Implementasi KNN untuk Sistem Klasifikasi Ukuran Baju Pria berdasarkan Pengukuran Badan menggunakan Metode Pengolahan Citra Digital berbasis Raspberry Pi - Fajra Rizky; Hurriyatul Fitriyah; Rakhmadhany Primananda (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2022)
The thing that is usually done in determining a dress size is to try out several available sizes in order to get the size of the clothes that you want and fit your body. To try on various sizes of clothes, a fitting room is provided which is used to try on the clothes. This system is made to make it easier for users to choose the size of the clothes without trying each size of each shirt and this system can replace the function of the fitting room. This system is made using the KNN with digital image processing methods. KNN or K-Nearest Neighbor is an algorithm that compares the value you are looking for with the value of those that have the same characteristics or are closest to the value you are looking for. In this system the input is the form of an image captured using a webcam camera which will later be processed digitally using a Raspberry Pi which is the place for data processing. This system works with a webcam camera to detect the user's body size, namely the height and width of the user's shoulders, this data is obtained using a function from image processing, namely the bounding box, which functions as a determinant of the height and width of the user's shoulders taken from the height and width of the bounding the box . The output of the system is that the user can see the size of the shirt that best matches the size used on the 16x2 LCD. Based on the testing, the system gets 92% accuracy and the computation time is 3,07641s.