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The large variety of frame shapes and sizes make it difficult for consumers to choose which one suits their face. The absence of a standard frame style guide between face types against the eyeglass frame complicates the selection of eyeglass frames. The application of the Zen principle (balance) in the selection of the right frame expected to be a consideration in choosing eyeglass frame. Various forms of eyeglass frames that look like a square, round and oval make the Zen principle difficult to apply, so machine learning is needed to be able to create eyeglass frames selection system. Face shape identification help to determine eyeglass frames. Face shape identification is done based on the morphological facial index by calculating face length and width. The decision tree CART algorithm is chosen as a method for selecting eyeglass frames. The study uses 109 face data that have been selected by the optical, from 109 data divided into two parts, 100 training data, and 9 test data. The prediction system produces an accuracy value of 93% at max depth 6 for reading glasses and 91% for sunglasses. The implementation of the CART algorithm is proven to be able to predict the selection of eyeglass frames using morphological attributes of face index.

Penggunaan Algoritma CART untuk Pemilihan Bingkai Kacamata dengan Penerapan Model Morfologi Indeks Wajah untuk Identifikasi Bentuk Wajah