DiabeticFoodBot: Food and Water Intake Recommender System for Diabetics

Irwan Firmansyah, Z. K. A. Baizal, Ramanti Dharayani

2023

Abstract

Diabetes is a non-communicable disease which is one of the highest causes of death in the world. Diabetics need to arrange the schedule, amount and type of food and water consumed every day from a nutritionist to regulate blood sugar levels so that complications do not occur. A recommender system for food and water intake that has been validated by nutritionists is needed to assist diabetics in determining the nutrients con-sume. In this study we develop Artificial Intelligence (AI) telegram chatbot called as DiabeticFoodBot. This system can provide food recommendations and water intake for diabetics. There are many previous works that developed recommender systems for diabetics. However, this study has not considered the amount of water intake for diabetics. In addition, our research uses household size in presenting the results of recommendations to make it easier for users to determine serving sizes without using a scale. We develop our system using ontologies with Semantic Web Rule Language (SWRL) because they are considered capable of providing better performance. The DiabeticFoodBot validation result of 94.7 percent shows that our system can provide good recommendation results for users.

Paper Citation

in Harvard Style

Firmansyah I., K. A. Baizal Z. and Dharayani R. (2023). DiabeticFoodBot: Food and Water Intake Recommender System for Diabetics. In Proceedings of the 3rd International Conference on Advanced Information Scientific Development - Volume 1: ICAISD; ISBN 978-989-758-678-1, SciTePress, pages 314-320. DOI: 10.5220/0012639000003848

in Bibtex Style

@conference{icaisd23,
author={Irwan Firmansyah and Z. K. A. Baizal and Ramanti Dharayani},
title={DiabeticFoodBot: Food and Water Intake Recommender System for Diabetics},
booktitle={Proceedings of the 3rd International Conference on Advanced Information Scientific Development - Volume 1: ICAISD},
year={2023},
pages={314-320},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012639000003848},
isbn={978-989-758-678-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Advanced Information Scientific Development - Volume 1: ICAISD
TI - DiabeticFoodBot: Food and Water Intake Recommender System for Diabetics
SN - 978-989-758-678-1
AU - Firmansyah I.
AU - K. A. Baizal Z.
AU - Dharayani R.
PY - 2023
SP - 314
EP - 320
DO - 10.5220/0012639000003848
PB - SciTePress