Implementasi Convolutional Neural Network Untuk Identifikasi Penyakit Daun Gambas
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Keywords

Identifikasi
Convolutional Neural Network
Luffa Acutangula

How to Cite

Implementasi Convolutional Neural Network Untuk Identifikasi Penyakit Daun Gambas. (2020). Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi), 4(3), 137-142. https://doi.org/10.29407/inotek.v4i3.76

Abstract

Tanaman Gambas atau oyong (Luffa acutangula L.) termasuk golongan sayuran dan buah yang mengandung  nutrisi  seperti  vitamin,  mineral  dan  serat.  Proese  penanaman  gambas  tidak  luput  dari  masalah seperti  adanya  serangan  hama  dan  penyakit  yang  bisa  mengakibatkan  kegagalan  panen.  Proses  identifikasi penyakit yang dilakukan manual dengan indera penglihatan manusia memiliki kekurangan yaitu penilaian yang bersifat subyektif yang dipengaruhi oleh kurangnya konsentrasi dan rasa lelah serta perlu pengalaman yang cukupbanyak.Penerapan Jaringan Syaraf Tiruan metode Convolutional Neural Network dengan arsitektur MobileNet untuk melakukan proses identifikasi 3 jenis penyakit pada tanaman gambas yaitu Embun Bulu, Kumbang Daun, dan Ulat Daun memiliki akurasi terbaik pada epoch 25 dan learning rate 0,001 dengan akurasi training senilai 92% dan akurasi cross-validation 91,1% dan akurasi testing senilai 90%.

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