Penerapan Fuzzy K-Nearest Neighbor (FK-NN) Dalam Menentukan Status Gizi Balita - Satria Dwi Nugraha; Rekyan Regasari Mardi Putri; Randy Cahya Wihandika (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2017)
Infants or so-called children is a group that have an important period in physical growth. Infants itself is categorized as a group of children between age 1 to 3 as a teddler group, and age 3 to 5 as a pre-school group. Some says children has a big role in order to attaining of growth success in the future for human, hence they call it as the golden age of living. Children's growth not only discribing as an increasing of body dimensions but also as the continuity of intake and nutrient needs. An indicator to know the children's health is by determining their nutritional status. Based on SK Minister of Health in Indonesia, they use a method called anthropometry to determining children's nutritonal status. While this method only reviewing 4 internal factors, there're some other factors which influence of children's nutritional status itself such as genetic, disease, education, knowledge, and income. Therefore Fuzzy K-Nearest Neighbor is used in this study as a classifiaction method that can determining children's nutritional status because this method using the data training as the knowledge to clasify and would adjust other factors of nutritional status itself right in the future. From the test results of the study, this system can clasify well with maximum accuracy of 84,37% when using 160 training data with k value = 4.