Classification Of Borax Content In Tomato Sauce Through Images Using GLCM

• Main Authors: Reyhan Achmad Rizal, Mario Susanto, Andy Chandra
• Format: Article
• Language: English
• Published: Politeknik Ganesha Medan 2020-03-01
• Series: Sinkron
• Online Access: https://jurnal.polgan.ac.id/index.php/sinkron/article/view/10508

One of the food products that need to be reviewed for safety and is the most consumed is tomato sauce, although it contains a large amount of water in the sauce which has a long shelf life because it contains acid, sugar, salt, and is often given preservatives. The purpose of this study was to determine the tomato sauce using harmful preservatives such as the addition of borax. The dataset used in this study is the image of tomato sauce containing borax and not with the number of samples 400 images of tomato sauce with different comparison percentages starting from the image of tomato sauce with 70% borax content, image of tomato sauce with 50% borax content, image tomatoes with 30% borax content and image of tomato sauce that does not contain borax. A sampling of images using a camera phone brand xiaomi note 5 by mixing borax in the original sauce before the sample is used for the training and testing process. The classification results show the gray level co-occurrence matrix (GLCM) method is quite optimal in classifying tomato sauce data containing borax and not with an average percentage of the introduction of 88%.