Browsing by Author "Kimayong, Princess Joy D."

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    (Don Mariano Marcos Memorial State University - Mid La Union Campus, 2025-11) Bernal, Yhoebe Rae C.; Acocos, Kyla Q.; Garcia, Jasmin M.; Kimayong, Princess Joy D.; Estira, Marydel C.; Mique Jr., Eusebio L.; Malicdem, Alvin R.; Pulmano, Dominador G.
    This study was conducted to support sugarcane farmers in detecting and managing leaf diseases that affect crop quality and yield, especially for Basi production. The capstone project aimed to build a dataset of sugarcane leaf images and train an optimized deep learning model using the MobileNetV3 architecture. The modeling and development process followed the CRISP-DM framework, ensuring structured stages from data understanding to model evaluation. The trained model was then integrated into both web and mobile platforms through the Agile Methodology. A descriptive and developmental research design was applied with twenty (20) respondents: five (5) agricultural staff, five (5) Basi producers, and ten (10) sugarcane farmersfrom Naguilian, La Union. The system achieved a 98% accuracy rate and a System Usability Scale (SUS)score of 85.6, indicating excellent usability. Respondents described the system as efficient, user-friendly, and highly valuable for early detection and effective management of common sugarcane leaf diseases.