<![CDATA[Fish are vertebrates that live in the water. Fish have gills that function as a respiratory organ to take oxygen in the water and fins are used for swimming. In vertebrates, fish have the largest number, which is estimated at 40,000 species, while around 25,000 have been recorded. These fish are mostly scattered in marine waters of about 13,630 species, because almost 70% of the earth's surface consists of marine water and only about 1% is fresh water. This study uses a marine fish database taken from a public dataset that has 7 types of marine fish where each type of marine fish there are 7,000 images that will be carried out in the HSV color segmentation stage by taking the value so that it becomes grayscale which will proceed to the HOG process and to classify fish species sea using the SVM. For testing techniques and dataset distribution using the K-Fold Cross Validation method of Leave One Out (LOO) type. Based on the results of the SVM classification test both linear and polynomial gaussian kernels using 3-Fold, 4-Fold, and 5-Fold. The highest accuracy of Black Sea Sprat fish is 94.06%. For the highest type of Gilt Head Bream fish, it was obtained at 94.31%. Furthermore, the Hourse Mackerel fish got the highest accuracy value of 94.74%. Then the type of fish Red Mullet the highest accuracy value of 94.76%. Furthermore, the Red Sea Bream fish species obtained the highest accuracy value of 94.86%, the Sea Bass fish species with the highest accuracy value of 77.86% and Striped Red Mullet fish obtained the highest accuracy value of 94.41%.]]>
