Deteksi Kesegaran Ikan Nila Berbasis Pengolahan Citra Digital Menggunakan Metode Convolutional Neural Network (CNN)

Apriany, Vidi (2026) Deteksi Kesegaran Ikan Nila Berbasis Pengolahan Citra Digital Menggunakan Metode Convolutional Neural Network (CNN). Bachelor thesis, Institut Teknologi Kalimantan.

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Abstract

Indonesia merupakan negara maritim dengan sumber daya ikan yang melimpah. Penentuan tingkat kesegaran ikan umumnya masih dilakukan secara manual oleh konsumen atau melalui pengujian mikrobiologi dan kimiawi yang memerlukan waktu dan peralatan khusus. Oleh karena itu, penelitian ini mengusulkan pendeteksian kesegaran ikan berbasis pengolahan citra digital menggunakan metode Convolutional Neural Network (CNN). Data yang digunakan berupa citra mata ikan nila yang diklasifikasikan ke dalam dua kelas, yaitu ikan segar dan ikan tidak segar. Tahapan penelitian meliputi preprocessing citra, pelatihan model CNN, serta pengujian performa model. Model dilatih selama 10 epoch dan dievaluasi menggunakan akurasi, confusion matrix, classification report, serta visualisasi hasil prediksi. Hasil pelatihan menunjukkan akurasi training sebesar 96% dan akurasi validasi sebesar 99,5% pada epoch terakhir. Pengujian terhadap 1.820 data uji menunjukkan bahwa seluruh data berhasil diklasifikasikan sesuai dengan kelasnya. Berdasarkan hasil tersebut, metode CNN dapat digunakan sebagai pendekatan pendukung dalam deteksi kesegaran ikan berbasis citra mata ikan sesuai dengan ruang lingkup data penelitian.

Item Type:	Thesis (Bachelor)
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:	Jurusan Teknologi Industri dan Proses > Teknik Elektro
Depositing User:	Vidi Apriany
Date Deposited:	08 Jan 2026 05:32
Last Modified:	08 Jan 2026 05:32
URI:	http://repository.itk.ac.id/id/eprint/24972

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