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

Author

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  • Helfi Nasution
  • Muhammad Syaukani

Abstract

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

Suggested Citation

  • Helfi Nasution & Muhammad Syaukani, 2025. "System Engineering Process Methodology for Machine Learning Detection and Validation of Halal Products: Case Study in Pharmaceutical Industry," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 11(2), pages 136-149, March.
  • Handle: RePEc:jbh:ijsrcs:v11:y2025:i2:id:1058
    DOI: 10.32628/CSEIT251112395
    Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT251112395
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