@inproceedings{e716dff0701d48fe8dcbd52bad8642c8,
title = "BEQI: Mobile Application of Beef Image Classification for Quality Identification",
abstract = "Beef is a food source high in protein and quite popular with many people because it has a delicious taste. However, it is not easy to distinguish the quality of beef in circulation. Fat in the beef can also be called marbling, one of the determining factors for beef quality. This fat can be seen visually on the surface of the meat cut with thin lines or spots on the beef cut surface, but determining the quality level is quite tricky. For this reason, an Android-based application will be developed to identify the quality of beef using the GLCM Feature Extraction and the KNN algorithm. The implementation consists of two stages, namely the implementation of the interface or client sides that sends image data and the implementation of the feature extraction system and its classification or the server sides that receive image data then upload. It sends the classification results back to the client sides in the form of JSON. The experiments carried out resulted in a classification result in grade or quality of meat with the best accuracy of 91.7\%.",
keywords = "Beef, GLCM, Image Classification, K-Nearest Neighbor, Marbling, Mobile Application",
author = "Hanggara, \{Buce Trias\} and Merlinda Wibowo and N. Priandani",
note = "Publisher Copyright: {\textcopyright} 2021 ACM.; 6th International Conference on Sustainable Information Engineering and Technology, SIET 2021 ; Conference date: 13-09-2021 Through 14-09-2021",
year = "2021",
month = sep,
day = "13",
doi = "10.1145/3479645.3479689",
language = "English",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
pages = "63--68",
booktitle = "Proceedings of 2021 International Conference on Sustainable Information Engineering and Technology, SIET 2021",
}