AN OPTIMIZATION OF FAMILY NUTRITION NEEDS COMPLETION USING PARTICLE SWARM OPTIMIZATION

Abstract

Data consumption of Indonesian society when checked with balanced nutritional guidelines, tends
still below standard.This is confirmed by results Riset Kesehatan DasarRiskesdas(2013) who found
the data on fruit and vegetable that consumption by among people aged over 10 years who are still
under which it should be, namely 93.5%. On the protein also tend to be low, and many are derived
from vegetable protein, as well as the high levels of sugar, salt, fat from food and beverage
consumption in cities and villages. In fact, the food that combined with the better according to the
activity or physical condition of the body can be the big benefit to fulfill the energy needs, growth
and healthy. If not, then the activity would be disturbed. Thus, the required dose of the proper
foods to fulfill the nutritional needs of all family members, according to with factors such as age,
sex, weight, height, and activity will be a major concern. Appropriate dose with the complex
condition including how to minimize the price and still be able to fulfill the nutritional needs of the
many choices of food and alsostill consider the number of family members, it will be very difficult
if done traditionally, especially if made schedule for the preparation of the food menu to a few
days, it is certainly necessary support technology that can work automatically. In this research
proposes the use of algorithms particle swarm optimization (PSO) which has proven very quick to
give optimal results and automated recommendations, from a combination of food ingredients for
fulfilling a family nutritional needs, with the simple steps when compared to other optimization
algorithms. The test results proved that the system able to fulfill the nutritional needs of families
who still fulfill the threshold of tolerance at ± 1 0%, and can be save total price on capital expenses
amounted to 39.31%.