E3S Web Conf.
Volume 31, 2018The 2nd International Conference on Energy, Environmental and Information System (ICENIS 2017)
|Number of page(s)||10|
|Section||10. Industrial Information Systems|
|Published online||21 February 2018|
The Decision Support System (DSS) Application to Determination of Diabetes Mellitus Patient Menu Using a Genetic Algorithm Method
Master Program of Information System, School of Postgraduate Studies, Diponegoro University, Semarang - Indonesia
2 Department of Physics, Faculty of Science and Mathematics, Diponegoro University, Semarang – Indonesia
* Corresponding author: email@example.com
Composition of foods containing sugar in people with Diabetes Mellitus should be balanced, so an app is required for facilitate the public and nutritionists in determining the appropriate food menu with calorie requirement of diabetes patient. This research will be recommended to determination of food variation for using Genetic Algorithm. The data used is nutrient content of food obtained from Tabel Komposisi Pangan Indonesia (TKPI). The requirement of caloric value the patient can be used the PERKENI 2015 method. Then the data is processed to determine the best food menu consisting of energy (E), carbohydrate (K), fat (L) and protein (P) requirements. The system is comparised with variation of Genetic Algorithm parameters is the total of chromosomes, Probability of Crossover (Pc) and Probability of Mutation (Pm). Maximum value of the probability generation of crossover and probability of mutation will be the more variations of food that will come out. For example, patient with gender is women aged 61 years old, height 160 cm, weight 55 kg, will be resulted number of calories: (E=1621.4, K=243.21, P=60.80, L=45.04), with the gene=4, chromosomes=3, generation=3, Pc=0.2, and Pm=0.2. The result obtained is the three varians: E=1607.25, K=198.877, P=95.385, L=47.508), (E=1633.25, K=196.677, P=85.885, L=55.758), (E=1630.90, K=177.455, P=85.245, L=64.335).
© The Authors, published by EDP Sciences, 2018
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