Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI)
Freddi Moriston Alfa Doli
Indraprasta Pgri University

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Implementasi Steganografi dengan Metode Least Significant Bit (LSB) Untuk Penyisipan Dalam Data Gaji pada PT Nusa Network Pratama Freddi Moriston Alfa Doli; Lukman Lukman; Meri Chrismes Aruan
Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Vol. 7 No. 02 (2026): Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI)
Publisher : Program Studi Teknik Informatika, FTIK, Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/jrami.v7i02.1247

Abstract

This research was conducted with the aim of enhancing information security for employee salary data at PT Nusa Network Pratama through the application of steganography methods. Given the importance of salary confidentiality as part of the company’s sensitive information, a system is needed that can hide this data without being detected visually or digitally by unauthorised parties. The method used in this study is Least Significant Bit (LSB)-based steganography, a data-embedding technique that replaces the least significant bit of each pixel in a digital image. This approach was chosen for its ability to embed data without significantly affecting the visual quality of the image. The implementation process involved testing data embedding and extraction to ensure that salary data could be hidden and retrieved with high accuracy. The results of the study indicate that the LSB method can be effectively used to embed salary data into images without compromising the visual appearance of the image. The embedded data can be extracted with a 100% success rate, without any damage to the original data or the image file. Thus, the implementation of LSB steganography has proven to be feasible and secure as an alternative for distributing salary data internally within a corporate environment.
Co-Authors Lukman Lukman Meri Chrismes Aruan