TY  - JOUR
T1  - Digital herbal pharmacopeia as a solution for herbal plant identification based on computer vision
A1  - Aldi Budi Riyanta
A1  - Dwi Intan Af’idah
A1  - Ardi Susanto
JF  - Journal of Advanced Pharmacy Education and Research
JO  - J Adv Pharm Educ Res
SN  - 2249-3379
Y1  - 2025
VL  - 15
IS  - 3
DO  - 10.51847/i7wEFwrt2v
SP  - 85
EP  - 92
N2  - 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.
UR  - https://japer.in/article/digital-herbal-pharmacopeia-as-a-solution-for-herbal-plant-identification-based-on-computer-vision-bz8e14a9dmc0zcp
ER  -