Kain Tenun; Nusa Tenggara Timur; Primary Dataset; Image Classification; Machine Learning

The recognition of woven fabrics through image processing has a high value in preserving cultural heritage and assisting in identifying and classifying traditional textile products. To this end, this study proposes an approach that utilizes a Decision Tree (DT) to recognize images of woven fabrics typical of East Nusa Tenggara. DT's effectiveness in high-dimensional data classification makes it an ideal tool for modeling unique patterns in woven fabric drawings.