BahanbaKu: intuitive mobile application for buying recipe ingredients

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Komang Candra Brata, Rigel Vibi Ramadhan, Irvan Rizki Nugraha, Rifqi Hilmy Zhafrant, Ananda Ilyasa Putra

2024 IAES International Journal of Artificial Intelligence Vol. 13 Issue 3 Article Cited by 0 SDG 17SDG 9SDG 8 Quartile

Abstract

Many solutions were proposed to help people get their food or recipe ingredients easily without having to go to the market in person. Especially for people who have limited time and energy to go out and buy groceries. However, the existing solutions still lack the intuitiveness for users to get the ingredient information of a food recipe and still can’t facilitate the customers to have an all-in-one solution to get the needed ingredients. This study aims to combine the machine learning modalities and image recognition approach to provide a mobile app that can help people find food recipes intuitively and provide a digital ecosystem that can accommodate collaboration between various business actors including the micro, small, and medium enterprises (MSMEs). Instead of users buying items separately, the unique value of the proposed app (BahanbaKu) is that each of the ingredients needed by the user will be delivered in a single package. The preliminary evaluation result reveals that the accuracy of the proposed app is promising to assist people while getting recipe information for a particular food. The proposed app is also considered intuitive to the users with 81.7 SUS score. © 2024, Institute of Advanced Engineering and Science. All rights reserved.

Affiliations

Department of Informatics Engineering, Faculty of Computer Science, Universitas Brawijaya, Malang, Indonesia; Graduate School of Natural Science and Technology, Okayama University, Okayama, Japan; Department of Informatics, Faculty of Information Technology and Data Science, Universitas Sebelas Maret, Surakarta, Indonesia

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