Utilization of SVM Method and Extraction of GLCM Features in Classifying Fish Images with Formalin - Muhathir, Muhathir; Wanti, Eka Pirdia; Pariyandani, Ayu; Idrus, Syed Zulkarnain Syed; Lubis, Andre Hasudungan (Universitas Negeri Semarang, 2021)
Purpose: Fish is a type of animal protein that can be consumed by humans to supplement protein in the body. Due to the fact that there is an abundance of fish in Indonesia, traders often experience losses because of rotting fish. A small proportion of traders tricked the buyers by mixing fish with formaldehyde to preserve fish in order to prevent fish spoilage until it can be consumed. Thus, every fish buyer must be aware of fraud by traders. Methods: To be able to find out that the fish has been mixed with formalin, the solution offered is computerized by utilizing the GLCM feature extraction as information extraction on the fish image and the SVM method as a classification method. Result: The results showed an average accuracy of 0.784, precision of 0.799, recall of 0.784, and f-measure of 0.781. Novelty: The effect of the SVM classification method on the performance measurement of the model is not too big compared to previous studies, but it is better.