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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
I Gusti Ayu Putri Diani
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Optimasi Komposisi Bahan Makanan bagi Pasien Rawat Jalan Penyakit Jantung dengan Menggunakan Algoritme Particle Swarm Optimization (PSO) I Gusti Ayu Putri Diani; Imam Cholissodin; Suprapto Suprapto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 11 (2017): November 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Heart is an organ which is very important in the body that pumps blood. Many people can suffered heart disease caused by unhealthy lifestyle. Most of the deaths, according to the report of the World Health Organization (WHO), caused by cardiovascular disease that cause 17.7 million or approximately 45%. For people who suffers with heart disease, take care of food consumption is important in order to be healthy again. This research will be conducted on the giving food ingredients for the patients who suffers cardiovascular disease whose can continue their treatment in their home.Research conducted is optimizing the composition of the food ingredients for cardiovascular disease outpatient by using particle swarm optimization algorithm which the results will be displayed in the program is data such as age, weight, height, along with recommended of food ingredients and minimum price of each food ingredients.This algorithm consists stages of initialize particles, calculating fitness value, define pbest and gbest value, calculating velocity and position of particles. The results from this research, it is found that the optimal parameters are the number of particles are 40 particles, the value of ωmax is 0,75, the value of ωmin is 0,25, the value of C1 is 2, the value of C2 is 2 and the number of maximum iterations are 80 iterations. The results of the program using these parameters resulted in an average difference from actual patients data and the results from the program of 4,67%. Moreover, the result of this research can reduce expenses up to 14,68%.
Co-Authors Imam Cholissodin Supraptoa Supraptoa