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Anggi Mahadika Purnomo
Faculty of Computer Science, Universitas Brawijaya
Computer Science & IT Electrical & Electronics Engineering

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Algoritma Genetika untuk Optimasi Komposisi Makanan Bagi Penderita Hipertensi Anggi Mahadika Purnomo; Davia Werdiastu; Talitha Raissa; Restu Widodo; Vivi Nur Wijayaningrum
Jurnal Teknologi dan Sistem Komputer Volume 7, Issue 1, Year 2019 (January 2019)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (219.705 KB) | DOI: 10.14710/jtsiskom.7.1.2019.1-6

Abstract

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.
Co-Authors Davia Werdiastu Restu Widodo Talitha Raissa Vivi Nur Wijayaningrum