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ITEj (Information Technology Engineering Journals)
Published by Universitas Islam Negeri Siber Syekh Nurjati Cirebon
ISSN : 25482130     EISSN : 25482157     DOI : https://doi.org/10.24235/itej.v5i2
Core Subject : Science, Education, Engineering,
Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Mathematics
ITEj (Information Technology Engineering Journals) is an international standard, open access, and peer-reviewed journal to discuss new findings in software engineering and information technology. The journal publishes original research articles and case studies focused on e-learning and information technology. All papers are peer-reviewed by reviewers. The scope of the system discussed is attached but not limited; Systems and software engineering Artificial Intelligence Technology (AI) and Machine Learning Internet of Thing and Big Data Smart Education systems and components Computer Vision Information Technology etc
Arjuna Subject : -
Articles 122 Documents
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Implementation of Ethereum-Based Blockchain Technology for ADS-B Data Security and Validation Rabbaniansyah, Kgs Muhammad Farhan; Lindawati, Lindawati; Soim, Sopian
ITEJ (Information Technology Engineering Journals) Vol 11 No 1 (2026): In Progress
Publisher : Pusat Teknologi Informasi dan Pangkalan Data IAIN Syekh Nurjati Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24235/itej.v11i1.271

Abstract

Automatic Dependent Surveillance–Broadcast (ADS-B) has significantly enhanced air traffic monitoring by enabling real-time broadcasting of aircraft positions and identifiers. However, its lack of cryptographic safeguards makes it inherently vulnerable to spoofing, replay, and tampering attacks. This study presents a blockchain-based ADS-B validation framework that leverages Ethereum smart contracts and MetaMask for secure, decentralized data authentication. The proposed system validates incoming flight messages by enforcing logical constraints on altitude changes, timestamp order, and geographic displacement using Solidity-coded rules. Each data transaction is subject to a dual-layer security model: automated detection by the smart contract and manual authorization via MetaMask. This ensures that even flagged anomalies cannot be committed without human approval, thus combining operational oversight with blockchain's immutability. The system was tested using flight data from the OpenSky Network, with 56 attack simulations performed across spoofing, replay, and tampering categories. The contract achieved a 92.9% detection rate, with all accepted anomalies intentionally approved to test forensic transparency. Ethereum’s transparent ledger preserved all transaction details, reinforcing its potential for regulatory compliance and incident investigation. The results affirm blockchain’s suitability in protecting aviation telemetry against unauthorized modifications. Future enhancements may include machine learning for anomaly detection, stricter timestamp controls, and integration with global aircraft registries to improve spoofing detection. This implementation bridges theoretical blockchain benefits with operational air traffic requirements.
Tsukamoto Fuzzy Logic Method for Determining Mental Health Levels of Final-Year University Students Sarip, Nabila Rizky; Sriani, Sriani
ITEJ (Information Technology Engineering Journals) Vol 10 No 2 (2025): December
Publisher : Pusat Teknologi Informasi dan Pangkalan Data IAIN Syekh Nurjati Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24235/itej.v10i2.291

Abstract

Mental health is an important aspect that affects the ability of final-semester students to complete their studies and face academic and non-academic pressures. The problem that arises is the difficulty in assessing mental health conditions because it is subjective and complex. The Tsukamoto fuzzy method is used because it is able to handle data uncertainty and provides results in the form of measurable crisp values. This study aims to apply the Tsukamoto fuzzy logic method in determining the level of mental health of final-semester students in a more objective and measurable manner. This system model uses four input variables, namely stress level, sleep quality, emotional exhaustion, and duration of gadget use, with 81 rules (rule base) that form relationships between variables. The inference process is carried out through the stages of fuzzification, rule inference, and defuzzification with increasing and decreasing linear triangular membership functions. Testing was carried out using MATLAB by comparing the prediction results to actual data to calculate the model accuracy level using the Mean Absolute Percentage Error (MAPE). The results showed that the total MAPE value was 19.34%, which is in the range of 10%–20% so it is included in the good accuracy category. This demonstrates that the Tsukamoto fuzzy method can provide fairly accurate predictions of the mental health of final-semester students. Therefore, this system can be used as a tool for evaluating and early detection of student mental health in higher education settings.

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