<![CDATA[Batik Besurek is an Indonesian cultural heritage that presents a variety of motifs reflecting the richness of creativity and symbolic meanings. A significant challenge in this field is accurately and efficiently identifying and classifying batik Besurek motifs, known for their intricate designs and cultural significance. In efforts towards cultural preservation and development, a combination of modern technology and local wisdom is required. One technology that can be utilized is object detection technology using You Only Look Once (YOLO), specifically the latest version, YOLOv8, for the classification of batik Besurek motifs. The dataset collected consists of 1,656 images taken from the Roboflow public repository, containing various motifs such as Burung Kuau, Kaligrafi, Kembang Melati, Rafflesia, and Rembulan. The dataset is divided into 1,324 images (80%) for the training set, 166 images (10%) for the validation set, and 166 images (10%) for the test set. Model training is conducted with hyperparameter values: learning rate of 0.01, batch size of 16, and 100 epochs. The application of the YOLOv8 model as a training model for the batik Besurek motif dataset yields an accurate final model with an average precision value for each motif class of 96%, and an average recall value for each motif class of 93%. This study aims to assist communities in recognizing and distinguishing batik Besurek motifs, contributing to the preservation of Indonesia’s cultural heritage.]]>
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