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This Author published in this journals
All Journal The IJICS (International Journal of Informatics and Computer Science) Jurnal Ilmiah Universitas Satya Negara Indonesia
Sophia Widiana
STMIK Pelita Nusantara
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences

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ANALISIS ANCAMAN KEAMANAN JARINGAN SERTA IMPLEMENTASI FIREWALL, IDS, DAN IPS DALAM MENINGKATKAN PERLINDUNGAN SISTEM PADA LINGKUNGAN JARINGAN KOMPUTER Sophia Widiana; Sri Ayu Kartika; Reni Try Setianingsih; Reyna Aulia Zavira; Anita Sindar
Jurnal Ilmiah Universitas Satya Negara Indonesia Vol. 4 No. 2 (2026): Mei - October 2026
Publisher : Lembaga Penelitian, Publikasi, & Pengabdian kepada Masyarakat, Universitas Satya Negara Indonesia (LP3M-USNI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59408/jisni.v4i2.115

Abstract

The development of information technology has increased the use of computer networks in various sectors, including educational settings. However, this increased network usage has also been accompanied by an increase in cybersecurity threats that can disrupt service availability and data security. One frequently encountered threat is a Distributed Denial of Service (DDoS) attack, which can degrade network performance and disrupt academic activities. This study aims to analyze network security threats and the implementation of firewalls, Intrusion Detection Systems (IDS), and Intrusion Prevention Systems (IPS) to improve system protection in computer network environments. The method used is a literature review with a qualitative descriptive approach through an analysis of several studies discussing DDoS attacks in educational environments. The results indicate that DDoS attacks can degrade the quality of network services and hinder user access to academic systems. Furthermore, the implementation of firewalls, IDS, and IPS has been proven to improve network security through more effective filtering, detection, and prevention of attacks. Based on the analysis, implementing layered security that combines firewalls, IDS, and IPS can be an effective solution for improving system protection and maintaining the stability of computer network services.
Analysis of Digital Image Forensics Authentication in Image Forgery Cases Dameria E Br Jabat; Megaria Purba; Mhd. Avin Winata; Sophia Widiana
The IJICS (International Journal of Informatics and Computer Science) Vol. 9 No. 3 (2025): November
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/ijics.v9i3.9440

Abstract

This document introduces a combined framework for validating digital images in forensic contexts by merging Error Level Analysis (ELA) with Convolutional Neural Networks (CNN). The innovation of this research resides in the direct integration of a conventional explainable forensic method alongside a datadriven deep learning approach to ensure both clarity and enhanced detection efficacy. ELA serves to identify JPEG compression irregularities as forensic indicators, whereas CNN is employed to extract significant hierarchical features for robust image categorization. Trials were performed on the CASIA v2.0 dataset, which comprises 10,002 authentic and altered images. The suggested two-stream architecture concurrently processes original images and ELA-generated maps, facilitating synergistic feature acquisition. The hybrid model secures an accuracy rate of 74.32%, illustrating a 7.2% enhancement over isolated ELA. Furthermore, the framework diminishes the false positive rate from 50.2% to 34.8% while maintaining high sensitivity (0.84) in identifying altered regions. From a machine learning angle, this research illustrates how manually crafted forensic attributes can boost CNN capabilities when merged at the input stage. From an image processing viewpoint, it confirms ELA as a potent preprocessing strategy for directing deep feature extraction. The proposed framework provides an equilibrium between precision and forensic transparency, making it ideal for real-world digital forensic practices, including application in environments with limited resources.
Co-Authors Anita Sindar Dameria E Br Jabat Megaria Purba Mhd. Avin Winata Reni Try Setianingsih Reyna Aulia Zavira Sri Ayu Kartika