Prediksi Pemilihan Warna Hijab Berdasarkan Tone Kulit Menggunakan Algoritma K-Nearest Neighbor (KNN) - Putri, Atsilah Daini; Adrianto, Sopan; Mulyana, Dadang Iskandar (Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh, 2025)
Choosing the right hijab color that matches a person's skin tone is essential for many Muslim women to achieve a harmonious and attractive appearance. However, selecting a suitable color is often subjective and requires specific knowledge of color compatibility. This study aims to develop an automated prediction system that recommends hijab colors based on the user’s skin tone using the K-Nearest Neighbor (KNN) algorithm. KNN was chosen for its simplicity and effectiveness in classifying data based on proximity. The dataset used includes skin tone and corresponding hijab color data, collected through both primary and secondary sources. The classification process involves extracting color features from images and calculating Euclidean distances to determine the best hijab color prediction. The experimental results show that the KNN model provides fairly accurate predictions in recommending hijab colors based on skin tone. This system is expected to assist users in selecting appropriate hijab colors in a more objective and efficient manner.