According to the latest data from the World Health Organization (WHO) published in 2023, an estimated 262 million people worldwide suffer from food allergies. This figure represents a significant increase over previous years and reflects a rapidly growing global public health crisis. Food allergies have the potential to cause a variety of negative impacts, ranging from mild to life-threatening reactions. One solution that can be proposed to address the problem of food allergies globally is to build a recipe recommendation application for allergy sufferers. This application is accessible to all and aims to provide a variety of recipes that are safe, nutritious, and in accordance with user preferences. Thus, this application helps individuals suffering from food allergies to avoid food ingredients that trigger allergic reactions, thereby reducing the risk of serious allergic reactions.
Amidst the escalating global challenge posed by food allergies, our project endeavors to pioneer a solution: a personalized recipe recommendation application. The World Health Organization (WHO) has underscored a notable increase in food allergy cases worldwide, necessitating urgent action to address this pressing public health crisis. Our application will leverage advanced machine learning algorithms to furnish tailored recipe suggestions that accommodate the specific allergies of users, thereby ensuring their safety and well-being. Through the empowerment of individuals impacted by food allergies, our team aspires to enhance their quality of life and mitigate the associated risks of allergic reactions. We are firmly convinced that by furnishing a pragmatic and accessible tool for managing food allergies, we can profoundly influence public health outcomes and cultivate a more inclusive and supportive community for individuals affected by this pervasive issue.
Looking at allergy case data from WHO, we noticed that people tend to be unaware of allergies that may look mild but can be dangerous. Many allergy cases in the data come from daily food consumption. Therefore, we decided to create an app that can provide food recommendations for users based on the allergies they have. The app we created will also provide food recipe recommendations and supporting features such as cooking video tutorials embedded in the app.
| Bangkit ID | Name | Learning Path | University | |
|---|---|---|---|---|
| M006D4KY3102 | Carel Martin | Machine Learning | Universitas Brawijaya |  |
| M665D4KY2033 | Dimas Ilham | Machine Learning | STMIK Kaputama | |
| M319D4KX2586 | Novariya Br Saragih | Machine Learning | Universitas Sumatera Utara | |
| C006D4KY0118 | Stefanus Rangga Ananta Susanto | Cloud Computing | Universitas Brawijaya | |
| C319D4KX0594 | Latifah Putri Simanjuntak | Cloud Computing | Universitas Sumatera Utara | |
| A614D4KY4153 | Muhammad Juzairi Safitli | Mobile Development | Universitas Nurdin Hamzah | |
| C319D4KX0594 | Rizki Wahyudi | Mobile Development | Universitas Sumatera Utara | |
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