CD Skripsi

Klasifikasi Jenis Rempah-Rempah Menggunakan Metode Convolutional Neural Network

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Spices represent a natural wealth in Indonesia that must be preserved. Distinguishing between various types of spices poses a significant challenge for some individuals due to their visual similarities. The processing of packaged spices, minimal direct involvement in their processing, and a lifestyle inclined towards consuming fast food are factors contributing to a lack of knowledge regarding the authentic forms of spices. Despite traditional spice recognition through guidance from books, the internet, or an expert, the limited comprehensive knowledge of each spice's characteristics results in difficulties for the community in identification. To address this issue, a system is required to assist in identifying types of rhizomes, one of which involves employing Convolutional Neural Network methods through image processing technology. This method represents a deep learning technique proven to be effective in classifying types of rhizomes based on their visual features, offering a modern and easily accessible solution for spice recognition. The image dataset is categorized into four classes, with each class comprising 250 images for a total of 1000 images. The network architecture utilized in the model consists of four convolutional layers. Test results demonstrate that the model excels in image classification, achieving the highest test accuracy value of 90%.

Keywords: Classification, Convolutional Neural Network, Image Processing, Rhizome, Spices.

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

1907124638

Penerbit

Pekanbaru : Universitas Riau - F. Teknik - Teknik Elektro., 2023

Deskripsi Fisik

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Bahasa

Indonesia

ISBN/ISSN

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Klasifikasi

1907124638

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

TEKNIK ELEKTRO

Info Detail Spesifik

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Pernyataan Tanggungjawab

Vina

Versi lain/terkait

Lampiran Berkas

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