Algoritma Genetika untuk Optimasi Komposisi Makanan Bagi Penderita Hipertensi

Genetic Algorithm for Optimizing Food Composition for Hypertension Patients

Anggi Mahadika Purnomo  -  Faculty of Computer Science, Universitas Brawijaya, Indonesia
Davia Werdiastu  -  Faculty of Computer Science, Universitas Brawijaya, Indonesia
Talitha Raissa  -  Faculty of Computer Science, Universitas Brawijaya, Indonesia
Restu Widodo  -  Faculty of Computer Science, Universitas Brawijaya, Indonesia
*Vivi Nur Wijayaningrum orcid scopus  -  Faculty of Computer Science, Universitas Brawijaya, Indonesia
Received: 27 Oct 2018; Revised: 13 Jan 2019; Accepted: 30 Jan 2019; Published: 31 Jan 2019; Available online: 31 Mar 2019.
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Citation Format:
Hypertension can be prevented and handled by eating nutritious foods with the right composition. The genetic algorithm can be used to optimize the food composition for people with hypertension. Data used include sex, age, weight, height, activity type, stress level, and patient hypertension level. This study uses a reproduction method that is good enough to be applied to integer chromosome representations so that the search results provided are not local optimum solutions. The testing results show that the best genetic algorithm parameters are as follows population size is 15 with average fitness 20.97, the generation number is 40 with average fitness 50.10, and combination crossover rate and mutation rate are 0.3 and 0.7 with average fitness 41.67. The solution obtained is the optimal food composition for people with hypertension.
Keywords: genetic algorithm; hypertension; food composition; stroke; high blood pressure
Funding: Faculty of Computer Science, Universitas Brawijaya

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