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KLASIFIKASI KESEGARAN WORTEL MENGGUNAKAN INCEPTIONV3

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Carrot, scientifically known as Daucus carota L., is a root vegetable that is widely consumed around the world. Visual determination of carrot freshness visual determination by humans can be subjective and not always efficient due to the differences in viewpoints. The InceptionV3 model, which is one of the architectural models of CNN gets good results in classifying image cases. in classifying image cases, so the InceptionV3 model will be developed for carrot freshness classification. developed for carrot freshness classification. This model aims to identify whether a carrot can be considered fresh or rotten based on its visual image. Thus, this research can obtain good results to detect the Carrot Freshness and help in ensuring safe and high quality products to consumers in the agriculture and food industry. to consumers in the agriculture and food industry. The results showed model with 20 epochs, RMSprop optimizers, learning rate of 0.00001, dense with 128 neurons, Relu activation function, and dropout of 0.2, has successfully achieved an accuracy value of 94.17%, precision of 94.74%, sensitivity of 93.10%, and f1-score of 93.91%. It can be concluded that the classification of carrot freshness using the InceptionV3 model shows excellent very good performance.

Availability
Inventory Code Barcode Call Number Location Status
2407002967T144764T1447642024Central Library (REFERENCES)Available but not for loan - Not for Loan
Detail Information
Series Title
-
Call Number
T1447642024
Publisher
Indralaya : Prodi Teknik Informatika, Fakultas Ilmu Komputer.,
Collation
xiv, VI-2 hlm.; ilus.; tab.; 28 cm
Language
Indonesia
ISBN/ISSN
-
Classification
004.650 7
Content Type
Text
Media Type
unmediated
Carrier Type
unspecified
Edition
-
Subject(s)
Prodi Teknik Informatika
InceptionV3
Specific Detail Info
-
Statement of Responsibility
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