IV. Discussion

The deployment of Stayfit over a one-month pilot period from December 19, 2024, to January 19, 2025, demonstrated several key benefits, as reflected in the collected data:

• Optimized System Performance: Stayfit has streamlined its features, reducing processing time for functions like scheduling and workout requests. However, with an expanding user base, there’s room to further enhance performance by implementing load balancing and optimizing backend processes. Future improvements may include cloud-based scaling to ensure that the system can handle higher traffic loads without compromising performance or speed.

• Enhanced User Interaction: The current user interface is functional but could benefit from further refinements. Simplifying navigation and introducing personalized user dashboards for tracking progress, goals, and trainer interactions could improve user experience. Future updates might integrate AI to provide more tailored workout suggestions based on user behavior and fitness data.

• Comprehensive Data Security: While user data is securely encrypted, incorporating advanced data protection technologies such as end-to-end encryption for workout plans and payment information could provide an added layer of security. Blockchain technology could be explored for transparent, decentralized management of user records, ensuring both security and privacy are at the forefront.

• Broadened Accessibility: While Stayfit is designed for a wide range of users, the app could improve its accessibility for people with disabilities. Features like voice navigation, screen reader compatibility, and customizable font sizes could be added to ensure that everyone can easily navigate and benefit from the platform. Additionally, multi-language support could help extend Stayfit’s reach to a more diverse audience.

Figure 6 List of certified fitness trainers

Figure 6, displays information about a certified fitness trainer named Albert Adang, including his details. The figure also includes an option to "Assign client," indicating its use in a system for managing trainer-client assignments. To improve clarity and functionality, adjustments such as adding a unique trainer ID, categorizing trainers by specialization, and including certification expiration dates may be necessary. Additionally, enhancing the layout with clear headings and search filters would make the list more user-friendly for administrators assigning clients efficiently.

Figure 7 Progress Tracking

Figure 7 presents the weight loss progress of two clients (Roy Francisco and Kurt Daraposa) over 22 days, displaying their starting and target weights, along with periodic measurements. Roy’s data is consistent, but Kurt’s target weight appears contradictory (62 kg → 79 kg), and "WA" marks missing entries. To improve clarity and usefulness, future enhancements should include correcting data errors (e.g., Kurt’s target), replacing "WA" with "N/A," adding body composition metrics (e.g., body fat %), and incorporating visual trends (e.g., graphs). Standardized time intervals, progress summaries, and input validation would further refine the tracking system.

Figure 8 Customer Engagement

This table tracks the login/logout times of Roy Francisco and Kurt Daragosa in December 2024 and January 2025. It shows their engagement durations but could be improved by adding total time calculations, consistent date formatting, and clearer visual highlights for better readability.