Optimization of Corn Crop Nitrogen Percentage Using Genetic Algorithm - Aidil Adrianda A; Septian, Belen; M. Fauzan Ridho (AI Society & STMIK Indonesia, 2025)
Corn is one of the strategic commodities in food fulfillment in Indonesia. Despite being one of the strategic commodities for food security, corn production is still far from meeting total consumption. One of the main factors for increasing yield is the availability of nutrients, especially nitrogen. This research aims to determine the optimal nitrogen percentage to maximise corn production using genetic algorithm. Simulations were conducted using the genetic algorithm method with parameters such as population size, maximum number of generations, mutation rate, as well as Bayesian approach for the crossover method and a Gaussian distribution for mutation. The results showed that the more generations used, the better the accuracy of the curve approach to the actual data, with an optimal nitrogen value of 1.506% in the 500th generation and a production yield of 227,718 bu/ac or 15.325 ton/ha.