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Journal : Indo-Fintech Intellectuals: Journal of Economics and Business

Mendeteksi Orisinalitas Citra Menggunakan Teknik Error Level Analysis dan Metadata Abrori, Rian; Fitria, Maulidah; Bullah, Habi
Indo-Fintech Intellectuals: Journal of Economics and Business Vol. 4 No. 2 (2024): Indo-Fintech Intellectuals: Journal of Economics and Business
Publisher : Lembaga Intelektual Muda (LIM) Maluku

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54373/ifijeb.v4i2.1169

Abstract

The current development of digital image technology is often misused by certain parties to carry out fraudulent acts that can harm other people, for example what is often encountered in society is proof of bank transfers that have been manipulated. This study aims to detect image originality in an image using the Error Level Analysis (ELA) and Metadata techniques in Forensicallybeta web-based applications. Research model by completing two image files consisting of original images and manipulated images. The results showed that Forensicallybeta with the Error Level Analysis (ELA) and Metadata techniques were able to detect the authenticity of an image, so it was appropriate to determine whether the image file was original or manipulated
Mendeteksi Orisinalitas Citra Menggunakan Teknik Error Level Analysis dan Metadata Rian Abrori; Maulidah Fitria; Habi Bullah
Indo-Fintech Intellectuals: Journal of Economics and Business Vol. 4 No. 2 (2024): Indo-Fintech Intellectuals: Journal of Economics and Business
Publisher : Lembaga Intelektual Muda (LIM) Maluku

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54373/ifijeb.v4i2.1169

Abstract

The current development of digital image technology is often misused by certain parties to carry out fraudulent acts that can harm other people, for example what is often encountered in society is proof of bank transfers that have been manipulated. This study aims to detect image originality in an image using the Error Level Analysis (ELA) and Metadata techniques in Forensicallybeta web-based applications. Research model by completing two image files consisting of original images and manipulated images. The results showed that Forensicallybeta with the Error Level Analysis (ELA) and Metadata techniques were able to detect the authenticity of an image, so it was appropriate to determine whether the image file was original or manipulated