System Engineering Process Methodology for Machine Learning Detection and Validation of Halal Products: Case Study in Pharmaceutical Industry DOI Open Access

Helfi Nasution,

Muhammad Syaukani

International Journal of Scientific Research in Computer Science Engineering and Information Technology, Journal Year: 2025, Volume and Issue: 11(2), P. 136 - 149

Published: March 3, 2025

Halal product pharmacies have become the primary attention of consumers and industry, especially in ensuring that raw materials production processes follow Sharia principles. The halal certification process still depends on manual methods often faces challenges matter efficiency accuracy. Therefore, research proposes application System Engineering Process Methodology (SEPM) for developing a system based Machine Learning(ML) detecting validating pharmacies. This covers stages Requirements Analysis, Design, Implementation, Testing, Deployment, Maintenance, Works optimally appropriately with applicable regulations. ML model was developed tested various technique validation For increased accuracy classifying products. Research results shows approach can improve integrate it into scale industry to support compliance standards more systematically.

Language: Английский

System Engineering Process Methodology for Machine Learning Detection and Validation of Halal Products: Case Study in Pharmaceutical Industry DOI Open Access

Helfi Nasution,

Muhammad Syaukani

International Journal of Scientific Research in Computer Science Engineering and Information Technology, Journal Year: 2025, Volume and Issue: 11(2), P. 136 - 149

Published: March 3, 2025

Halal product pharmacies have become the primary attention of consumers and industry, especially in ensuring that raw materials production processes follow Sharia principles. The halal certification process still depends on manual methods often faces challenges matter efficiency accuracy. Therefore, research proposes application System Engineering Process Methodology (SEPM) for developing a system based Machine Learning(ML) detecting validating pharmacies. This covers stages Requirements Analysis, Design, Implementation, Testing, Deployment, Maintenance, Works optimally appropriately with applicable regulations. ML model was developed tested various technique validation For increased accuracy classifying products. Research results shows approach can improve integrate it into scale industry to support compliance standards more systematically.

Language: Английский

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