Integrating Artificial Intelligence and Blockchain to Improve the Accuracy of Halal Certification

Abstract

Objective: The study aims to explore the integration of artificial intelligence (AI) and blockchain technology into the halal certification process, focusing on improving accuracy, transparency, and efficiency. It evaluates how these technologies can enhance the halal certification system in Indonesia, mainly through the SiHalal platform developed by the Halal Product Assurance Agency (BPJPH). Research Design & Methods: This study uses a qualitative approach, reviewing the literature and analyzing the implementation of AI and blockchain technologies in halal certification in Indonesia through case studies and interviews with key stakeholders to assess the effectiveness and potential impact of integrating these technologies. Findings: The study found that AI and blockchain improve efficiency, transparency, and security in the halal certification process. AI automates error detection and improves accuracy, while blockchain prevents fraud through immutable records. The SiHalal platform successfully integrates the two to simplify the process and increase public trust and user satisfaction. Implications & Recommendations: The study recommends the expansion of the SiHalal platform and further development of AI and blockchain integration to improve scalability and security, policy support for technology infrastructure and training of halal auditors, and adoption of SiHalal by halal businesses to improve efficiency and transparency, with suggestions for technology developers to continue innovating in addressing scalability and interoperability challenges. Contribution & Value Added: This study contributes to the literature on modernizing halal certification systems by showing how integrating AI and blockchain can revolutionize the process. It also provides insights into how technology increases trust, reduces fraud, and enables regulation, positioning Indonesia as a global halal market leader.