The study explores a hybrid recommendation system for improving women's health nutrition during the menstrual cycle, addressing issues like hair loss, heavy bleeding, and pain. It utilizes blockchain technology to manage menstrual cycles and nutrition recommendations, focusing on Melia dubia liquid and fermented rice water as nutritional suggestions. The system employs collaborative and content-based filtering, achieving a 94% accuracy in its recommendations. The findings suggest that this approach is effective and could enhance current nutritional guidance practices for menstruating women.
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