Comparison of Data Mining Methods Using the Naïve Bayes Algorithm and K-Nearest Neighbor in Predicting Immunotherapy Success
Article Sidebar
Main Article Content
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.
Downloads
Article Details
The Authors submitting a manuscript do so on the understanding that if accepted for publication, copyright of the article shall be assigned to journal Tech-E, Universitas Buddhi Dharma as publisher of the journal.
Copyright encompasses exclusive rights to reproduce and deliver the article in all form and media, including reprints, photographs, microfilms and any other similar reproductions, as well as translations. The reproduction of any part of this journal, its storage in databases and its transmission by any form or media, such as electronic, electrostatic and mechanical copies, photocopies, recordings, magnetic media, etc. , will be allowed only with a written permission from journal Tech-E.
journal Tech-E, the Editors and the Advisory Editorial Board make every effort to ensure that no wrong or misleading data, opinions or statements be published in the journal. In any way, the contents of the articles and advertisements published in the journal Tech-E, Universitas Buddhi Dharma are sole and exclusive responsibility of their respective authors and advertisers.
Abstract views: 137
/ 
PDF downloads: 99