Penerapan Genetic Algorithm pada Optimasi Bahan Makanan Pendamping Air Susu Ibu (MPASI) Guna Memenuhi Gizi Bayi

Abstract

The nutritional status of infants refers to the condition of their bodies resulting from food consumption and nutrient utilization. Inadequate nutrition during the toddler stage can lead to health complications in babies. Achieving optimal nutrition in Complementary Food for Mother's Milk (MPASI) involves consuming diverse foods that provide comprehensive nutrition, including carbohydrates, proteins, fats, and vitamins. To obtain varied and nutritionally complete food ingredients, algorithmic methods are employed for food optimization. The genetic algorithm treats food ingredients as chromosomes, subjected to selection, crossover, mutation, and fitness evaluation processes. Tests were conducted using genetic algorithms to determine optimal values for the population, generation, crossover rate (Cr), and mutation rate (Mr). Based on the test results, the optimal values were 140 for the population, 4500 for the generation, 1.4 for Mr, and 1 for Cr. Utilizing these optimal parameters, food ingredients aligned with calorie requirements and provided comprehensive nutrition. The differences between the results and the target calorie intake were evaluated to assess optimality. Smaller discrepancy values indicate higher levels of optimization. Calculating the difference between the actual (target) nutritional needs and the total given by the system from the calculation results of the genetic algorithm obtained 99.1% of the effects of total accuracy.