Journal of Information Technology and Cyber Security
Journal of Information Technology and Cyber Security (JITCS) is a refereed international journal whose focus is on exchanging information relating to Information Technology and Cyber Security in industry, government, and universities worldwide. The thrust of the journal is to publish papers dealing with the the design, development, testing, implementation, and/or management of Information Technology and Cyber Security, and also to provide practical guidelines in the development and management of these systems. The journal will publish papers in Information Technology and Cyber Security in the areas of, but not limited to: 1. Enterprise Systems (ES): o Enterprise Resource Planning, o Business Process Management, o Customer Relationship Management, o System Dynamics, o E-business and e-Commerce, o Marketing Analytics, o Supply Chain Management and Logistics, o Business Analytics and Knowledge Discovery, o Production Management, o Task Analysis, o Process Mining, o Discrete Event Simulation, o Service Science and Innovation, and o Innovation in the Digital Economy. 2. Information Systems Management (ISM): o Software Engineering, o Software Design Pattern, o System Analysis and Design, o Software Quality Assurance, o Green Technology Strategies, o Strategic Information Systems, o IT Governance and Audits, o E-Government, o IT Service Management, o IT Project Management, o Information System Development, o Research Methods of Information Systems, o Adoption and Diffusion of Information Technology, o Health Information Systems and Technology, o Accounting Information Systems, o Human Behavior in Information System, o Social Technical Issues and Social Inclusion, o Domestication of Information Technology, o ICTs and Sustainable Development, o Information System in developing countries, o Software metric and cost estimation, o IT/IS audit, and o IT Risk and Management. 3. Data Acquisition and Information Dissemination (DAID): o Open Data, o Social Media, o Knowledge Management, o Social Networks, o Big Data, o Web Services, o Database Management Systems, o Semantics Web and Linked Data, o Visualization Information, o Social Information Systems, o Social Informatics, o Spatial Informatics Systems, and o Geographical Information Systems. 4. Data Engineering and Business Intelligence (DEBI): o Business Intelligence, o Data Mining, o Intelligent Systems, o Artificial Intelligence, o Autonomous Agents, o Intelligent Agents, o Multi-Agent Systems, o Expert Systems, o Pattern Recognition, o Machine Learning, o Soft Computing, o Optimization, o Forecasting, o Meta-Heuristics, o Computational Intelligence, and o Decision Support Systems. 5. IT Infrastructure and Security (ITIS): o Information Security and Privacy, o Digital Forensics, o Network Security, o Cryptography, o Cloud and Virtualization, o Emerging Technologies, o Computer Vision and Image, o Ethics in Information Systems, o Human Computer Interaction, o Wireless Sensor Networks, o Medical Image Analysis, o Internet of Things, o Mobile and Pervasive Computing, o Real-time Systems and Embedded Systems, o Parallel and Distributed Systems, o Cyber attacks, o Machine learning mechanisms for cyber security, o Modern tools for improving cyber security, o Emerging trends in cyber security, o Cyber security in Internet of Things (IoT), and o Cyber security in Cloud.
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Comparison of Dimensionality Reduction Techniques to Improve Performance and Efficiency of Logistic Regression in Network Anomaly Detection
Ahfa, Mokhamad Isna Marzuki;
Hakim, Lukman;
Rosadi, Muhammad Imron
Journal of Information Technology and Cyber Security Vol. 3 No. 1 (2025): January
Publisher : Department of Information Systems and Technology, Faculty of Intelligent Electrical and Informatics Technology, Universitas 17 Agustus 1945 Surabaya
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DOI: 10.30996/jitcs.12212
Network anomaly detection is a crucial process to identify abnormal network traffic, which may pose a security threat. This research aims to improve the performance and efficiency of Logistic Regression (LR) in network anomaly detection by applying dimension reduction techniques, such as Principal Component Analysis (PCA), Truncated Singular Value Decomposition (TSVD), t-Distributed Stochastic Neighbor Embedding (t-SNE), and Independent Component Analysis (ICA). The performance of each dimension reduction method is evaluated based on accuracy, precision, recall, F1-score, and computation time. The results show that TSVD provides the best performance with 95.86% accuracy, 0.96 precision, 0.96 recall, 0.95 F1-score, and 13.83 seconds computation time. In contrast, ICA showed the worst performance, especially in precision, recall, and F1-score, with values of 0.73, 0.83, and 0.78, respectively. Meanwhile, although t-SNE produces competitive accuracy, it has a high computational cost with an execution time of 1698.54 seconds. These findings show that choosing the right dimension reduction algorithm not only improves detection performance but also supports data processing efficiency, making it highly relevant for large-scale network security scenarios. Keywords: dimensionality reduction, Logistic Regression, network anamoly detection, performance evaluation, Truncated Singular Value Decomposition.
Clustering of Post-Disaster Building Damage Levels Using Discrete Wavelet Transform and Principal Component Analysis
Purnamasari, Putri;
Imamudin, Mochamad;
Zaman, Syahiduz;
Syauqi, A’la;
Almais, Agung Teguh Wibowo
Journal of Information Technology and Cyber Security Vol. 3 No. 1 (2025): January
Publisher : Department of Information Systems and Technology, Faculty of Intelligent Electrical and Informatics Technology, Universitas 17 Agustus 1945 Surabaya
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DOI: 10.30996/jitcs.12270
Damage assessment of buildings after natural disasters is generally performed manually by a team of experts at the disaster site, making it prone to human error and resulting in low accuracy in classifying the level of damage. This research aims to develop a more efficient and accurate method in post-disaster building damage assessment by integrating Discrete Wavelet Transform (DWT) and Principal Component Analysis (PCA) techniques. The main contribution of this research is the use of DWT as well as the application of this method on more than one image to improve the accuracy of damage level classification. A total of nine unlabelled images of post-disaster buildings were used in this study, which were obtained from the Regional Disaster Management Agency or Badan Penanggulangan Bencana Daerah (BPBD) of Malang City, Indonesia. The methods applied include data pre-processing, DWT decomposition for image analysis to identify features, and clustering using PCA to cluster the level of building damage into light, medium, and heavy categories, which are then evaluated based on accuracy. The results showed that the method yielded 100% accuracy with validation results from surveyors, as evidenced through 2D and 3D visualisations based on principal components (PC1-PC3). These findings confirm that the integration of DWT and PCA can be an effective alternative in improving the accuracy of post-disaster building damage assessment, as well as supporting decision-making in rehabilitation and reconstruction after natural disasters.
Ontology in Requirements Software Development Method: A Systematic Literature Review
Fauzan, Reza;
Hamidi, Mohammad Zaenuddin;
Safitri, Winda Ayu;
Siahaan, Daniel Oranova;
Karimi, Muhammad Ihsan
Journal of Information Technology and Cyber Security Vol. 3 No. 1 (2025): January
Publisher : Department of Information Systems and Technology, Faculty of Intelligent Electrical and Informatics Technology, Universitas 17 Agustus 1945 Surabaya
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DOI: 10.30996/jitcs.12297
The requirement process is one of the most critical factors in determining whether the software development process is successful. It is crucial to consider the function that ontology plays in the requirements of software engineering development. People and organizations can more easily utilize and share data, information, and knowledge with one another because of the implementation of ontology. During our systematic assessment of the literature published between 2011 and 2020, we came across twenty publications that discussed ontology in requirements and how it might be used in software development processes. To determine which studies were the most pertinent to our research endeavors, we developed and implemented inclusion and exclusion criteria in two separate rounds. The review identified the leading ontology in data software development challenges. We found various ways to do this in our selected papers with different systematics as well. However, our findings indicate that the ontology requirements in software development must be addressed by examining various software development methods apart from agile scrum and XP.
Early Detection of Student Problems Through a Knowledge-Based Systems-Based Counseling Approach
Rahmawati, Nisrina Salsabil;
Riska, Suastika Yulia
Journal of Information Technology and Cyber Security Vol. 3 No. 1 (2025): January
Publisher : Department of Information Systems and Technology, Faculty of Intelligent Electrical and Informatics Technology, Universitas 17 Agustus 1945 Surabaya
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DOI: 10.30996/jitcs.12617
Higher education is an important phase in an individual's academic development, but it is often characterized by challenges such as academic pressure, time management, and student mental health. To overcome these problems, this research aims to develop a technology-based Counseling Expert System with a Forward Chaining approach to detect student problems and provide relevant solutions. The system is designed and implemented as a web-based platform that can be accessed anytime and anywhere, allowing students to answer questions related to the problems faced by students. The answers are processed in a knowledge base that is integrated with an inference engine to produce diagnosis and solution recommendations. The results of system testing using 30 data samples show results that are in accordance with expert judgment. This expert system can identify six types of student problems, such as laziness, skipping classes, adaptation difficulties, difficulty doing final assignments, decreased Grade Point Average (GPA or IP), and potential dropout, by considering 32 causal factors grouped into academic, time management, emotional, and social environment categories. This research proves that the Forward Chaining-based Counseling Expert System is effective as a flexible solution to support student well-being and better student academic achievement.
Design and Implementation of Digital Transmitter Monitoring Information System for TVRI East Java Transmission Unit Using Scrum Framework
Pratama, Ario Satria Wahyu;
Shanty, Ratna Nur Tiara;
Swastyastu, Cempaka Ananggadipa
Journal of Information Technology and Cyber Security Vol. 3 No. 1 (2025): January
Publisher : Department of Information Systems and Technology, Faculty of Intelligent Electrical and Informatics Technology, Universitas 17 Agustus 1945 Surabaya
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DOI: 10.30996/jitcs.12979
The Digital Transmitter Monitoring Information System for the TVRI East Java Transmission Unit is developed to enhance efficiency in recording and monitoring transmitter conditions, which were previously documented manually using logbooks. This system is designed to facilitate operators in recording technical transmitter data and assist technicians in the failure analysis process. The development method used is the Scrum methodology, allowing the system to be developed iteratively with improvements based on user feedback. System testing is conducted using Black-Box Testing to ensure all features function according to user requirements, while system acceptance evaluation is carried out using the Technology Acceptance Model (TAM) to measure the system's usability and ease of use. The testing results indicate that all system features function properly without significant errors. The TAM evaluation produced an average score of 84.5% for perceived usefulness and 86.5% for perceived ease of use, indicating that the system is well accepted by users. With key features such as transmitter data recording, reporting, employee performance tracking, and data export, this system is expected to help TVRI East Java monitor digital transmitters more effectively and efficiently. Compared to the previous manual logbook system, this digital-based approach reduces dependency on physical documentation, minimizes the risk of data loss, and improves accessibility for operators and technicians. By enabling centralized data storage and streamlined reporting, the system ensures that monitoring activities are more structured, responsive, and cost-effective.