| dc.contributor.advisor | Zamzami, Elviawaty Muisa | |
| dc.contributor.advisor | Suyanto | |
| dc.contributor.author | Napitupulu, Fajrul Malik Aminullah | |
| dc.date.accessioned | 2024-08-27T07:08:36Z | |
| dc.date.available | 2024-08-27T07:08:36Z | |
| dc.date.issued | 2024 | |
| dc.identifier.uri | https://repositori.usu.ac.id/handle/123456789/96161 | |
| dc.description.abstract | Steganalysis is a technique used to detect hidden messages in steganographic
images. It involves detecting the existence of hidden messages in digital media.
Recent steganography techniques have gained attention due to their security. This
research presents a universal steganalysis method for blocking recent techniques
in the spatial domain. The method analyzes using CC-PEV and SPAM feature
extractor for classifying whether the suspicious image is stego or normal. SPAM
feature extractor successfully detects all stego images with an accuracy of 75,28%
while the CC-PEV feature is slightly left behind with an accuracy of 66,95% both
using a linear kernel | en_US |
| dc.language.iso | id | en_US |
| dc.publisher | Universitas Sumatera Utara | en_US |
| dc.subject | Steganography | en_US |
| dc.subject | Steganalysis | en_US |
| dc.subject | CC-PEV | en_US |
| dc.subject | SPAM | en_US |
| dc.subject | SDGs | en_US |
| dc.title | Analisis Perbandingan Ekstraksi Fitur CC-PEV dan Subtractive Pixel Adjacency Matrix dalam Steganalisis Berbasis Machine Learning | en_US |
| dc.title.alternative | Comparative Analysis of CC-PEV and Subtractive Pixel Adjacency Matrix Feature Extraction in Machine Learning Based Steganalysis | en_US |
| dc.type | Thesis | en_US |
| dc.identifier.nim | NIM207038010 | |
| dc.identifier.nidn | NIDN0016077001 | |
| dc.identifier.nidn | NIDN0013085903 | |
| dc.identifier.kodeprodi | KODEPRODI55101#Teknik Informatika | |
| dc.description.pages | 67 Pages | en_US |
| dc.description.type | Tesis Magister | en_US |
