Predicting Halal Critical Control Points of Microbial-based Ingredients: A Self-Assessment for MSMEs

Abstract

The Muslim population is expected to reach 26% of the world by 2030. As the Muslim population increases, the awareness of halal food is also improving. Halal goes beyond the religious obligation. It is part of the Islamic way of life, including dietary requirements, behavior, speech, dress, and conduct. Indonesia has the largest Muslim population in the world and represents a significant global-market opportunity for halal food producers. The emergence of the Halal food market as one of the largest consumer markets has encouraged firms to implement Halal food certification. However, statistical data shows that food product businesses registered for halal certification in Indonesia are only around 0.11% compared to the total number of Micro, Small, and Medium Enterprises (MSMEs). The low percentage of halal certification is partly because most MSMEs still need to familiarize themselves with it. A self-assessment system is proposed to help MSMEs to detect whether food products are made from halal microbial ingredients before they start halal certification process. Business process modeling is conducted using ProcessMaker, a business process management (BPM) software. The classification model is constructed on three classifiers: Decision Tree, Random Forest, and SVM. Early detection of microbial critical point tracing was carried out by using products of several MSMEs: yogurt, cheese, and soy sauce. SVM outperforms the other two methods with an accuracy of 99.44% in detecting potential nonhalal ingredients.