Image forgery detection is challenging to solve, especially in blind image forgery detection. Copy-move forgery is a common and popular method in image forgery. Copy-move forgery become more challenging to detect with addition of post-processing operation in the image. In this paper, the proposed methodology is copy-move detection with Stationary Wavelet Transform (SWT), Discrete Cosine Transform (DCT), and Four-Square Mean Features. SWT is used because it enables to handle various kind of post-processing operation. Likewise, DCT has many advantages such as the lower dimension and robust to various attacks. The proposed methodology is evaluated using CoMoFoD dataset and the performance are measured using precision, recall, and F1-scores. The result reveal that the methodology is successful in detecting duplicated region and robust against brightness change, contrast adjustment, image blurring, and color reduction.