Snakebite Classification Using Active Contour Model and K Nearest Neighbor - Chiara Janetra Cakravania; Dody Qori Utama (Telkom University, 2020)
Indonesia is categorized as one of tropical countries that have a high risk of snakebites. This surely may endanger rural citizens’ lives for there are still many snakes found in rural areas. The main cause of death from snakebite cases is by reason of the venom squirted from snake’s canine teeth. Others causes are errors in identifying the bite marks visually. There are anatomical differences between puncture wounds from venomous and non-venomous snakes. This study established a snakebite identification system using Active Contour Model and K Nearest Neighbor (KNN) methods. By performing some tests related to the parameters used in the method, the highest accuracy value on K Nearest Neighbor method was obtained by using the correlation distance rule, the K value = 3, without using distance weight in the classification system.