Skripsi

SISTEM PENDETEKSI ALERGEN PADA PRODUK KEMASAN UNTUK PENDERITA ECZEMA MENGGUNAKAN METODE OCR

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Penilaian

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Eczema, also known as dermatitis, is a chronic skin condition characterized by recurring episodes of dry and itchy skin. While it cannot be cured, it can be managed through medication and by addressing triggering factors such as stress and certain foods. To minimize eczema flare-ups through dietary intervention, researchers have conducted studies to detect allergenic food compositions using OCR techniques like OpenCV and Tesseract. The implementation of OpenCV and Tesseract involved analyzing 100 images of packaged food compositions to identify allergens based on data collected from various sources. The results yielded an average text detection accuracy of 61.88% and an average allergen detection accuracy of 83.06%. Additionally, the highest accuracy achieved in text detection was 78.52%, and the highest accuracy in allergen detection was 100%. Conversely, the lowest accuracy in text detection was 22.20%, and the lowest accuracy in allergen detection was 0.00%.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2307003259	T121435	T1214352023	Central Library (REFERENS)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1214352023

Publisher

Indralaya : Jurusan Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2023

Collation

xiv, 62 hlm.; ilus.; 29cm

Language

Indonesia

ISBN/ISSN

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Classification

006.4 07

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Jurusan Teknik Informatika
Computer pattern recognition

Specific Detail Info

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Statement of Responsibility

ANUG

Other version/related

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