Gusti E. Yuliastuti, Adyan N. Alfiyatin, Agung M. Rizki, A. Hamdianah, H. Taufiq, W.F. Mahmudy
According to health reports of Malang city, many people are exposed to sexually transmitted diseases and most sufferers are not aware of the symptoms. Malang city being known as a city of education so that every year the population number increases, it is at risk of increasing the spread of sexually transmitted diseases virus. This problem is important to be solved to treat earlier sufferers sexually transmitted diseases virus in order to reduce the burden of patient spending. In this research, authors conduct data mining methods to classifying sexually transmitted diseases. From the experiment result shows that K-NN is the best method for solve this problem with 90% accuracy. © 2018 Institute of Advanced Engineering and Science. All rights reserved.
Faculty of Computer Science, Brawijaya University, Veteran Road 8, Malang, 65145, Indonesia
