Skripsi

KLASIFIKASI SAPI TERNAK NORMAL DAN TERINFEKSI LUMPY SKIN DISEASE MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK (CNN)

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Penilaian

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Lumpy Skin Disease (LSD) is a contagious disease in cattle that causes significant losses in the livestock sector, making early detection crucial. This study aims to classify cattle into normal and LSD-infected categories using the Convolutional Neural Network (CNN) method with the ResNet50 architecture. The dataset consists of 4000 images, divided into 80% training data, 10% validation data, and 10% testing data. The model was trained to recognize visual features of infected cattle and demonstrated excellent performance, achieving an average accuracy of 96.75%, precision of 96.78%, recall of 96.75%, and F1-score of 96.76%. These results indicate that the ResNet50 CNN architecture is effective for detecting Lumpy Skin Disease in cattle and has the potential to be implemented as an automated diagnostic tool in the livestock industry.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2507003670	T176748	T1767482025	Central Library (Reference)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1767482025

Publisher

Indralaya : Prodi Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2025

Collation

xiv, 83 hlm.; ilus.; tab.; 29 cm.

Language

Indonesia

ISBN/ISSN

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Classification

004.07

Content Type

Text

Media Type

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Carrier Type

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Edition

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Subject(s)

Teknik Informatika

Specific Detail Info

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Statement of Responsibility

MI

Other version/related

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