Optimasi Biaya Bahan Menu Makanan bagi Penderita Penyakit Jantung dengan Menggunakan Metode Evolution Strategies - Veronica Kristina Br Simamora; Imam Cholissodin; Mochammad Ali Fauzi (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2017)
People who suffered heart disease should get serious handling. Not only taking medicines regularly, maintaining diet and nutritional intake for the body is also important. The price of the food ingridients which tend to be unstable makes it difficult for patients to consume foods in meeting their nutritional needs. This research used evolution strategies algorithm to optimize the cost of food ingidients for people with heart disease. Evolution strategies algorithm consists stages of initialization population with the real-vectors chromosome representation, reproduction method using intermediate recombination, and mutation, evaluation, and selection with method called elitism. The parameters were tested by the number of population testing, number of offspring testing, number of recombination testing, and generation testing. The greater the number of populations, number of offsprings, and generations does not guarantee produce more optimal results. The greater the number of population, the number of offspring, and many generations will bring up the various chromosomes, so the chances of this algorithm produce more optimal results will be even greater. This result can happen because the basic concepts of evolution strategies algorithms that use random values in the calculation process. Number of recombination testing indicates that the fewer parent's chromosomes involved in recombination will result a varied number of offspring's chromosomes. The more varied the result of offspring's chromosomes then the chances to achieve optimal results are greater. From the parameter tests results, this research obtained that the system can meet the nutritional needs of patients using the initial 105 population, 430 offspring produced, involving 2 parents on recombination, and 400 generations. Comparison of recommended food system recommendations with expert recommendations shows that the system has provided more optimal results compared to expert recommendations. This proved that the system delivers recommendations with cheaper prices and foods that varies.