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All Journal Elkom: Jurnal Elektronika dan Komputer Teknik: Jurnal Ilmu Teknik dan Informatika Jurnal Publikasi Ilmu Komputer dan Multimedia
Adi Affandi Rotib
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Computer Science & IT Education

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Application of RED and PCQ Algorithms for Network Traffic Management in CBT Systems Prastika Indriyanti; Abdurohman; Rahman Hakim; Adi Affandi Rotib; Silviana Windasari
Elkom: Jurnal Elektronika dan Komputer Vol. 18 No. 1 (2025): Juli : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/tcjwkj28

Abstract

The digital transformation in education has encouraged the adoption of computer-based tests (CBT) using video content, which demands stable and efficient network performance. This study aims to evaluate the performance of two queue management algorithms, namely Random Early Detection (RED) and Per Connection Queue (PCQ), in maintaining the quality of service (QoS) of school networks during online video-based examinations. A case study approach was applied using a real network topology in a school environment, and QoS parameters such as throughput, delay, packet loss, and jitter were measured. The implementation was conducted using a MikroTik RB450Gx4 router configured with simple queue settings for each algorithm. The results show that PCQ provides more consistent performance under high user loads, achieving an average throughput of 56,482 bps and lower delay compared to RED. Conversely, RED performs better in scenarios with a small number of users. The study recommends using PCQ for networks with dynamic and dense user environments, while RED is more suitable for low-traffic conditions where latency stability is crucial. These findings offer practical guidance for managing bandwidth and improving the quality of CBT delivery in educational settings.
Single Tone Trigger Implementation for Seamless and Automated Broadcast to Ad Insertion Dama, Mardiyan; Windasari, Silviana; Adi Affandi Rotib; Frihadi, Ade; Abdurohman, Abdurohman
Teknik: Jurnal Ilmu Teknik dan Informatika Vol. 5 No. 1 (2025): Mei: Teknik: Jurnal Ilmu Teknik dan Informatika
Publisher : LPPM Sekolah Tinggi Ilmu Ekonomi - Studi Ekonomi Modern

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/teknik.v5i1.889

Abstract

Abstract. The advancement of broadcasting technology has driven the demand for reliable and efficient automation systems, particularly in managing the transition from broadcast content to advertisement segments. In this context, the present study proposes the application of the Single Tone Trigger (STT) method as an automatic triggering mechanism to systematically regulate content switching. This method utilizes a single-frequency audio signal embedded within the primary broadcast, which can be detected by the receiving system. The detection of this signal initiates an automatic content transition without requiring intervention from playout operators. A key advantage of this approach lies in its ease of integration with conventional broadcasting systems and its ability to reduce manual involvement that has traditionally been essential in broadcast content management. Through a series of tests, the system demonstrated high signal detection accuracy, low latency, and optimal operational reliability. These findings indicate that the Single Tone Trigger method can significantly enhance workflow efficiency within the broadcasting industry. Overall, this approach presents substantial potential for broad implementation as an automation solution that is not only stable and cost-effective, but also adaptive to the operational demands of modern broadcasting.   Keywords: Automatic Transition, Broadcast Automation, Single Tone Trigger (STT).
AI-Powered Intrusion Detection System Design for Government Data Center Infrastructure Security: Desain Sistem Deteksi Intrusi Berbasis Kecerdasan Buatan untuk Keamanan Infrastruktur Pusat Data Pemerintah Adi Affandi Rotib; Silviana Windasari; Abdurohman Abdurohman
Jurnal Publikasi Ilmu Komputer dan Multimedia Vol. 5 No. 1 (2026): Januari: Jurnal Publikasi Ilmu Komputer dan Multimedia
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupikom.v5i1.6745

Abstract

Government data centers serve as critical infrastructure for national digital sovereignty, yet they remain highly vulnerable to sophisticated cyber threats. Recent incidents, notably the 2024 LockBit 3.0 ransomware attack on Indonesia’s Temporary National Data Center (PDNS 2), have exposed the fundamental limitations of traditional signature-based security systems. This research proposes the design of an Artificial Intelligence (AI)-powered Intrusion Detection System (IDS) specifically tailored for government data center environments. Utilizing the Knowledge Discovery in Databases (KDD) framework, the system was evaluated against the CICIDS2017 and NSL-KDD benchmark datasets. To address the challenge of imbalanced network traffic, the study implemented the Synthetic Minority Oversampling Technique (SMOTE) combined with Edited Nearest Neighbors (ENN). Experimental results demonstrate that the Random Forest (RF) and XGBoost algorithms achieve superior performance, reaching an overall accuracy of 99.66%. While RF excels in recall for detecting Distributed Denial of Service (DDoS) and Brute Force attacks, Support Vector Machine (SVM) provides higher precision in minimizing false positives. Additionally, deep learning models such as LSTM show effectiveness in identifying complex temporal patterns like botnets. The integration of this AI-IDS into the National Data Center (PDN) architecture not only aligns with the Personal Data Protection Law (UU PDP) of 2022 but also fulfills the audit standards mandated by BSSN Regulation No. 8 of 2024. This study concludes that an autonomous, AI-driven defense mechanism is essential to ensuring proactive security and service continuity within the Indonesian government’s digital ecosystem
Co-Authors Abdurohman Abdurohman Abdurohman Abdurohman, Abdurohman Dama, Mardiyan Frihadi, Ade Indriyanti, Prastika Rahman Hakim Silviana Windasari