Empowering Pregnant Women with Tailored Food Recommendations through K-Nearest Neighbors in Android Application

Stevanus Kurniawan (Universitas Multimedia Nusantara, Indonesia)
Raymond Sunardi Oetama (Universitas Multimedia Nusantara, Indonesia)

G-Tech : Jurnal Teknologi Terapan
Vol 8 No 2 (2024): G-Tech, Vol. 8 No. 2 April 2024

When at a restaurant, pregnant women often face difficulties in choosing healthy and appropriate foods during pregnancy, primarily due to lack of knowledge, uncertainty about food ingredients, and difficulty in remembering the list of foods to avoid. This research aims to assist restaurants and pregnant women in avoiding consuming foods containing unhealthy ingredients for pregnant women. Our solution is to develop an Android-based application that can detect foods containing ingredients that pregnant women should not consume and then offer alternative foods that are similar to those foods. The application is developed using the Rapid Application Development method, and the algorithm used is the K-nearest Neighbor. The application has been tested with a User Acceptance Test with an 84-90% acceptance rate.