Smart Malnutrition Detection: Deteksi Dini Kecukupan Gizi Dan Rekomendasi Gizi Harian

Syariful Alim, Arif Arizal


This study aims to develop a mobile-based application, Smart Malnutrition Detection, which can help early detection independently of the nutritional status of each individual and provide recommendations for daily nutritional intake. The system was developed by adopting a prototyping system development model. The system can determine the nutritional status of individuals based on the threshold value of BMI. The system can also calculate individual daily calorie needs based on BMI, EMB and daily physical activity values. The final output of this system is in the form of recommendations for daily nutritional intake in grams. The functional testing results show that all features contained in the Smart Malnutrition Detection application can run well and no errors are found. Validity testing results show that the output of the system is in accordance with the rules set by the Ministry of Health of the Republic of Indonesia. Starting from calculating the BMI value, the value of daily calorie needs to the size of the menu consumption in grams. So that it can be concluded that this application is very useful to support early detection of individual malnutrition conditions. The system is also able to provide recommendations for daily nutritional intake so that it can help improve diet and healthy lifestyle.

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Copyright: JPIT (Jurnal Informatika: Jurnal Pengembangan IT) p-ISSN: 2477-5126 (print), e-ISSN 2548-9356 (online) 

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Creative Commons License
JPIT (Jurnal Informatika: Jurnal Pengembangan IT) is licensed under a Creative Commons Attribution 4.0 International License.