Klasifikasi Penyakit Pada Tanaman Kopi Menggunakan K-nearest Neighbor Dioptimasi Dengan Genetic Algorithm
DOI:
https://doi.org/10.34818/eoe.v9i3.17996Abstrak
Abstrak Daun kopi merupakan salah satu bagian yang paling mudah untuk dideteksi Ketika tanaman kopi terserang penyakit. Banyak sekali faktor yang dapat mengakibatkan tanaman kopi menjadi sakit, beberapa faktor penyebabnya yaitu hama, karat daun, jamur daun dan juga bercak daun. Dengan memanfaatkan image processing dapat membantu mengklasifikasikan penyakit melalui citra daunnya, sehingga dapat dengan tepat diberikan penanganan pada tanaman yang sakit tersebut. Dengan melakukan ekstraksi fitur pada fitur warna menggunakan Color Moment. Kemudian dilakukannya klasifikasi menggunakan metode non deep learning K-Nearest Neighbor dan dilakukan optimasi dengan menggunakan Genetic Algorithm, maka didapatkan nilai k yang paling optimal sehingga nilai akurasi yang didapatkan adalah nilai akurasi maksimal yang bisa dihasilkan oleh KNN. Hasil tersebut didapatkan akurasi terbaik dengan menggunakan color moment pada ruang warna RGB yaitu sebesar 78.9% dengan menggunakan klasifikasi KNN+GA. Kata kunci : image processing, color moment, knearest neighbor, genetic algorithm, daun kopiReferensi
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