Quadrotor control is needed so that the quadrotor can float close to the stationary state. For that we need control techniques. One control technique that can be designed and implemented in quadrotor is PID control. PID parameter tuning using the Genetic Algorithm technique can speed up the manual tuning process. The weakness in the application of the Genetic Algorithm rule is that it often rejects important information found in other individuals and causes premature convergence, especially at the beginning of the generation. These problems can be overcome by using crossover and mutation rules with different probability levels according to fitness values and evolutionary processes. The results of the study using fast genetic algorithm techniques obtained constants Kp, Ki and Kd with the lowest rise time and overshoot, namely 0.010, 0.001 and 0.036 at the pitch angle. At the roll angle, they are 0.010, 0.001 and 0.03. At yaw angle 0.018, 0.006 and 0.043. Comparison of PID tuning simulations using fast genetic algorithm with genetic algorithm standards, shows that fast genetic algorithm has increased optimum generation achievement faster by 26.67% at pitch angle, 44% at roll angle and 20% at yaw angle. This condition has an effect on increasing simulation execution time, where fast genetic algorithm is 26.4% faster at pitch angle, 38.05% at roll angle, and 24.19% at yaw angle.