Web-Based Application for Diagnosing Corn Plant Diseases Using the Naive Bayes Method
Aplikasi Berbasis Web Diagnosa Penyakit Tanaman Jagung Menggunakan Metode Naive Bayes
DOI:
https://doi.org/10.21070/ups.7507Keywords:
Expert System, Naive Bayes, Maize, Maize DiseaseAbstract
Maize (Zea Mays) originates from the Mesoamerican region and is the second most important source of carbohydrates after rice with the main benefits as human food, livestock, and other needs. As an effort to support food self-sufficiency, maize cultivation in Indonesia is carried out intensively to meet the increasing market demand. Diseases are a major challenge in increasing maize productivity. To help farmers overcome this problem, an expert system can be used as a knowledge-based decision-making tool from experts with the Naïve Bayes method approach. The system is equipped with a disease diagnosis feature on corn plants that effectively helps farmers identify problems quickly and accurately. Testing on the system using the Black-box Testing method shows that the system runs according to predetermined specifications. With the expert system, farmers can diagnose corn diseases quickly and accurately, thereby increasing productivity and crop quality.
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