Indonesian food items labeling for tourism information using Convolution Neural Network

Recognition process and classification of food through image processing technology has been developed especially to know the nutrients or information contained in the food. This certainly can be useful for tourists who are in Indonesia, which is sometimes the tourists who are not accustomed to Indonesian food need information about diverse types of food. Considering some foods in Indonesia have similarities and almost resemble each other. So in this study, we utilize the method of Convolution Neural Network which proved quite reliable and fast in the process of classification of a complex and detail object, to get information about Indonesian food for tourists. By using CNN method, the process of classification can run accurately, as well as information about food in the form of names or ingredients of food can be obtained appropriately too. Evidenced by the accuracy of the classification reached 70%, which is this approach will be expected to be applied in the mobile-based system and serve as an easy alternative way to obtain information about Indonesian food.