Open AccessWeb based food combination system for diabetes mellitus type 2 with genetic algorithm
Author(s) -
Kevin Kuwito,
Desi Arisandi,
Novario Jaya Perdana
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1007/1/012121
Subject(s) - genetic algorithm , computer science , disease , diabetes mellitus , medicine , algorithm , machine learning , endocrinology
As the age of a person makes it easily infected with a disease such as diabetes. In this case, the food of people suffering from the disease must eat foods that are in accordance with the nutrients needed to reduce the patient’s blood sugar levels. Based on this problem, this study aims to develop a food combination system to help diabetics manage food according to patient criteria. This system requires criteria for producing food combinations and using genetic algorithm methods to produce the best alternative food combinations for diabetics. The combination of food resulted is taken based on the efficiency of chromosomes from genetic algorithms. The genetic algorithm accuracy calculation method reaches 100% by comparison with manual calculations from 5 test cases that have been made. From these results it can be concluded that the application of genetic algorithm methods is sufficient to assist diabetics in making food combinations that fit the patient’s criteria.