Prayoga, Ryan Sea (2025) KLASIFIKASI JENIS LOVEBIRD MENGGUNAKAN ALGORITMA CONVOLUTIONAL NEURAL NETWORK (CNN) DENGAN ARSITEKTUR RESIDUAL NETWORKS 50. Undergraduate thesis, Universitas Nusantara PGRI Kediri.
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Abstract
Penelitian ini bertujuan mengembangkan sistem klasifikasi otomatis untuk mengidentifikasi jenis lovebird berdasarkan gambar menggunakan algoritma Convolutional Neural Network (CNN) dengan arsitektur ResNet-50. Data citra yang digunakan diproses melalui tahapan resize dan normalisasi, kemudian dilatih dan diuji menggunakan platform Google Colab dengan dukungan GPU. Model yang dikembangkan mampu mencapai akurasi sebesar 87,5% dan dievaluasi melalui confusion matrix serta metrik precision dan recall. Sistem dirancang dengan antarmuka berbasis web menggunakan Streamlit, sehingga memudahkan pengguna dalam mengunggah gambar dan memperoleh hasil klasifikasi secara langsung. Penelitian ini menunjukkan bahwa pendekatan deep learning dapat digunakan secara efektif dalam penerapan sistem klasifikasi citra berbasis visual secara praktis.
Item Type: | Thesis (Undergraduate) |
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Uncontrolled Keywords: | Convolutional Neural Network, Klasifikasi Citra, Lovebird, Residual Networks 50 |
Subjects: | 410 Engineering science > 457 Computer engineering 410 Engineering science > 459 Computer science 410 Engineering science > 461 Information systems |
Divisions: | Fakultas Teknik dan Ilmu Komputer > S1-Teknik Informatika |
Depositing User: | Ryan Sea Prayoga |
Last Modified: | 06 Aug 2025 16:30 |
URI: | http://repository.unpkediri.ac.id/id/eprint/19994 |
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KLASIFIKASI JENIS LOVEBIRD MENGGUNAKAN ALGORITMA CONVOLUTIONAL NEURAL NETWORK (CNN) DENGAN ARSITEKTUR RESIDUAL NETWORKS 50. (deposited UNSPECIFIED)
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