Implementasi Machine Learning untuk Sistem Rekomendasi Gaya Rambut Berdasarkan Bentuk Wajah pada Aplikasi Mobile

Abstract

This research aims to implement machine learning technology to develop a hairstyle recommendation system tailored to individual face shapes in a mobile application. The background of this study arises from the common challenge faced by many teenagers who struggle to identify suitable hairstyles that match their facial features, often resulting in a lack of confidence and aesthetic mismatch. Utilizing the Convolutional Neural Network (CNN) algorithm, the system is designed to classify facial shapes into categories such as oval, round, square, rectangular, and heart. The classification results are then sent through an Application Programming Interface (API) to a recommendation system that provides hairstyle suggestions accordingly. This study adopts a digital image processing approach combined with the development of a user-friendly mobile application. The expected outcome is a practical and personalized solution that assists users in selecting hairstyles that suit their facial structure, while also contributing to the advancement of artificial intelligence applications in the beauty and style domain.