Article Per Year (5 Year)
p-Index From 2019 - 2024
3.247
P-Index
This Author published in this journals
All Journal Perfecting a Video Game with Game Metrics Jurnal Teknologi Informasi dan Komputer The IJICS (International Journal of Informatics and Computer Science) EDUKATIF : JURNAL ILMU PENDIDIKAN JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) JIIP (Jurnal Ilmiah Ilmu Pendidikan) Jurnal PkM MIFTEK Jurnal Pengabdian Masyarakat Bidang Sains dan Teknologi Jurnal Karya Abdi Masyarakat
Sudiatmika, Ida Bagus Kresna
STMIK Primakara
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Transportation Veterinary Other

Published : 18 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Perfecting a Video Game with Game Metrics

 1 
Image forgery detection using error level analysis and deep learning Ida Bagus Kresna Sudiatmika; Fathur Rahman; Trisno Trisno; Suyoto Suyoto
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 2: April 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i2.8976

Abstract

Many images are spread in the virtual world of social media. With the many editing software that allows so there is no doubt that many forgery images. By forensic the image using Error Level Analysis to find out the compression ratio between the original image and the fake image, because the original image compression and fake images are different. In addition to knowing whether the image is genuine or fake can analyze the metadata of the image, but the possibility of metadata can be changed. In this case the authors apply Deep Learning to recognize images of manipulations through the dataset of a fake image and original images via Error Level Analysis on each image and supporting parameters for error rate analysis. The result of our experiment is that we get the best accuracy of training 92.2% and 88.46% validation by going through 100 epoch.
Co-Authors Astawa, Ni Luh Putu Ning Septyarini Putri Dharma, Eddy Muntina Eka Grana Aristyana Dewi Fathur Rahman Gede Deva Rananda Putra I Gede Juliana Eka Putra I Gede Putu Krisna Juliharta I Gusti Arya Mahasastrawan I Gusti Ayu Agung Sari Dewi I Gusti Ayu Agung Sari Dewi I Nyoman Wiyana I Nyoman Yudi Anggara Wijaya I Nyoman Yudi Anggara Wijaya I Putu Suwindratama Ida Bagus Dwi Putra Purnawa Ida Bagus Gede Arga Kusuma Ketut Queena Fredlina Komang Tri Werthi Kyrana Deanora Debra Ni Kadek Nirmalasari Nyoman Purnama, Nyoman Nyoman Renata Putri Anugrah Cahya Dewi Putu Surya Kusuma Suyoto Suyoto Trisno Trisno Wedhaputri, Made Vidya Sasmitha