CONVOLUTIONAL NEURAL NETWORK UNTUK KLASIFIKASI TINGKAT KEMATANGAN BUAH PEPAYA

• YUSUF ARIF SETIAWAN
• 14002634

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ABSTRAK

 

ABSTRAK
Nama : Yusuf Arif Setiawan .

NIM : 14002634
Program Studi : Ilmu Komputer
Fakultas : Teknologi Informasi
Jenjang : Strata Dua (S2)
Konsentrasi : Image Processing
Judul Tesis : “Convolutional Neural Network Untuk Klasifikasi Tingkat
Kematangan Buah Pepaya”
Penelitian ini untuk menentukan tingkat kematangan buah pepaya california
(Carica papaya l.) yang dilakukan buruh tani ketika pemanenan. Turn over
tenaga kerja dipertanian terhitung tinggi, sehingga buruh keluar masuk dari
pekerjaan. Hal ini menyita waktu petani karena harus selalu mengajarkan kepada
buruh baru bagaimana cara memanen buah pepaya. Pemanenan yang salah
menyebabkan kerugian. Mengandalkan tacit knowledge petani tentunya ada
keterbatasan, sehingga praktis bila kecerdasan tersebut dialihkan kepada mesin.
Metode penentuan tingkat kematangan buah pepaya menggunakan Arsitektur
CNN dengan dataset 1.500 citra buah pepaya yang dibagi menjadi data latih dan
data uji. Model yang dihasilkan dari pelatihan 20 epoch menunjukkan bahwa
pendekatan transfer learning clasification model VGG16 menunjukkan akurasi
paling baik yaitu 97 persen.
Kata kunci: CNN, Tacit Knowledge, Transfer Learning, Classification, Maturity
level

KATA KUNCI

Convolutional Neural Network

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DAFTAR PUSTAKA

 

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