Optimasi Komposisi Makanan untuk Penderita Hipertensi Menggunakan Variable Neighborhood Search - Aprilia Nur Fauziyah; Wayan Firdaus Mahmudy (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2017)
Hypertension is a major symptom that cause other diseases appear such as noncommunicable diseases, cancer, and diabetes. One of healthy life effort in the patients with hypertension is a healthy food that attentions level of salt in foods. The food composition with attentions level of salt and cost of the food can use Variable Neighborhood Search (VNS) algorithm. The data which are used for this study are 103 data food that consists of staple foods, vegetables, vegetable sources, animal sources and fruits. VNS have 3 stages after generate initial solution, there are shaking, local search and move or not. The results of Kmax and local search's testing show that the average of highest fitness is 0.516848 with Kmax = 13 and the highest average fitness is 0.524301 with 2000 iterations. Kmax and local search iterations that too much not guarantee a solution with great fitness is obtained but many Kmax numbers or local search iterations can give wider search opportunities. The result of this study contains composition of foods with nutrients which are close to the needs of hypertension patients with attentions the natrium and minimal cost within a day.