The Covid-19 pandemic is the most difficult time faced by the community and health workers, prevention of the virus is also increasingly being done to reduce the rate of infection. It is very important to increase the body's resistance or immunity. Therefore, in this study, the problem to be solved is regarding the optimization of nutrition for foodstuffs and herbal packages of Indian wood for adolescents for the prevention of COVID-19 and its new variants in an effort to increase immunity and performance using genetic algorithms. Genetic algorithm is a heuristic search algorithm that uses the mechanism of biological evolution. Some resistance that can be traversed by genetic algorithms is that information will be combined randomly. The following will also be matched Back regarding individuals with previous iterations. Then it will produce a minimum and maximum function to determine the price and get the fitness value as a price reference. The most optimal parameter values are obtained in the generation of 800, using a crossover reproduction of two cut points of 0.5, scrambler mutation value of 0.9, and a population of 125 by obtaining optimal parameter values, then the patient can get the best food ingredients. From the parameter values that have been obtained, the food package is optimally tested with the average nutritional requirement for patient G of 3.53%, patient K of 1.43%, patient E of 3.85%, and patient N of 4.15%, with each price obtained is Rp. 67,945, Rp. 76,397, Rp. 58,853, Rp. 58,195, in the order according to the patient.
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