IDENTIFIKASI KESEGARAN SAYURAN MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK

• MUHAMMAD SYAHRANI
• 14002621

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ABSTRAK

 

ABSTRAK Nama : Muhammad Syahrani NIM : 14002621 Program Studi : Ilmu Komputer Jenjang : Strata Dua (S2) Konsentrasi : Image processing Judul Tesis : “Identifikasi Tingkat Kesegaran sayuran Menggunakan
Convolutional Neural Network” Penelitian ini untuk identifikasi tingkat kesegaran sayuran yang dilakukan buruh tani ketika pemanen hingga ke produsen serta konsumen. Mengandalkan
tacit knowledge petani tentunya ada keterbatasan, sehingga praktis bila kecerdasan tersebut dialihkan kepada mesin. Metode penentuan tingkat kesegaran sayuran menggunakan 3 Model Arsitektur Convolutional Neural Network (CNN) dengan melakukan Optimasi pada beberapa parameter yaitu, optimizer, learning rate, dan epoch.. Model yang dihasilkan dari pelatihan 20 epoch dapat disimpulkan bahwa untuk Bayam didapatkan oleh dari lima hidden layer dengan learning rate 0.001 pada optimizer Adam yaitu sebesar 90 %. Kemudian untuk sayuran Brokoli didapatkan dari tiga hidden layer dengan optimasi learning rate 0.001 pada optimizer Adam yaitu sebesar 64 %. Selanjutnya untuk sayuran Cabai didapatkan dari tiga hidden layer dengan optimasi learning rate 0.001 pada optimizer Adam yaitu sebesar 70 %. Kemudian untuk Sayuran Kangkung didapatkan dari tiga
hidden layer dengan optimasi learning rate 0.001 pada optimizer SGD yaitu sebesar 82 %. Untuk sayuran Sawi didapatkan dari tiga hidden layer dengan optimasi learning rate 0.0001 pada optimizer Adam yaitu sebesar 80 %. Dan untuk sayuran Tomat didapatkan dari lima hidden layer dengan optimasi learning
rate 0.001 pada optimizer Adam yaitu sebesar 66 %. Kata kunci : Sayuran, CNN, lapisan tersembunyi, Identifikasi
 

KATA KUNCI

Identifikasi Tingkat Kesegaran Sayuran,Convolutional Neural Network

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DAFTAR PUSTAKA

 

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