Abstract
Mammals are a group of vertebrate animals that have characteristics such as hair and mammary glands. And the kingdom of mammals is one of the kingdoms with a large number of species. The shape, color, and size of animals belonging to the mammalian kingdom can vary greatly. These differences can be distinguished by the characteristics of animals such as the distinctive shape of their body motifs. For image processing, the method that has been used to identify features in an image is edge detection. In the field of mathematics that is widely used to study the irregular shape of an object is fractal geometry. In this research, grouping of animals based on their body motifs based on fractal dimensions was carried out. 120 animal images were obtained in the mammal kingdom which will be processed through segmentation which obtains the region of animal body motifs. The region obtained will be used to determine the pattern of body motifs with Canny edge detection. Then it will be calculated using the box counting method and produce fractal dimension values for the cluster stage. The results of the experimental K-Medoids Clustering method from six clusters, namely cheetahs, tigers, leopards, hyenas, giraffes, and zebras, have an accuracy of 84.16%.
 Keywords: Mammal Animal Body Motives, Box Counting, K-Medoids.
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