Rancang Bangun Sistem Klasifikasi Ukuran Baju berdasarkan Ukuran Tubuh dengan Metode K-Nearest Neighbor berbasis Arduino - Xavierro Lawrenza; Hurriyatul Fitriyah; Dahnial Syauqy (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2022)
Technological developments that are currently growing rapidly indicate the emergence of several new innovations that make work activities more practical and efficient because at this time time efficiency is an added value in the success factor in work, one of the fields of work is clothing measurement activities. Currently, the activity of measuring clothing sizes in order to get clothes of the right size requires an innovation to create efficiency and comfort. The purpose of this research is to create a system that can overcome the problems of efficiency and convenience. In this thesis research, the system was created using two ultrasonic sensors HC-SR04 as a measuring tool for body height and width as a parameter for determining the size of clothes and pants and a 16X2 LCD as the output of the size results obtained so that they are more efficient in terms of measurement and speed of time. Arduino Uno is used as a microcontroller in this study because it is hoped that its smaller size can overcome efficiency problems. The sizes that will be included as a classification include sizes S, M, L and XL. Parameters for determining the size include body height and body width. K-nearest neighbor is a classification calculation method by determining the closest distance from the test data to the training data, the number of training data for the nearest neighbor or referred to as K has been determined previously by the researcher. The calculation speed of each test data is about 10 seconds at the latest. Determination of the size using the k-nearest neighbor method because after testing and analysis this method has a high level of accuracy where the calculation results on average almost all get 100% accuracy results.