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Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls (AVITEC)
Published by Institut Teknologi Dirgantara Adisutjipto
ISSN : 26852381     EISSN : 27152626     DOI : 10.28989/avitec
Core Subject : Science, Engineering,
Aerospace Engineering Computer Science & IT Electrical & Electronics Engineering Engineering
This journal is the scientific publications journal published by Department of Electrical Engineering, Sekolah Tinggi Teknologi Adisutjipto. It aims to promote and disseminate the research finding in the development of management theories and practices. It will provide a platform for academicians, researchers, and practitioners to share their experience and solution to problems in different areas of journal scopes. Every submitted paper will be blind-reviewed by peer-reviewers. Reviewing process will consider novelty, objectivity, method, scientific impact, conclusion, and references.
Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro
Articles 10 Documents
 1 
Search results for , issue "Vol 8, No 1 (2026): February" : 10 Documents clear
THD Minimization in Seven-Level Packed U-Cell (PUC) Inverter using Particle Swarm Optimization Amran, Osamah Abdullah Yahya; Windarko, Novie Ayub; Syarif, Iwan
Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC) Vol 8, No 1 (2026): February
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/avitec.v8i1.3352

Abstract

This study presents the modeling and simulation of an asymmetric seven-level Packed U-Cell (PUC) multilevel inverter employing a reduced number of power switches. A Modified Pulse Width Modulation (MPWM) scheme, optimized through the Particle Swarm Optimization (PSO) algorithm, is implemented to determine the optimal switching angles for enhanced harmonic elimination. The primary objective is to improve the output voltage waveform quality while reducing Total Harmonic Distortion (THD) and enhancing switching efficiency. The novelty of this work lies in integrating PSO with MPWM control in an asymmetric seven-level PUC inverter configuration with fewer switches, a combination that has not been previously addressed. Simulation results in Simulink demonstrate that the proposed PSO-optimized MPWM strategy achieves a THD of 17.72%, outperforming conventional modulation techniques. These findings highlight the effectiveness of intelligent optimization methods for multilevel inverter control and their potential contribution to improving power quality in renewable energy applications.
Smart Airport Radar: Multimodal AI Classification of Aerial Threats with Communication Link Performance Evaluation Abdulkhaleq, Nadhir Ibrahim; Hussein, Ahmed Saad
Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC) Vol 8, No 1 (2026): February
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/avitec.v8i1.3295

Abstract

The proliferation of small unmanned aerial vehicles (UAVs) near airports poses increasing risks to airspace safety and infrastructure security. This paper presents Smart Airport Radar, a simulation-based framework for classifying aerial threats — including drones, decoys, and birds — using multimodal AI features. The system emulates dynamic swarming behaviors and extracts five key descriptors — mean speed, heading variability, jerk, thermal signature, and radar cross-section (RCS) — to train a multiclass Support Vector Machine (SVM) classifier. Comparative analysis with a traditional RCS-based rule method shows the SVM achieving a classification accuracy of 93.33%, far outperforming the baseline at 20.00%. Radar-style trajectory visualizations and class-specific precision, recall, and F1-scores confirm the model’s robustness and interpretability. Beyond sensing and classification, the framework incorporates a communication link performance evaluation, analyzing classification accuracy under varying Signal-to-Noise Ratio (SNR) levels. Results reveal that maintaining link quality above 15 dB SNR preserves near-optimal detection performance, bridging radar sensing with wireless communication reliability. With minimal computational overhead, high adaptability, and strong cross-domain relevance, the proposed system offers a robust, explainable, and deployable solution for real-time perimeter defense in modern airport security infrastructures.
AI-Powered Mobile Proctoring Frameworks using Machine Learning Algorithms in Higher Education: Post-Covid Trends, Challenges, and Ethical Implications Mogoi, Bartholomew Oganda; Kamau, John; Ongus, Raymond
Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC) Vol 8, No 1 (2026): February
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/avitec.v8i1.3600

Abstract

The rapid transition to online learning during and after the COVID-19 (Corona Virus Disease) pandemic has heightened the need for secure, scalable, and ethical online exam systems. AI-powered mobile proctoring frameworks have emerged as viable alternatives to traditional invigilation methods, enabling automated anomaly detection and behavior analysis through machine learning algorithms. This systematic review examines post-COVID trends, technological developments, challenges, and ethical implications of mobile AI proctoring in higher education. Following PRISMA 2020 guidelines, 180 studies were retrieved and screened, with 20 peer-reviewed articles meeting the inclusion criteria. Findings reveal that while AI-powered proctoring enhances scalability, integrity, and real-time monitoring, it raises significant concerns about privacy, algorithmic bias, accessibility, and technical reliability. The review identifies gaps in relation to technical and methodological issues, ethical and social concerns, and institutional and infrastructural readiness. This review illustrates a lapse in the existing literature, which focus on resource intensive proctoring frameworks without considering mobile compatibility and light-weight frameworks, discusses technical challenges, and recommends future research directions to balance technological effectiveness with ethical standards.
Ground Movement Tracking System for Airside Operations using Global Navigation Satellite System (GNSS) and Long Range (LoRa) Communication Wisnuardana, Cokorda Dwija; Wahyudi, Johan; Sulaiman, Muhammad Arif
Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC) Vol 8, No 1 (2026): February
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/avitec.v8i1.3544

Abstract

Accurate monitoring of ground vehicle and aircraft movement in the airport airside is essential to reduce the risk of incidents caused by limited coordination between controllers, pilots, and ground operators. This study proposes the design of a ground movement tracking system for airside operations, utilizing a Global Navigation Satellite System (GNSS) module (Matek M10Q-5883) and a Long Range (LoRa) communication module (LILYGO ESP32), integrated with a web dashboard for real-time visualization. The system was developed using the Waterfall methodology, covering requirement analysis, system design, hardware and software implementation, and performance testing in simulated airside conditions. Experimental results show that the system achieved an average coordinate deviation of only 0.000017º equivalent to about 1.7 meters  compared to a reference device, and maintained reliable data transmission up to 1.4 km under line-of-sight conditions. These findings demonstrate that the proposed system provides accurate and stable monitoring of ground movements, offering a cost-efficient and weather-independent alternative to GSM-based solutions. In addition, by optimizing LoRa parameters, the system successfully extended its communication range beyond the ~1 km typically reported in related studies, highlighting its novelty and contribution to enhanced safety in airport operations.
Performance Evaluation of Overcurrent Relay Coordination on 20-kV Busbar and Feeders Rizkianto, Ageng; Trihasto, Agung; Pravitasari, Deria; Setiawan, Hery Teguh
Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC) Vol 8, No 1 (2026): February
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/avitec.v8i1.3484

Abstract

The coordination of Overcurrent Relays (OCR) in power systems is crucial to ensure selectivity and reliability. Mis-coordination between OCRs on the 20-kV busbar and feeders can significantly reduce system performance, often due to improper determination of pick-up values and Time Multiplier Setting (TMS). Previous studies mostly focused on protection coordination for a single feeder and relied solely on simulation. This study evaluates OCR coordination on the 20-kV busbar and five feeders connected to the Unit I transformer at Secang Substation by combining manual analysis and Electrical Transient Analyzer Program (ETAP) simulations, validated against IEEE Std 242-2001. This integrated approach provides more reliable insights than earlier works limited to single-feeder coordination or software-only methods. Evaluation was conducted through short-circuit current analysis and Time Current Characteristic (TCC) curves, yielding pick-up and TMS values that produce Coordination Time Intervals (CTI) in compliance with IEEE Std 242-2001. Results indicate that the busbar OCR achieved a pick-up of 0.566 and a TMS of 0.236. For the feeders, SCG 10 achieved 0.27 and 0.173; SCG 03 yielded 0.5025 and 0.147; SCG 05 produced 0.441 and 0.153; SCG 07 yielded 0.35 and 0.165; and SCG 08 achieved 0.5535 and 0.137. Applying these settings produced CTI values exceeding the minimum requirement of 0.3 seconds. This evaluation demonstrates that coordinated OCR settings can improve reliability in 20-kV distribution systems and reduce the risk of widespread outages due to protection failures.
Hyperparameter Tuning of XGBoost for Flooding Attack Detection in SDN-based Vehicular Ad Hoc Networks (VANETs) under Limited Resources Putri, Chairunisa Rahma; Suranegara, Galura Muhammad; Ichsan, Ichwan Nul
Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC) Vol 8, No 1 (2026): February
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/avitec.v8i1.3510

Abstract

Software-Defined Network (SDN) based Vehicular Ad Hoc Network (VANET) infrastructure network enables centralized vehicle control. However, due to its centralized nature, SDN-based VANET is vulnerable to flooding attacks such as Distributed-Denial of Services (DDoS) or Denial of Service (DoS) attacks that can disrupt network availability and endanger traffic safety. This study aims to detect flooding attacks using the Extreme Gradient Boosting (XGBoost) algorithm with a focus on hyperparameter tuning in a limited computing environment to find optimal hyperparameter values for the model. This study uses basic Google Colab with 12 GB RAM with a total dataset of 431,371 entries. The results obtained from this study conclude that hyperparameter tuning achieves optimal performance at n_estimators = 150 and max_depth = 15, resulting in 99.97% accuracy, 99.99% precision, 99.97% recall, and 99.98% F1 score, which proves the effectiveness of the model in detecting flooding attacks. The novelty of this study lies in the application and evaluation of hyperparameter tuning on the XGBoost algorithm in a resource-constrained environment to improve attack detection in SDN-VANET.
CFM56-7B Electronic Engine Control System Performance During Ground Run-Up Test Widuri, Ani; Aritonang, Sovian; Amperiawan, Gita; Putranto, Andy Marjono; Akbar, Lalu Aan Sasaka; Risnawan, Novan
Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC) Vol 8, No 1 (2026): February
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/avitec.v8i1.3415

Abstract

The performance of the Electronic Engine Control (EEC) system is essential for ensuring safe aircraft operation following engine maintenance. This study evaluates the EEC performance of a CFM56-7B turbofan engine during an on-aircraft Engine Ground Run-Up (EGR) test conducted after engine replacement on a Boeing 737-800 Next Generation aircraft. The test was performed under controlled ground conditions in accordance with the Aircraft Maintenance Manual, and key EEC-controlled parameters—including fan speed (N1), compressor speed (N2), exhaust gas temperature (EGT), fuel flow, lubrication parameters, and engine vibration—were recorded using the aircraft’s built-in sensor system. The results indicate that all monitored parameters remained within manufacturer-specified acceptance limits during engine start, idle, Maximum Power Assurance, and static take-off power conditions, demonstrating stable EEC regulation under both transient and steady-state operation. Fuel consumption during the EGR procedure was consistent with the applied power settings, reflecting appropriate fuel scheduling. Comparison with representative test-cell–based studies show similar performance trends, with expected differences in thermal behavior attributable to on-wing installation effects during ground operation. Overall, the findings confirm that on-aircraft EGR testing provides an effective and operationally representative approach for post-maintenance validation of EEC performance, bridging the gap between test-cell evaluations and actual aircraft operation.
Smart Campus Framework for Higher Education Institutions in Tanzania Mongi, Alex Frank
Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC) Vol 8, No 1 (2026): February
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/avitec.v8i1.3407

Abstract

The deployment of smart campus has gained significance globally as Higher Education Institutions (HEIs) strive to  adopt digital technologies for efficient delivery of education and resource management. In achieveing proper deployment, scholars have proposed various features and frameworks for a smart campus of HEIs. However, HEIs around the globe have different needs and priority depending on their context. Establish a context based framework and features, this study examines smart campus features and their applicability in Tanzanian HEIs. It has adopted a trianglation of Systematic Literature Review (SLR) and Survey methods. Through SLR, the study identified 11 key features that various literature associate them with smart campus. Furthermore, though survey method, the study collected opinions from HEIs in Tanzania to test the findings of results that were obtained from SLR. Through ordinal logistic regression, we found that network infrastructure, smart governance, smart people, smart economy, smart living, and smart technology were more likely agreed as significant features of smart campus (p < 0.05), followed by smart education features with slightly large p-value (p = 0.057). Features like smart environment and smart buildings were perceived as not significant features of smart campus in most of HEIs (p > 0.05). Based on these findings, this study proposes a framework for smart campus that is relevant for HEIs in Tanzania.
Explainable Machine Learning Framework for Distributed Denial-of-Service (DDoS) Attack Detection using Comparative Evaluation and SHAP Analysis Riziq, Muhammad Fathur; Ichsan, Ichwan Nul
Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC) Vol 8, No 1 (2026): February
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/avitec.v8i1.3594

Abstract

The proliferation of Distributed Denial-of-Service (DDoS) attacks poses critical threats to network infrastructure, while conventional intrusion detection systems struggle to adapt to evolving attack patterns. Although ensemble learning methods achieve high accuracy on benchmark datasets, their opaque decision-making processes hinder deployment in Security Operations Centers (SOCs). To address this interpretability-performance gap, we propose an explainable machine learning framework integrating comparative benchmarking with quantitative interpretability analysis using the CIC-DDoS2019 dataset. Six supervised algorithms Decision Tree, Random Forest, XGBoost, LightGBM, Multilayer Perceptron, and Naïve Bayes were evaluated under standardized preprocessing protocols including random undersampling (50:50 class ratio), correlation-based feature selection (r > 0.9 threshold), and three-tier validation combining hold-out testing, train-validation splits, and 5-fold stratified cross-validation. LightGBM achieved optimal performance with 99.96% accuracy and F1-score of 0.9996, outperforming simple baselines by 0.35 percentage points while demonstrating superior computational efficiency. Beyond conventional performance metrics, we introduce the Feature Stability Score (FSS), a novel quantitative measure of SHAP-based feature importance consistency across validation folds. Spearman correlation analysis reveals a strong positive relationship between FSS and model robustness measured by cross-validation variance (ρ = 0.857, p = 0.014), establishing that stable feature attributions predict superior generalization. SHAP analysis identifies Flow Duration, Bwd Packet Length Mean, Fwd Packet Length Max, and Flow IAT Mean as dominant attack indicators. This integrated framework demonstrates that combining explainable AI with ensemble learning enables accurate, robust, and interpretable DDoS detection suitable for operational cybersecurity deployments.
Analysis of Policy Based Routing (PBR) and Failover in Dual-WAN Networks Alifi, Daryan Pratama; Ichsan, Ichwan Nul
Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC) Vol 8, No 1 (2026): February
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/avitec.v8i1.3605

Abstract

Reliance on stable and high-speed internet connectivity is crucial for modern business operations. A failure in a single internet link often leads to significant disruptions in productivity. This study designs and implements a Dual-WAN network architecture utilizing Policy-Based Routing (PBR) combined with an automated failover mechanism on a MikroTik router. Unlike prior studies that primarily employ the Per-Connection Classifier (PCC) Load Balancing method to maximize bandwidth aggregation, this research prioritizes session integrity to minimize disruptions in sensitive applications. To validate the proposed method, a comparative analysis was performed against the conventional PCC method. The results indicate that while PCC yields a higher theoretical aggregated throughput (468.5 Mbps), it suffers from a high session drop rate in secure connections. In contrast, the proposed PBR implementation demonstrates superior connection stability with a maximum throughput of 344.25 Mbps on the primary link, alongside a responsive failover mechanism achieving a recovery latency of under 1000 ms with minimal packet loss (1–2 packets). This study concludes that the PBR architecture provides a more reliable solution compared to standard load balancing for Small Office Home Office (SOHO) and SME environments requiring high availability.

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