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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Muhammad Kurniawan Khamdani
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Implementasi Metode K-Nearest Neighbor Untuk Mendiagnosis Penyakit Tanaman Bawang Merah Muhammad Kurniawan Khamdani; Nurul Hidayat; Ratih Kartika Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 1 (2021): Januari 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Onion is a spices plant which have a usage as cooking seasoning flavour. The use benefit of red onion other than a cooking seasoning flavour is also as the source of Vitamin B and C, protein, fat and carbohydrate which is needed by human body. Badan Pusat Statistik (BPS) takes a note on the red onion production of 8.305 ton in 2013 that decreasing as much 5.851 ton (41.33%) from last year. The low productivity of red onion is caused by the implementation of cultivation technology. With the development of increasingly sophisticated technology, the existence of software that can help to diagnose pests and diseases will greatly help farmers to diagnose early and make early treatment of pests and diseases of red onion plants. One method that can be used to diagnose pests and diseases in red onion plants is k-nearest neighbor. k-nearest neighbor (kNN) is belong to instance-based learning group. This algorithm is also one of the lazy learning techniques. kNN is done by looking for group of k object in the closest or similar training data with objects on new data or testing data. in this study the k-nearest neighbor method is used to diagnose onion plants with an average accuracy of 85.835%.
Co-Authors Nurul Hidayat Ratih Kartika Dewi