LAKASABrowsing by Author "Lumaad, Zyla Rea D."

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Pestpix:
(Don Mariano Marcos Memorial State University – Mid La Union Campus, 2025-11) Tangalin, Mezrhime Kyle B.; Fortes, John Reymond N. .; Lumaad, Zyla Rea D.; Vallo, Maria Juliana N; Sardeng, Shekainah Kim A.; Hortizuela, Manny R.; Rodriguez, Marylen D.; Bajit, Danilo T.
Agricultural productivity is continuously threatened by pests and diseases, demanding rapid and accurate identification to safeguard global food security. Traditional expert-dependent methods are often slow, hindering timely intervention. This study addressed this challenge by developing and implementing the PESTPIX mobile application for vegetable pest identification using machine learning. The research employed descriptive and applied research designs, applying the CRISP-DM framework for the machine learning model development and the Agile methodology for application development, ensuring a user-centric and iterative process. The level of usability was assessed through the PSSUQ, resulting to high usability which confirmed the application's ease of use, functional completeness, and clear content, and validated its practical value and high potential for successful adoption by Filipino vegetable farmers. The successful integration of a machine learning solution into a mobile platform offered an accessible solution to strengthen sustainable agricultural practices and directly contribute to increased small-scale farmer productivity.