Sistem Manajemen Diet Terintegrasi untuk Membership Gym Berbasis Web
Keywords:
Keywords: Artificial Intelligence, Diet Management, Gym Membership, Image Recognition, Web-based SystemAbstract
In this study, the rising trend of a healthy lifestyle has increased gym memberships, yet it is often not balanced with proper nutritional management. Many members struggle to accurately calculate macronutrient needs due to the lack of integration between physical exercise facilities and food intake tracking. This research aims to develop a web-based diet management system integrated with gym membership status. The development method includes requirements analysis, 3-tier architecture design, and the implementation of image recognition technology for nutrient identification via food photos. Results indicate that the system can recognize food types in less than 5 seconds and provide graphical visualizations of daily intake versus user calorie targets. The conclusion of this study is that an integrated platform can assist gym members in achieving fitness goals, whether for fat loss or bulking programs, more efficiently and accurately.
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