PENERAPAN ALGORITMA K-NEAREST NEIGHBOR PADA SISTEM PAKAR UNTUK MENDIAGNOSA PENYAKIT PADA TANAMAN JAGUNG - Selmi Andriani; Oris Krianto Sulaiman; Tasliyah Haramaini (Deli Sains Informatika, 2021)
One of the declining levels of corn production is caused by the presence of disease. In addition, the delay in handling due to the lack of experts in the Kutacane area itself, so that it can affect the decline in plant production levels. Therefore, an application is needed to diagnose diseases in corn plants using expert system rules in decision making. In making this web-based expert system application using the KNN (K-Nearest Neighbor) algorithm, where the K-Nearest Neighbor algorithm is an approach to finding cases by calculating between new cases and old cases, which is based on the leakage of weights from a number of existing features. which can provide convenience in conducting consultations like an expert. This application serves as a tool to identify types of diseases in corn plants and how to overcome them. Users can only input the symptoms experienced by the system, then the system will provide output in the form of types of corn plant diseases and provide solutions based on similarities in previous cases. From this task, the final result can be known the results of the diagnosis of diseases in corn plants through a consultation process quickly and efficiently. Keywords: corn plant disease; expert system; KNN (K-Nearest Neighbor), web