Identifikasi Citra Warna Pada Kain Tenun Lotis Timor Tengah Selatan(TTS) Menggunakan Metode Convolution Network(CNN): Penerapan Convolutional Neural Networks (CNN) untuk Identifikasi Warna dalam Kain Tenun Lotis Timor Tengah Selatan: Analisis Digital pada Warisan Budaya - nenometa, elike adielwin; naikteas, maria rosalinda; Kaesmetan, Yampi R (Jurnal Sistem Informasi dan Aplikasi (JSIA), 2024)
Handwoven fabric is a rich cultural heritage reflecting the artistic and historical values, showcasing the cultural richness of a region. Among the diverse traditional fabrics in Indonesia, Lotis woven fabric from South Central Timor (TTS) possesses unique patterns, motifs, and colors. The identification of color images on Lotis woven fabric TTS is essential for preserving its authenticity and beauty. In the era of technological advancement, the utilization of artificial intelligence methods, particularly Convolutional Neural Networks (CNN), has garnered attention in various image processing applications. CNN has proven highly effective in classifying and recognizing patterns in images, including color identification. This study aims to implement the Convolutional Neural Networks (CNN) method in the process of identifying color images on Lotis woven fabric from South Central Timor (TTS). Through this approach, it is hoped that a system capable of recognizing and distinguishing various color combinations present in Lotis woven fabric TTS with high accuracy can be developed. This research is expected to contribute to the field of pattern recognition and image processing, as well as facilitate the preservation and development of traditional woven fabric culture, particularly Lotis woven fabric TTS.