Abstract

Nutrition literacy and tools for calculating individual energy needs remain limited among adolescents and adults, potentially hindering balanced diet implementation in daily life. This study aims to develop SehatMate, a web-based nutrition system integrating Basal Metabolic Rate (BMR) and Total Daily Energy Expenditure (TDEE) calculations with dietary recording and a food composition database. An Agile software engineering approach was used with iterative planning, UML-based design, web framework and MySQL implementation, followed by testing, documentation, and deployment. BMR is calculated using the Harris–Benedict equation, while TDEE is derived from an activity factor. Food composition data from the Indonesian Food Composition Table were integrated into the system. System validation included comparison with manual calculations and black-box testing of user and admin functions across devices and browsers. The results show that SehatMate provides modules for registration, profile management, energy requirement calculation, food selection, daily intake recording, and nutrient adequacy recap. Findings indicate that system-generated BMR and TDEE values are consistent with manual calculations, and functional testing confirms system reliability across platforms. In conclusion, the system meets functional requirements for supporting nutrition education and dietary planning; however, further development is required to expand the nutrient database, improve personalization, and evaluate usability in real-user settings.

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References

• 1. Savarino G, Corsello A, Corsello G. Macronutrient balance and micronutrient amounts through growth and development. Ital J Pediatr. 2021;47(1):109.
• 2. Kiani AK, Medori MC, Dhuli K, et al. Clinical assessment for diet prescription. J Prev Med Hyg. 2022;63(2 Suppl 3):E102-E124.
• 3. Retiaty F, Andarwulan N, Palupi NS, Ernawati F, Kazimierczak R, Srednicka-Tober D. Contribution of Food, Energy, Macronutrients and Fiber Consumption Patterns to Obesity and Other Non-Communicable Disease Risks in the Indonesian Population. Nutrients. 2025;17(9).
• 4. Kemenkes. Tabel Angka Kecukupan Gizi. In:2013.
• 5. Luy SC, Dampil OA. Comparison of the Harris-Benedict Equation, Bioelectrical Impedance Analysis, and Indirect Calorimetry for Measurement of Basal Metabolic Rate among Adult Obese Filipino Patients with Prediabetes or Type 2 Diabetes Mellitus. J ASEAN Fed Endocr Soc. 2018;33(2):152-159.
• 6. Jilkova A, Lampova B, Kade O, et al. Resting Energy Expenditure in Patients with Extreme Obesity: Comparison of the Harris-Benedict Equation with Indirect Calorimetry. J Clin Med. 2024;13(19).
• 7. Chandwani D, Singh V, Meena S. Impact of Social Media on Dietary Choices of Adolescents and Young Adults: A Scoping Review. European Journal of Nutrition & Food Safety. 2025;17(3):81-87.
• 8. Khaleel S, Abbas N, Niazi D, et al. Characteristics and correlates of the use of social media for nutrition among young adults in the United Arab Emirates. BMC Public Health. 2025;25(1):1994.
• 9. O'Hara C, Gibney ER. Meal Pattern Analysis in Nutritional Science: Recent Methods and Findings. Adv Nutr. 2021;12(4):1365-1378.
• 10. Neves PA, Simoes J, Costa R, et al. Thought on Food: A Systematic Review of Current Approaches and Challenges for Food Intake Detection. Sensors (Basel). 2022;22(17).
• 11. Al Naabi Y, Ibrahim N, Dhillon JS. Designing sustainable mobile weight management applications: information technology (IT) experts perspectives. Mhealth. 2024;10:25.
• 12. Akbar W, Sejati, R.H.P. Optimization of Elementary School Learning Processes through a multi-platform e-Learning System. Journal of Scientific Research, Education and Technology. 2025;4(4):2652-2675.
• 13. Tsolakidis D, Gymnopoulos LP, Dimitropoulos K. Artificial Intelligence and Machine Learning Technologies for Personalized Nutrition: A Review. Informatics. 2024;11(3).
• 14. Amorim AR, Ro¨ssner, S., Neovius, M., Lourenc¸o, P.M, Linne´, Y. Does Excess Pregnancy Weight Gain Constitute a Major Risk for Increasing Long-term BMI? Obesity. 2007;15:1278-1286.
• 15. Tetteh SG. Empirical Study of Agile Software Development Methodologies: A Comparative Analysis. Asian Journal of Research in Computer Science. 2024;17(5):30-42.
• 16. Garcia MB. ChatGPT as a Virtual Dietitian: Exploring Its Potential as a Tool for Improving Nutrition Knowledge. Applied System Innovation. 2023;6(5).
• 17. Siska N, Ahmad N, Abdillah MZ. Diagram Unified Modelling Language (UML) untuk Perancangan Sistem Informasi Manajemen Penelitian dan Pengabdian Masyarakat (SIMLITABMAS). Bridge : Jurnal publikasi Sistem Informasi dan Telekomunikasi. 2024;2(3):244-256.
• 18. Indonesia PAG. Tabel komposisi pangan Indonesia. Elex Media Komputindo; 2013.
• 19. Pavlidou E, Papadopoulou SK, Seroglou K, Giaginis C. Revised Harris-Benedict Equation: New Human Resting Metabolic Rate Equation. Metabolites. 2023;13(2).
• 20. Chatterjee A, Bajpai R, Gerdes MW. Analyze the Impact of Healthy Behavior on Weight Change with a Mathematical Model using the Harris-Benedict Equations. Research Square. 2021.
• 21. C Dhage P, A. Thakker R, K. Warhade K. Laravel Technology based Maternal e-Healthcare Systems with Improved Response Time and Stability. International Research Journal of Multidisciplinary Technovation. 2025:326-344.
• 22. C Dhage P, Sheth C, Warhade KK, Thakker RA. Analysis and Development of Framework and Modules for Mamata (Medical) Cyber Physical System using Lavarel and Cloud Computing. 2025;32(3):4123-.
• 23. Corso A, Moss, R.J., Koren, M., Lee, R., Kochenderfer, M.J. A Survey of Alogarithms for Black-Box Safety Validation of Cyber-Physical Systems. Journal of Artificial Intelligence Research. 2021;72:377-428.

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