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.
Articles
30 Documents
<![CDATA[Dialect Classification of the Javanese Language Using the K-Nearest Neighbor ]]>
<![CDATA[Filby, Brilliant]]>;
<![CDATA[Pujianto, Utomo]]>;
<![CDATA[Hammad, Jehad A. H.]]>;
<![CDATA[Wibawa, Aji Prasetya]]>
<![CDATA[ Journal of Information Technology and Cyber Security Vol. 2 No. 2 (2024): July ]]>
Publisher : <![CDATA[Department of Information Systems and Technology, Faculty of Intelligent Electrical and Informatics Technology, Universitas 17 Agustus 1945 Surabaya ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30996/jitcs.12213
<![CDATA[Indonesia is rich in ethnic and cultural diversity, each reflected in its unique linguistic characteristics. One way to preserve the Javanese language is by conducting research on its dialects. This study aims to classify three main dialects in Java Island—East Java, Central Java, and West Java—using text data from online sources. The classification process includes preprocessing (tokenizing, case folding, and word weighting), data balancing with the Synthetic Minority Oversampling Technique (SMOTE), and classification using the K-Nearest Neighbor (K-NN) algorithm. This study highlights the importance of dialect recognition in supporting the preservation of the Javanese language and the development of linguistic technology applications. Testing using 10-fold cross-validation showed the best performance at , with an accuracy of 94.05%, precision of 95.83%, and recall of 94.44%. These findings significantly support computational linguistics research and the preservation of regional languages.]]>
<![CDATA[Clustering of Post-Disaster Building Damage Levels Using Discrete Wavelet Transform and Principal Component Analysis ]]>
<![CDATA[Purnamasari, Putri]]>;
<![CDATA[Imamudin, Mochamad]]>;
<![CDATA[Zaman, Syahiduz]]>;
<![CDATA[Syauqi, A’la]]>;
<![CDATA[Almais, Agung Teguh Wibowo]]>
<![CDATA[ Journal of Information Technology and Cyber Security Vol. 3 No. 1 (2025): January ]]>
Publisher : <![CDATA[Department of Information Systems and Technology, Faculty of Intelligent Electrical and Informatics Technology, Universitas 17 Agustus 1945 Surabaya ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30996/jitcs.12270
<![CDATA[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.]]>
<![CDATA[Ontology in Requirements Software Development Method: A Systematic Literature Review ]]>
<![CDATA[Fauzan, Reza]]>;
<![CDATA[Hamidi, Mohammad Zaenuddin]]>;
<![CDATA[Safitri, Winda Ayu]]>;
<![CDATA[Siahaan, Daniel Oranova]]>;
<![CDATA[Karimi, Muhammad Ihsan]]>
<![CDATA[ Journal of Information Technology and Cyber Security Vol. 3 No. 1 (2025): January ]]>
Publisher : <![CDATA[Department of Information Systems and Technology, Faculty of Intelligent Electrical and Informatics Technology, Universitas 17 Agustus 1945 Surabaya ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30996/jitcs.12297
<![CDATA[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.]]>
<![CDATA[Penetration Testing and Vulnerability Analysis of SINTA Platform to Strengthen Privacy and Data Protection ]]>
<![CDATA[Supangat, Supangat]]>;
<![CDATA[Amna, Anis Rahmawati]]>;
<![CDATA[Rochman, Mochamad Yovi Fatchur]]>
<![CDATA[ Journal of Information Technology and Cyber Security Vol. 3 No. 2 (2025): July ]]>
Publisher : <![CDATA[Department of Information Systems and Technology, Faculty of Intelligent Electrical and Informatics Technology, Universitas 17 Agustus 1945 Surabaya ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30996/jitcs.12216
<![CDATA[The increasing reliance on digital platforms for academic and governmental purposes necessitates robust cybersecurity measures. Consequently, identifying vulnerability is critical to ensuring data security and providing actionable recommendations for cybersecurity officers. Platforms like Sinta (Science and Technology Index), which focus on collecting peer-reviewed papers and maintaining researcher’s research records, represents significant governmental contributions in academia. Cybersecurity awareness is demonstrated through events organized to evaluate the vulnerability of the platform, enabling researchers to access its security and report potential issues. This study addresses these concerns by conducting system penetration testing using the OWASP and Burp Suite Framework, focusing on identifying five critical vulnerabilities. The evaluation examines issues, such as sensitive data exposure in API responses, error log disclosures, email enumeration, and improper access to system files. The results reveal that the platform suffers from multiple levels of security vulnerabilities, prompting recommendations for authorities to take actions to mitigate potential risks effectively.]]>
<![CDATA[Early Detection of Student Problems Through a Knowledge-Based Systems-Based Counseling Approach ]]>
<![CDATA[Rahmawati, Nisrina Salsabil]]>;
<![CDATA[Riska, Suastika Yulia]]>
<![CDATA[ Journal of Information Technology and Cyber Security Vol. 3 No. 1 (2025): January ]]>
Publisher : <![CDATA[Department of Information Systems and Technology, Faculty of Intelligent Electrical and Informatics Technology, Universitas 17 Agustus 1945 Surabaya ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30996/jitcs.12617
<![CDATA[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.]]>
<![CDATA[A Comparison of Polynomial Regression and Support Vector Regression for Predicting the Consumer Price Index Based on Food Commodity Prices in East Java, Indonesia ]]>
<![CDATA[Suyono, Ayu Adelina]]>
<![CDATA[ Journal of Information Technology and Cyber Security Vol. 3 No. 2 (2025): July ]]>
Publisher : <![CDATA[Department of Information Systems and Technology, Faculty of Intelligent Electrical and Informatics Technology, Universitas 17 Agustus 1945 Surabaya ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30996/jitcs.12353
<![CDATA[Food price fluctuations occur almost daily and directly affect purchasing power as well as the stability of regional and national economies. As one of the largest provinces in Indonesia, East Java, which significantly contributes to national GDP, has diverse economic structures and highly sensitive to price changes. Given this situation, government needs more accurate prediction methods to monitor Consumer Price Index (CPI) movement as a basis for establishing more appropriate economic strategy and policy. This study aims to compare the performance of Polynomial Regression (PR) and Support Vector Regression (SVR) in predicting CPI using food price data from SISKAPERBAPO for the 2014 - 2020 period, covering regencies and cities in East Java. To ensure the quality of the analysis, missing values were removed. A Pearson’s r correlation analysis was then conducted to assess the relationships between food prices and CPI. The model obtained was then evaluated using mean squared error (MSE), root mean square error (RMSE), Mean absolute percentage error (MAPE), and computation time. The results shows that third order PR achieved higher accuracy with MAPE of 0.3% (training) and 3.4% (testing), while SVR performed lower with MAPE of 5.9% (training) and 6.0% (testing). In addition, PR was more computationally efficient than SVR. These findings underscore PR as a more reliable method for predicting CPI using complex regional food data.]]>
<![CDATA[Payroll Decision Support System for Production Employees Based on Key Performance Indicators Using the Simple Additive Weighting Method ]]>
<![CDATA[Suganda, Tegar Bangun]]>;
<![CDATA[Dzikria, Intan]]>
<![CDATA[ Journal of Information Technology and Cyber Security Vol. 3 No. 2 (2025): July ]]>
Publisher : <![CDATA[Department of Information Systems and Technology, Faculty of Intelligent Electrical and Informatics Technology, Universitas 17 Agustus 1945 Surabaya ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30996/jitcs.12523
<![CDATA[CV. XYZ is a Micro, Small, and Medium Enterprise (MSME) engaged in plastic sack sewing services and implements a piece rate pay system. The company faces obstacles in managing performance-based payroll, which impacts operational efficiency and payment accuracy. This study aims to develop a Payroll Decision Support System (DSS) to record and evaluate the work results of production employees using Key Performance Indicators (KPIs). KPI evaluation is applied as the main criteria in weighting using the Simple Additive Weighting (SAW) method, to produce optimal performance scores. The implementation of KPI-based incentives is expected to improve employee performance while encouraging a productive and transparent work culture. Blackbox testing shows that 97% of the test data meets user requirements, indicating that the system can run according to specifications. The results of this study contribute to the integration of KPIs and SAW in assessing production employee performance for fair and effective payroll decision-making, as well as helping companies implement efficient management practices.]]>
<![CDATA[Design and Implementation of Digital Transmitter Monitoring Information System for TVRI East Java Transmission Unit Using Scrum Framework ]]>
<![CDATA[Pratama, Ario Satria Wahyu]]>;
<![CDATA[Shanty, Ratna Nur Tiara]]>;
<![CDATA[Swastyastu, Cempaka Ananggadipa]]>
<![CDATA[ Journal of Information Technology and Cyber Security Vol. 3 No. 1 (2025): January ]]>
Publisher : <![CDATA[Department of Information Systems and Technology, Faculty of Intelligent Electrical and Informatics Technology, Universitas 17 Agustus 1945 Surabaya ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30996/jitcs.12979
<![CDATA[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.]]>
<![CDATA[Development of a Web-Based Spare Parts Inventory System Using the First-In, First-Out Method and Acceptance Analysis Based on the Unified Theory of Acceptance and Use of Technology ]]>
<![CDATA[Firdaus, Adam]]>;
<![CDATA[Swastyastu, Cempaka Ananggadipa]]>;
<![CDATA[Shanty, Ratna Nur Tiara]]>
<![CDATA[ Journal of Information Technology and Cyber Security Vol. 3 No. 2 (2025): July ]]>
Publisher : <![CDATA[Department of Information Systems and Technology, Faculty of Intelligent Electrical and Informatics Technology, Universitas 17 Agustus 1945 Surabaya ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30996/jitcs.13042
<![CDATA[As a service-oriented company, Jaya Sentosa faces significant challenges in managing its spare parts inventory, leading to resource inefficiencies. Key issues include documentation discrepancies, inventory inconsistencies, and inadequate monitoring mechanisms. To address these problems, this study designs and implements a web-based information system, referred to as SIWEB-JS, aimed at enhancing inventory accuracy and operational efficiency. The system was developed using the Rapid Application Development (RAD) approach, adopting the First-In, First-Out (FIFO) principle, and built with PHP using the CodeIgniter v4.4.4 framework, supported by a MySQL database. System functionality was evaluated through Black-Box Testing, while user acceptance was assessed using the Unified Theory of Acceptance and Use of Technology (UTAUT). The results indicate that SIWEB-JS effectively records real-time transactions, maintains accurate inventory levels, and improves data accessibility. The implementation of FIFO contributed to better inventory governance. Furthermore, the UTAUT-based evaluation revealed that Performance Expectancy (PE), Effort Expectancy (EE), and Social Influence (SI) significantly influenced Behavioral Intention (BI), suggesting that the system is perceived as useful, user-friendly, and well-supported by users.]]>
<![CDATA[Early Breast Cancer Detection Using Gabor Filter and Convolutional Neural Network for Microcalcification Identification ]]>
<![CDATA[Mufti, Abdul Latief]]>;
<![CDATA[Whardana, Adithya Kusuma]]>
<![CDATA[ Journal of Information Technology and Cyber Security Vol. 3 No. 2 (2025): July ]]>
Publisher : <![CDATA[Department of Information Systems and Technology, Faculty of Intelligent Electrical and Informatics Technology, Universitas 17 Agustus 1945 Surabaya ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30996/jitcs.132037
<![CDATA[Breast cancer poses a considerable challenge in Indonesia, resulting in numerous fatalities. This study aims to improve the accuracy and efficiency of early breast cancer diagnosis by leveraging modern image processing and artificial intelligence. The dataset used is the Mini-DDSM (Mini Digital Database for Screening Mammography), taken from Kaggle and vetted by radiologists into a Region of Interest (ROI) consisting of three categories: Benign, Cancer, and Normal. The methodology encompasses comprehensive image preprocessing, which includes resizing, cropping, RGB-to-grayscale conversion, Laplacian of Gaussian (LoG) filtering, Gabor filtering, global threshold segmentation, and image enhancement. A Convolutional Neural Network (CNN) is employed for classification purposes. Ninety percent of the images are allocated for training, while 10% are designated for testing, with critical parameters such as learning rate, batch size, and epochs being tuned throughout the training process. The CNN architecture was assessed based on recognition rate, error rate, epoch count, and training duration. The results provide a flawless validation accuracy of 100% over 32 trials. The findings demonstrate that the suggested method markedly enhances early breast cancer identification using microcalcification analysis in mammography images, assisting medical professionals in early diagnosis and potentially elevating patient recovery rates through prompt detection and treatment.]]>
