Genetic Algorithm (GA) is a metaheuristic algorithm which has stages; coding, selection, crossover, and mutation. The crossover operator plays an important role in producing offspring to find solutions. Single Point Crossover (SPC) and Two Point Crossover (TPC) are classic crossover operators that are easy to apply to ordinal representation coding rather than path representation coding. The greedy algorithm is applied to the SPC operator to solve the Traveling Salesman Problem (TSP) to improve the performance of the genetic algorithm in the ordinal representation coding scheme. The results show that the proposed Greedy Single Point Crossover (GSPC) has higher performance in finding the global optimal solution for all population sizes and cities used, but it costs computation time.