Sistem Rekomendasi Bahan Makanan Bagi Penderita Penyakit Jantung Menggunakan Algoritma Genetika - Elisa Julie Irianti Siahaan; Imam Cholissodin; Mochammad Ali Fauzi (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2017)
Lack of public awareness in regulating the consumption of food based on nutrition can cause several diseases including heart disease. Heart disease is caused from blockage of cholesterol and fat in the coronary artery. It is very important for people with heart disease to regulate food intake in order to reduce the blockage. Managing the food for the heart diet is difficult because heart diet is different from the other diets, because the amount of protein and fat is reduced. Genetic algorithms can solve the problem of managing food by computation process. The data that are used in this research are diet food ingredients data that consist of 8 kinds of food ingredients, carbohydrate, animal protein, vegetable protein, vegetable, fruit, milk, sugar and oil. In converting food into chromosome, chromosome real code representation is used. The crossover method that is used is extended intermediate crossover, the mutation method that is used is random mutation and the selection method is elitism selection. From the results of the testing, the optimal parameter scores of the genetic algorithm are the population number of 280 with the average fitness score of 103.7, Cr and Mr scores are 0.5 and 0.5 with the average fitness score of 103.3 and for the generations score is 100 with average fitness score of 111.2. Output of the system is food ingredients recommendation with 5 times a day meal time, which consists of breakfast, snack, lunch, snack and dinner with number of days based on user choice.