Optimasi Komposisi Makanan Bagi Penderita Hipertensi Menggunakan Metode Particle Swarm Optimization - Ayulianita A. Boestari; Dian Eka Ratnawati; Titis Sari Kusuma (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2017)
Indonesia ranks 2nd largest in Southeast Asia in the number of deaths caused by Hypertension. One way to treatment Hypertension disease is to control weight and reduce the amount of salt consumed. To solve the problem used Particle Swarm Optimization (PSO) method. Stages in the PSO algorithm are building the initial population, building initial velocity, fitness calculations, pbest and gbest determinations, velocity and position update. The representation of the particles used is the food index. The number of dimensions used is 14. The number of dimensions indicates the number of features consisting of breakfast, complementary food, lunch, complementary meals and dinner. Each features consisting of staple foods, sources of plant protein, sources of animal protein, vegetable and appendages. PSO parameters used in the test are: the number of iterations used is 130, the number of particles used is 100 and the value of wmin and wmax used are 0,4 and 0,5. Based on trials of 4 cases of patients, it can be stated that the system can produce food recommendations That can fulfill the nutritional adequacy of Â± 10% within the specified tolerance limits