rino. Comparison of Data Mining Methods Using the Naïve Bayes Algorithm and K-Nearest Neighbor in Predicting Immunotherapy Success. Tech-E, [S.l.], v. 2, n. 2, p. 30-35, feb. 2019. ISSN 2581-1916. Available at: <https://jurnal.ubd.ac.id/index.php/te/article/view/139>. Date accessed: 28 sep. 2021. doi: https://doi.org/10.31253/te.v2i2.139.
Section
Articles

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