Gymnastiar Ramadhan, . (2025) RANCANG BANGUN APLIKASI BERBASIS PWA UNTUK KLASIFIKASI NUTRI-GRADE MENGGUNAKAN CITRA INFORMASI NILAI GIZI DENGAN DEEP LEARNING. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
Non-communicable diseases (NCDs), such as diabetes and cardiovascular diseases, are rising significantly in Indonesia, partly due to excessive sugar and saturated fat consumption. While Singapore has implemented the Nutri-Grade labeling system to guide consumers in selecting healthier beverages, Indonesia has yet to adopt a similar initiative. This research aims to design and develop a Progressive Web Application (PWA) capable of classifying Nutri-Grade levels of packaged beverages using deep learning technology. The proposed system utilizes the YOLOv8 object detection algorithm to identify nutritional information from product label images, followed by Optical Character Recognition (OCR) to extract specific nutritional values such as sugar, saturated fat, lactose, and serving size. These extracted values are then used to compute Nutri-Grade classification based on Singapore's standards. The application is optimized for mobile devices and supports both online and offline modes. To evaluate the application’s functionality and performance, two testing methods were conducted: black box testing to assess feature correctness based on input-output behavior, and lighthouse testing to measure performance, and accessibility metrics. The testing results indicate that the system performs effectively in extracting nutritional data and classifying Nutri-Grade levels. This application is expected to serve as a temporary solution for Indonesian consumers to make healthier beverage choices prior to the official adoption of Nutri-Grade by the government.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | [No.Panggil: 2110511015] [Pembimbing 1: Didit Widiyanto] [Pembimbing 2: Jayanta] [Penguji 1: Musthofa Galih Pradana] [Penguji 2: Muhammad Panji Muslim] |
| Uncontrolled Keywords: | Nutri-Grade, Nutrition Facts Extraction, Progressive Web Application, YOLOv8 |
| Subjects: | Q Science > Q Science (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software T Technology > T Technology (General) |
| Divisions: | Fakultas Ilmu Komputer > Program Studi Informatika (S1) |
| Depositing User: | GYMNASTIAR RAMADHAN |
| Date Deposited: | 06 Aug 2025 07:40 |
| Last Modified: | 06 Aug 2025 07:40 |
| URI: | http://repository.upnvj.ac.id/id/eprint/37432 |
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- RANCANG BANGUN APLIKASI BERBASIS PWA UNTUK KLASIFIKASI NUTRI-GRADE MENGGUNAKAN CITRA INFORMASI NILAI GIZI DENGAN DEEP LEARNING. (deposited 06 Aug 2025 07:40) [Currently Displayed]
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