Penerapan Metode Fuzzy K-Nearest Neighbor pada Klasifikasi Penyakit Menular Seksual Pria - Nadia Siburian; Imam Cholissodin; Putra Pandu Adikara (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2020)
sexually transmitted diseases is one of the dangerous diseases that spreads every year, especially in the city of Malang. One of these educational cities has a growing human population each year so that it can be a trigger for the spread of the sexually transmitted diseases, especially for people who have sex. Based on information from the Malang Health Service, most people are exposed to sexually transmitted diseases without being aware of the symptoms that arise in them. Compared with women, more men who have a sexually transmitted infection. Sexually transmitted diseases in men such as Syphilis, HIV, Gonorrhea, Herpes and Warts have symptoms that have similarities in each disease so it is difficult to distinguish. To find out and reduce errors in predicting a disease, the Fuzzy k-Nearest Neighbor method is used in this study to help classify sexually transmitted diseases. The classification process consists of three processes are the fuzzy initialization process. The kNN algorithm process and the kNN fuzzy algorithm process. In the research test used the influence of K value testing, K-Fold Cross Validation test using 60 data divided into 10-fold and obtained the highest accuracy results of 91.67% with K = 5 then inter-class performance testing using confusion matrix to determine Precision and Recall values ​​on 30 test data.