The magnitude optimum (MO) method provides a relatively fast and nonoscillatory closed-loop tracking response for a large class of process models frequently encountered in the process and chemical industries. However, the deficiency of the method is poor disturbance rejection when controlling low-order processes. In this paper, the MO criterion is modified in order to optimize disturbance rejection performance, while the tracking performance has been improved by an integral set-point filtering PI controller structure. The new tuning rules, referred to as the disturbance rejection magnitude optimum (DRMO) method, were applied to several different two-degrees-of-freedom PI controllers. The DRMO method has also been tested on several different representatives of process models. The results of experiments have shown that the proposed tuning method with the integral set-point filtering PI controller is quite efficient in improving disturbance rejection performance, while retaining tracking performance comparable to the original MO method.