Article Per Year (5 Year)
p-Index From 2020 - 2025
0
P-Index
This Author published in this journals
All Journal Tech-E
Budi Harto
Universita Buddhi Dharma
Computer Science & IT

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Comparison of Data Mining Methods Using the Naïve Bayes Algorithm and K-Nearest Neighbor in Predicting Immunotherapy Success Budi Harto; Rino Rino
Tech-E Vol 2 No 2 (2019): Tech-E
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1012.214 KB) | DOI: 10.31253/te.v2i2.139

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.
Co-Authors Rino Rino