Apandi, Norqistina Afsha Afzan
(2025)
Food recommendation based on their nutrition using K-means algorithm / Norqistina Afsha Afzan Apandi.
Degree thesis, Universiti Teknologi MARA, Terengganu.
Abstract
The food recommendation system is designed to help users find foods with similar nutritional content. The user only needs to input a food item, and the system will suggest other foods with similar nutritional profiles. K-means clustering is utilized to group foods based on their nutrient levels, enabling the system to identify foods that share comparable nutrition. Once the user inputs a food item, the system calculates the closest match from the clusters and suggests foods that align with the nutritional characteristics of the input food. Additionally, the system evaluates the nutrient levels of each food item, categorizing them as low, medium, or high in terms of specific nutrients (such as calories, protein, fats, etc.).
Metadata
Item Type: | Thesis (Degree) |
---|---|
Creators: | Creators Email / ID Num. Apandi, Norqistina Afsha Afzan 2023115055 |
Contributors: | Contribution Name Email / ID Num. Thesis advisor Fadzal, Ahmad Nazmi UNSPECIFIED |
Subjects: | Q Science > QA Mathematics > Instruments and machines > Electronic Computers. Computer Science > Computer software > Software measurement |
Divisions: | Universiti Teknologi MARA, Terengganu > Kuala Terengganu Campus > Faculty of Computer and Mathematical Sciences |
Programme: | Bachelor of Computer Science (Hons) |
Keywords: | K-Means Algorithm, Food Recommendation |
Date: | 2025 |
URI: | https://ir.uitm.edu.my/id/eprint/115273 |
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