Artículo

The behavior toward halal traceability using blockchain for beef-based micro, small, and medium enterprises (literature review)

Resumen

With the largest Muslim population in the world, Indonesia has tremendous potential for the agroindustry sector, especially the halal industry. Micro, small, and medium-sized businesses (MSMEs) are essential to the Indonesian economy and play a key role in the development of the halal sector. Over the past ten years, there has been an increase in the consumption of beef due to increased understanding of nutrition and dietary diversification. But maintaining the halal purity of both domestic and imported beef is still difficult, especially in traditional marketplaces where large quantities of beef are sold. The majority of Indonesian customers prefer to buy beef from MSMEs, frequently without the use of commercial packaging. The purpose of this study is to investigate customer behavior in relation to beef products’ halal traceability, focusing on bulk and processed beef from MSMEs. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) method and Vos Viewer for bibliometric analysis, this paper looks into how blockchain technology could be used for halal traceability. A total of 7363 articles published in Scopus from 2019 to 2023 were screened, with 55 articles meeting inclusion criteria for systematic review. Numerous factors influence the halal status throughout the supply chain, necessitating tracing and tracking mechanisms to gather information on product sourcing, handling, and transportation. Blockchain technology emerges as a promising tool for ensuring traceability and verifying halal status. However, the systematic review underscores challenges related to consumer awareness and willingness to adopt blockchain implementation.
Hidayat, Erwin Yudi (57205439013); Hastuti, Khafiizh (56485990500); Muda, Azah Kamilah (23390362900)
Artificial intelligence in digital image processing: A bibliometric analysis
2025
10.1016/j.iswa.2024.200466
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85212984349&doi=10.1016%2fj.iswa.2024.200466&partnerID=40&md5=14c2a82f6cb46e9efa80c050fc79c24f
Faculty of Computer Science, Universitas Dian Nuswantoro, Semarang, 50131, Indonesia; Dinus Research Group for AI in Medical Science (DREAMS), Universitas Dian Nuswantoro, Semarang, 50131, Indonesia; Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Melaka, 76100, Malaysia
All Open Access; Gold Open Access
Scopus
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