<![CDATA[Obesity occurs due to buildup of fat in the body is very high. Thus causing weight gain be not ideal. Obesity can also cause disease complications, some of which can endanger lives. To get the ideal body weight and the minimum cost incurred, the patient needs to control the amount of food intake is by regulating the composition of food that enters the body. The research was done by optimizing food composition for obese people in adults using Particle Swarm Optimization Algorithm (PSO). In this study, the initial particle formation of the particle random based on the amount of food so there is no need to convert that into food index. The results displayed by the program is actual body weight, ideal weight, nutritional status, energy needs, the needs of protein, fat and carbohydrate needs needs. While the test results obtained the optimal parameters such as the number of particles = 80, the number of iterations based on testing convergence of 703, = 0,4, = 0,7 c1i = 1,5 and c1f = 0,3, c2i = 0,3 and c2f = 1,5. The results of the program with the first patient parameters produce an average difference between the actual data with the data from the program registration -2,08% and it can reduce the cost of expenditure up to 6,85%. While the second patient the average of the actual data difference with data from the program amounted to -1,06% and it can reduce the cost of expenditure up to 5,93%.]]>
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