One of the algorithm for aerial image stitching system is SURF (Speeded Up Robust Features). It is a robust algorithm which is invariant to image scale, rotation, blurring, illumination, and affine transformation. Although SURF has good performance, some of the detected keypoints are not always considered as necessary keypoints . As a result, these unnecessary keypoints are needed to be eliminated to decrease computation time.The proposed system uses SURF detector in the detection process. The data reduction method will eliminate couple of keypoints which have near distance each other. Next, the keypoints will be described by SURF descriptor.The description Results further matched using FLANN. The next step is the search pattern with RANSAC homography matrix and stitch the picture to accumulate keypoints using warpPerpective.Stitching system are tested with some variations, such as scale variations, rotation variations, and overlap variations on the image. Based on the result, the proposed Data Reduction method has optimum value of minimal radius from 40 pixels to 100 pixels. The stitching process is still working with up to 90% keypoint number reduction. Average computation time using data reduction method are 39,41% faster than without data reduction method.