cover
Contact Name
Freddy Kurniawan
Contact Email
freddykurniawan@itda.ac.id
Phone
+62274451263
Journal Mail Official
avitec@itda.ac.id
Editorial Address
Department of Electrical Engineering Institut Teknologi Dirgantara Adisutjipto, Jl. Janti, Blok R, Lanud Adisutjipto, Yogyakarta
Location
Kab. bantul,
Daerah istimewa yogyakarta
INDONESIA
Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls (AVITEC)
ISSN : 26852381     EISSN : 27152626     DOI : 10.28989/avitec
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.
Articles 142 Documents
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.