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Digital herbal pharmacopeia as a solution for herbal plant identification based on computer vision


, ,
  1. Department of Pharmacy, Politeknik Harapan Bersama, Tegal, Indonesia.
  2. Department of Informatics Engineering, Politeknik Harapan Bersama, Tegal, Indonesia.

Abstract

Pharmaceutical field, especially to ensure the safety, effectiveness, and consistency of plant-based products. In the digital era, digitizing herbal identification is increasingly relevant to improve accessibility and precision, while bridging traditional knowledge with modern pharmaceutical standards. This research aims to develop a Digital pharmacopeia system that includes herbal database features, computer vision technology for plant identification, text search based on a full-text search algorithm, and API integration to support connectivity between components. The system development process uses an image classification technology-based approach that utilizes the Convolutional Neural Network (CNN) algorithm to ensure a high level of accuracy. The results show that the system has successfully improved efficiency and accuracy in herbal plant recognition, with the identification accuracy rate reaching 96% in benchmark testing. In addition, the system also offers a modern solution to support pharmaceutical research, education, and practice. By utilizing digital technology, the system is expected to become a reliable tool for pharmaceutical professionals, researchers, and the general public, while encouraging the preservation and sustainable use of biodiversity. The successful development of this system provides a strong foundation for further innovations in pharmacy and botany.



Keywords: Digital pharmacopeia, Herbal plants, Plant identification, Computer vision, Pharmaceutical technology


How to cite this article:
Vancouver
Riyanta AB, Af’idah DI, Susanto A. Digital herbal pharmacopeia as a solution for herbal plant identification based on computer vision. J Adv Pharm Educ Res. 2025;15(3):85-92. https://doi.org/10.51847/i7wEFwrt2v
APA
Riyanta, A. B., Af’idah, D. I., & Susanto, A. (2025). Digital herbal pharmacopeia as a solution for herbal plant identification based on computer vision. Journal of Advanced Pharmacy Education and Research, 15(3), 85-92. https://doi.org/10.51847/i7wEFwrt2v
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