Forensic Metadata Analysis in Detecting Digital Image Manipulation - Mario Anugraha; Ryan Putranda Kristianto; Andre Hartanto (Universitas Kristen Immanuel, 2025)
The development of the digital era has brought significant changes to various aspects of life, including the field of photography. Digital photos offer both advantages and disadvantages, one of which is the ease with which they can be modified using image editing software. This makes it increasingly difficult to distinguish between original and manipulated images. Edited photos can spread widely through social media, causing public concern and doubts about the authenticity of information. Individuals often manipulate images for personal gain or interests. The easy access to image editing software further facilitates this manipulation process. In the field of research, digital image forensics has emerged as a scientific method to verify the authenticity of images through accountable evidence. This study aims to detect forgery in digital photos using that approach. The method employed in this research is metadata analysis with the assistance of an offline tool called JPEGsnoop and online tool Forensically Beta. The results show differences in metadata between the original and manipulated images, indicating that modifications have been made to the image.