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All Journal G-Tech : Jurnal Teknologi Terapan
Stevanus Kurniawan
Universitas Multimedia Nusantara, Indonesia
Computer Science & IT Decision Sciences, Operations Research & Management Energy Engineering

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Empowering Pregnant Women with Tailored Food Recommendations through K-Nearest Neighbors in Android Application Stevanus Kurniawan; Raymond Sunardi Oetama
G-Tech: Jurnal Teknologi Terapan Vol 8 No 2 (2024): G-Tech, Vol. 8 No. 2 April 2024
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33379/gtech.v8i2.4084

Abstract

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.
Co-Authors Raymond Sunardi Oetama