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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Mohamad Yusuf Arrahman
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Diagnosis Hama Penyakit Tanaman Bawang Merah Menggunakan Algoritma Modified K-Nearest Neighbor (MKNN) Mohamad Yusuf Arrahman; Nurul Hidayat; Sutrisno Sutrisno
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 1 (2019): Januari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Red onion (Allium cepa L.) is a spice vegetable that is quite popular in Indonesia, has high economic value, serves as flavoring, and can be used as a traditional medicine ingredient. . However, obstacles encountered in the process of planting onions, one of the pests and diseases that often lead to crop failure. One method to diagnose diseases of shallot plants can be done with modified k-nearest neighbor (MKNN). The expert system of onion plant disease diagnosis using the k-nearest neighbor (MKNN) modified method can make it easier to detect diseases that attack onions based on symptoms. The k-nearest neighbor (MKNN) modified method is implemented on an expert system inference engine in order to draw conclusions based on existing knowledge on the knowledge base. Results obtained after the system accuracy test of 83.33% indicating that the modified k-nearest neighbor (MKNN) method is suitable for clove plant disease onion.
Co-Authors Nurul Hidayat Sutrisno Sutrisno