Optimasi K-Nearest Neighbor Dengan Particle Swarm Optimization Untuk Klasifikasi

Abstract

ABSTRACT – Immune Thrombocytopenic Purpura (ITP) is a hematological disease caused by autoimmune damage to platelets, causing a person to bruise easily or bleed excessively. ITP disease must be detected early because it can cause chronic or long-term disorders, so this study aims to classify ITP disease in order to avoid misdiagnosis of patients and can be treated and treated immediately. This classification uses the PSO-KNN combination method. The results obtained from the classification using the PSO-KNN combination method are an accuracy value of 91.8% with an increase of 4.9% from the KNN standard, a sensitivity value of 91.2% with an increase of 11.8% from the KNN standard, and a specificity value of 92.6% with a decrease of 3.7% from the KNN standard. % The training and testing time of PSO-KNN is also faster than standard KNN so that PSO is able to optimize and improve the classification results of KNN.