Klasifikasi pada Penyakit Dental Caries Menggunakan Gabungan K-Nearest Neighbor dan Algoritme Genetika - Dennes Nur Dwi Iriantoro; Candra Dewi; Delvi Fitriani (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2018)
Dental caries disease is a disease commonly encountered in cases of dental problems. Indonesia is ranked 6th in dental caries cases 60% - 80% in the population in Indonesia. Therefore, early treatment expected to reduce the high caries disease in Indonesia. Classification Caries using computer programs is expected to improve performance in the field of dentistry. The problem with using the K-Nearest Neighbor method has been widely applied to other cases. This method has a deficiency in determining the value of K that must be sought alone for K. This study will discuss about the optimization of KNN K method. This study will use the combined K-Nearest Neighbor and Genetic Algorithm. Genetic algorithms can produce optimal solutions with various variations and have advantages in terms of ability. The use of optimization with this genetic algorithm makes K-Nearest Neighbor method easier to use because it does not have to choose manually. The results obtained on the accreditation test by Genetics algorithm quality are optimal K with 88% honesty and 0.9 fitness. Classification of dental caries disease would be better to use this combined method