KLASIFIKASI HASIL EKSTRASI TENUN IKAT SUMBA DENGAN METODE FUZZY K-NEAREST NEIGHBOR
Keywords:
East Nusa Tenggara, Fuzzy k-nearest Neighbor, Sobel, Sumba, WeavingAbstract
Sumba Island, as one of the islands which administratively belongs to the East Nusa Tenggara Province. Weaving as one of East Nusa Tenggara's cultural heritages. The number of ikat weaves with diverse motifs or patterns makes weaving difficult to recognize. so there is a need for pattern recognition to be used to identify Sumba weaving which has similarities in terms of motifs. Utilization of technology through digital image processing can be applied to overcome the problems encountered. Based on sampling of Sumba weaving images, it can be classified using the Fuzzy k-Nearest Neighbor algorithm by extracting Sumbanese woven motifs from RGB images to grayscale and then resized and segmented using sobel detection. The extracted image data is processed by the Fuzzy k-Nearest Neighbor algorithm. Based on the results obtained from the research on the accuracy of the system obtained by 98% of 1 test image. Confusion Matrix calculation results obtained the smallest average error value of 23.5294 on the 4th test.
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