Dokumen Tesis

Dokumen Tesis

• By Sarasati, Fajar;
• Disertasi
• 274

Usaha sektor pertanian khususnya produksi tanaman padi sering mengalami ketidakpastian akibat penyakit yang menyerang. Tanaman padi yang terinfeksi penyakit jika tidak segera dibasmi beresiko menjalar ke tanaman padi lainnya, sehingga menyebabkan gagal panen. Resiko gagal panen tersebut terjadi akibat kesulitan yang dialami petani dalam mengidentifikasi penyakit padi secara kasat mata dengan cepat dan akurat. Tren teknologi dengan image processing yang diterapkan di bidang pertanian untuk mendeteksi penyakit padi sejak dini sehingga diharapkan dapat membantu petani untuk melakukan pengendalian penyebaran penyakit. Penelitian ini bertujuan untuk mengklasifikasikan penyakit padi berdasarkan kategori penyakit yang telah disepakati oleh 9 orang ahli melalui media kuesioner. Dimana dalam mengklasifikasikan penyakit padi ini dilakukan dengan menggunakan arsitektur EfficientNetB4 menjadi 5 kategori penyakit padi diantaranya Blas, Brown Spot, Hawar, Kresek, dan Narrow Brown Spot yang sebelumnya dilakukan segmentasi dengan menggunakan metode K-Means. Sehingga pada penelitian ini menghasilkan klasifikasi penyakit padi dengan tingkat akurasi sebesar 94.53%.

• Katakunci Klasifikasi, Penyakit Padi, EfficientNetB4, Segmentasi, K-Means
• URL http://
• Penerbit Universitas Nusa Mandiri, Jakarta DKI Jakarta

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