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Journal : JURNAL Al-AZHAR INDONESIA SERI SAINS DAN TEKNOLOGI

Sistem Identifikasi Titik Kritis Halal Menggunakan Algoritma Forward Chaining Alexander Moya Hin; Adhi Kusnadi; Marlinda Vasty Overbeek; Oqke Prawira; Yaman Khaeruzzaman; Syarief Gerald Prasetya
JURNAL Al-AZHAR INDONESIA SERI SAINS DAN TEKNOLOGI Vol 8, No 1 (2023): Januari 2023
Publisher : Universitas Al Azhar Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36722/sst.v8i1.1285

Abstract

Halal products are obligatory to be used by people who are Muslim. When viewed in terms of the number of the Muslim population in the world and Indonesia, halal products have very potential economic opportunities. However, halal products have the risk of becoming non-halal if the accompanying process and storage do not follow halal rules. Therefore, it is necessary to identify the critical halal point, the point where the potential for such change occurs. So far, identification is made manually, of course there will be opportunities for identification errors to happen and it will take a relatively long time. To overcome these problems, identification can use a computer-based system. Forward chaining is an algorithm that is suitable for identifying halal points, because in SJH LPPOM MUI there is a decision tree for identifying halal critical points which is carried out in the same forward sequence as the forward chaining algorithm process flow. The development of a halal critical point identification system is carried out using the Software Development Life Cycle V-model method, the PHP programming language and the MySQL Database Management System. The system was successfully tested using Whitebox testing, including unit testing, integration testing, and overall system testing. Then testing using Blackbox testing techniques by comparing the results of identifying critical points using the system with the results of identifying critical points manually producing the same results. User satisfaction testing was also carried out using the End User Computing Satisfaction method and obtained an average satisfaction score of 86.53%Keywords – halal products, critical halal point, AI, forward chaining