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

MARDILAH, RISKA TRI and Rini, Dian Palupi and Rizqie, M. Qurhanul (2023) SISTEM PENDETEKSI ALERGEN PADA PRODUK KEMASAN UNTUK PENDERITA ECZEMA MENGGUNAKAN METODE OCR. Undergraduate thesis, Sriwijaya University.

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Abstract

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%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Eczema, makanan, deteksi, komposisi, kemasan, OCR, OpenCV, Tesseract, alergen, akurasi
Subjects:	T Technology > T Technology (General) > T1-995 Technology (General) Z Bibliography. Library Science. Information Resources > Z52-52.5 Word processing Z Bibliography. Library Science. Information Resources > Z696-697 Classification and notation
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Riska Tri Mardilah
Date Deposited:	26 Jul 2023 02:13
Last Modified:	26 Jul 2023 02:13
URI:	http://repository.unsri.ac.id/id/eprint/121435

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