Named-Entity Recognition and Optical Character Recognition for Detecting Halal Food Ingredients: Indonesian Case Study

This study offers solutions using OCR and NER technology to read and recognize the compositional entities listed on packaged product. The purpose of this study is to guide Muslim consumers identifying ingredients of a consumers products, we define three food category entities in NER: Halal, Haram, Syubhat (doubtful). The motivation is to meet the needs of a Muslim for halal products that halal guarantees should support. Because consumers have easier access to various imported products, it is hoped that consumers can freely choose the consumption products they like, including imported ones, while maintaining the halal guarantee. Our proposed system is built using OCR to scan the composition listed on packaged products and processed with the trained NER Model; the evaluation of the model gets an F-Score value of 0.967, and in system testing, by testing 24 packaged products, it produces an OCR accuracy value of 90% and the accuracy of the NER model. for a food reading of 84%.