<![CDATA[Research on image processing methods has become increasingly diverse in modifying images with more attractive visuals. The results of visual modification of this image are often used to convey certain information that will often be found in various media. The method used to identify images that have been modified is the Error Level Analysis (ELA) method, which detects the quality level of a visual image compared to other images. So the method approach proposed in this research involves computing the visual components of images with shape, color and texture features. The method used in shape computing is Prewitt edge detection, while for color features using HSV color transformation and Grayscalling. The method used to identify texture is using the Gray Level Co-occurrence Matrix (GLCM). The urgency of the method proposed in this research is very important to keep up with the various image processing methods that are developing increasingly rapidly. The results of the research are the Error Level Analysis (ELA) method with an analysis approach to shape components using the edge detection method, analysis of color components using the HSV and Grayscalling color transformation methods, and analysis of texture components using the Gray-Level Co-Occurrence Matrix (GLCM) method. ) can be used to detect image authenticity based on the statistical output of processing data. The Error Level Analysis (ELA) method with identification of shape, color and texture shows the differences between the original image and the manipulated image, so that the method used in the research can be a recommendation in completing the system. It is hoped that the approach method in this research will become an instrument for identifying images that have been modified to avoid misuse of visual image information.]]>
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