Klasifikasi Penyimpangan Tumbuh Kembang pada Anak Menggunakan Metode Neighbor Weighted K-Nearest Neighbor (NWKNN) - Afrizal Rivaldi; Putra Pandu Adikara; Sigit Adinugroho (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2018)
Humans during life must experienced a phase of growth and development. This growth and development phase is very influential on the quality of child growth. The critical period of growth and development occurs in the first years of a child's life. At an early age, the process of growing physical, mental, and psychological development is very fast so that requires more attention from parents. In the development phase may occur disorders where the process of growth and development of children obstructed or unnatural. Development disorders are often encountered autism, ADHD, and Down syndrome. This study will classify development disorders based on symptoms that appear using Neighbor's Nearest K-Neighbor (NWKNN). The NWKNN method is the development of the KNN method, which is weighted on each class to be classified. In this research will be classify various types of development disorderds that include autism, ADHD, Down syndrome and normal. The results of this study indicate that the NWKNN method can classify well by using 80 training data and 20 test data, K = 10, and E = 4 with 95% up to accuracy. This study also proved NWKNN method which has 3% average of accuracy better than KNN method in doing classification of growth and development of child.