ANALISIS DAN PENGEMBANGAN APLIKASI MOBILE DIET ARTIFICIAL INTELLIGENCE DENGAN PENDEKATAN CHALLENGE BASED
DOI:
https://doi.org/10.47080/simika.v6i1.2365Keywords:
iOS, Machine Learning, Meal Planner, Technology Acceptance ModelAbstract
College life is a period where most students are required to live independently and begin to plan for their diet. Unfortunately, they commonly adopt poor dietary habits due to a lack of nutritional literacy. The lack of knowledge about healthy diets may potentially affect their health. This study aims to develop a meal planner iOS application that integrates daily calorie information and includes a machine learning-based meal recommendation feature. The application was built using Swift programming language along with Challenge Based Learning (CBL) framework. The application then was used to analyze the effectiveness usage of the meal planner mobile application using Technology Acceptance Model (TAM). The study was conducted by distributing an online questionnaire to 360 university students in Batam City. Hypothesis testing was carried out through linear regression using SPSS 25 software. The results showed a positive impact of Perceived Ease of use toward Perceived Usefulness in using the meal planner application. Additionally, both Perceived Usefulness and Perceived Ease of use also positively impact the Attitude Towards Using the meal planner application. The results of this study should be beneficial to the future developments of meal planner applications so that they can improve the nutritional literacy of students on living a healthy lifestyle and adopt new technologies for future research.
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