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International Journal of Information Engineering and Science
Published by Asosiasi Riset Teknik Elektro Dan Informatika Indonesia
ISSN : 30481902     EISSN : 30481953     DOI : 10.62951
Core Subject : Engineering,
Engineering
The scope of the this Journal covers the fields of Information Engineering and Science. This journal is a means of publication and a place to share research and development work in the field of technology
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 27 Documents
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Literature Review on Histogram-Based Image Forensics for Recaptured Image Detection Nathanael David Christian Barus; Nayem Kibriya; Natasha Fedora Barus
International Journal of Information Engineering and Science Vol. 1 No. 3 (2024): August : International Journal of Information Engineering and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijies.v1i3.35

Abstract

This qualitative literature review explores the realm of histogram-based image forensics for recaptured image detection, addressing the challenges posed by advancements in display technology and the subsequent need for robust forensic techniques. The research methodology involves a systematic approach, including defined research objectives, thorough literature search, data extraction, thematic analysis, and ethical considerations. The focal point is the proposed method utilizing Local Ternary Count (LTC) histograms normalized from residue maps, demonstrating exceptional performance across various databases. The methodology involves residue map calculation, LTC histogram extraction, and experiments showcasing the method's efficiency in both single and mixed databases. The discussion emphasizes emerging frontiers in recaptured image forensics, presenting innovative algorithms categorized by the medium used during the recapture process. The shift towards deep learning methods is noted, with a focus on a proposed algorithm for detecting images recaptured from LCD screens based on quality-aware features and histogram features. The RID field has witnessed advancements, with a detailed overview of methods categorically addressing recapture from LCD screens. Ethical considerations are integrated into the discussion, and the conclusion emphasizes the need for constant adaptation, innovation, and collaboration in the fight against evolving manipulation techniques. Looking ahead, the fusion of features, standardized datasets, and advanced deep learning architectures are identified as key elements for future research in ensuring image authenticity
Optimizing the Transmission of Church Information Through the Design Thinking-Based Church News Application Gunawan Prayitno; Jenny Tandi
International Journal of Information Engineering and Science Vol. 1 No. 3 (2024): August : International Journal of Information Engineering and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijies.v1i3.44

Abstract

The church plays a crucial role in spreading Christian values and nurturing the growth of faith within its community. However, in the context of GPSI EFATA, there are several challenges in effectively conveying church information. These challenges include the unappealing presentation of physical congregation news, the accumulation of paper, and limited distribution of information. In order to address these issues, this research project utilizes the Design Thinking method to develop a smartphone-based application for congregational news. The Design Thinking method consists of five stages: empathy, definition, ideation, prototype, and testing. During the empathy stage, the needs of the congregation are identified, particularly the need for more accessible and engaging information. The ideation stage then generates a solution in the form of a smartphone application. This application includes various features such as notifications, prayer schedules, financial reports, photo galleries, and management profiles. A prototype of the application was developed to meet these needs and was subsequently tested using a questionnaire. The results of the testing indicated that the application had an easy-to-understand interface, adequate features, and received suggestions for improvement. Overall, this smartphone application offers a modern and efficient solution to the challenges of delivering information within churches. It enhances accessibility and improves the quality of communication with the congregation.
Processing Student Comments on Understanding of Lecture Materials Using Rule Based Automata Finite State Model Febri Febri; Suharmanto Suharmanto
International Journal of Information Engineering and Science Vol. 1 No. 3 (2024): August : International Journal of Information Engineering and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijies.v1i3.45

Abstract

Serang Raya University, is a private tertiary institution in the province of Banten, There are 4 faculties, Vocational D3 and 17 Study Programs, in the process of teaching and learning activities each lecturer has a different way of teaching students. Faculty of Information Technology, Computer Science Engineering study program with 30 lecturers, 9 classes, 59 courses and 126 students. This does not require the possibility that with the number of courses taken on campus there are sti ll many students who do not understand what the lecturer is delivering. Management of student comments on the understanding of lecture material is designed to make it easy for students to comment on the lecturer's presentation of the material. This is also used as evaluation material for lecturers regarding the delivery of material. Currently, Serang Raya University does not have a website-based information system. From this discussion, comments are made with the Rule-based Finite State Automata model. In reading the comments, this produces a system that can read comments word by word until the end of the word with a space separator so that it finds keywords, namely the keywords understand and don't understand.
Detection of Attacks in Computer Networks Using C4.5 Decision Tree Algorithm: An Approach to Network Security Wahyu Wijaya Widiyanto; Rizka Licia
International Journal of Information Engineering and Science Vol. 1 No. 4 (2024): November : International Journal of Information Engineering and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijies.v1i4.48

Abstract

The detection of computer network attacks is becoming increasingly important as the complexity and frequency of cyber-attacks threatening information systems and network infrastructure continue to rise. These attacks may lead to severe consequences, including data breaches, service disruptions, and financial losses. To address these challenges, artificial intelligence techniques have become a major focus in the development of more effective, adaptive, and reliable intrusion detection systems. Among various classification algorithms, the C4.5 decision tree has demonstrated strong performance due to its simplicity, interpretability, and high classification accuracy. This study aims to apply the C4.5 algorithm for network attack detection using a comprehensive dataset that includes multiple categories of attacks and normal network activities. The proposed methodology consists of several stages, including data preprocessing, feature selection, decision tree model construction, and performance evaluation using standard metrics such as accuracy, precision, recall, and F1-score. Data preprocessing is performed to handle missing values, normalize data, and reduce noise, thereby improving the overall quality of the dataset and enhancing classification results. The experimental results indicate that the C4.5 decision tree algorithm effectively classifies network traffic into attack and normal categories with a satisfactory level of accuracy. The model successfully identifies attack-related patterns and highlights significant features that influence detection performance. Further analysis reveals that appropriate feature selection and parameter tuning significantly contribute to improving model reliability and robustness. This research provides a valuable contribution to the development of efficient, accurate, and practical network intrusion detection systems. The proposed approach is expected to strengthen information security frameworks and support proactive defense strategies against increasingly sophisticated cyber threats, thereby enhancing the protection of critical network infrastructures.
Enhancing Cybersecurity Posture: A Framework for Anomaly Detection in Cloud Computing Environments David Jackson; Barbara Harris; Richard Clark
International Journal of Information Engineering and Science Vol. 1 No. 3 (2024): August : International Journal of Information Engineering and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijies.v1i3.66

Abstract

The rapid adoption of cloud computing has transformed the way organizations manage and store their data. However, this shift has also increased vulnerabilities to cyber threats. Anomaly detection is a critical component of cybersecurity frameworks, allowing for the identification of unusual patterns that may indicate security breaches. This paper presents a comprehensive framework for anomaly detection in cloud computing environments. It reviews existing methodologies, explores the integration of machine learning techniques, and discusses the challenges associated with implementing these systems. The proposed framework aims to enhance the cybersecurity posture of organizations by providing proactive detection of anomalies.
An Enhanced Machine Learning Model for Real-Time Anomaly Detection in Cyber-Physical Systems Karen Robinson; Nancy Allen; Christopher Young
International Journal of Information Engineering and Science Vol. 1 No. 3 (2024): August : International Journal of Information Engineering and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijies.v1i3.67

Abstract

As cyber-physical systems (CPS) gain prevalence in sectors such as manufacturing, transportation, and critical infrastructure, ensuring their security and reliability is paramount. Traditional anomaly detection methods often fall short due to the dynamic and complex nature of CPS, leading to missed or false alarms. This study introduces an enhanced machine learning model that integrates statistical and deep learning techniques for real-time anomaly detection in CPS. By employing a hybrid approach of convolutional neural networks (CNNs) with statistical pattern recognition, the model demonstrates improved detection accuracy and responsiveness. Performance is evaluated using industry-standard CPS datasets, showing that the proposed model outperforms existing techniques in both accuracy and efficiency.
Utilization Application and System Geographical Information Website: Systematic Literature Review Muhamad Rizky
International Journal of Information Engineering and Science Vol. 1 No. 4 (2024): November : International Journal of Information Engineering and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijies.v1i4.101

Abstract

Geographic Information Systems (GIS) have become essential technological tools for collecting, storing, processing, analyzing, and visualizing spatial data to support various human activities. The rapid advancement of information technology has significantly expanded the use of GIS, particularly through web-based platforms and mobile applications, enabling wider accessibility and real-time data utilization. This study focuses on analyzing the utilization of GIS applications and websites across multiple sectors and their contributions to improving efficiency, accuracy, and decision-making processes in daily life. The main objective of this research is to identify, evaluate, and synthesize recent developments in GIS implementation through a systematic literature review. Scientific articles were collected from reputable international and national journals published within the last five years (2018–2022). A total of 130 international journals and 100 national journals were initially identified through database searches. After applying relevance screening and inclusion criteria, 33 selected articles were analyzed in depth to extract key findings, application trends, and potential research gaps. The results show that GIS applications and web-based systems play a vital role in supporting various sectors. In education, GIS facilitates spatial mapping for industrial internship placement (PRAKERIN) and school zoning management. In healthcare, GIS assists in mapping healthcare facilities, including pharmacies and hospitals, to improve service accessibility. In transportation, GIS-based systems provide route planning, traffic monitoring, and public transport information to enhance mobility and reduce congestion. GIS applications are also increasingly applied in environmental monitoring, disaster management, urban planning, and natural resource management. Overall, this study emphasizes the growing importance of GIS technologies as strategic tools for data-driven decision-making and sustainable development. The findings are expected to provide valuable insights for researchers, practitioners, and policymakers in optimizing GIS-based solutions to improve public services and quality of life.
Online Class UI/UX Design Using Design Thinking Method in Virtual Reality Environment Bosya Perdana; Tata Sutabri
International Journal of Information Engineering and Science Vol. 1 No. 4 (2024): November : International Journal of Information Engineering and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijies.v1i4.114

Abstract

Online learning has become an essential component of modern education; however, conventional online learning platforms often rely on two-dimensional interfaces that limit user engagement, interaction, and immersion. These limitations reduce learning motivation and hinder the creation of an effective learning experience, particularly for activities that require active participation. To address these challenges, this research focuses on the design of User Interface (UI) and User Experience (UX) for online learning implemented in a Virtual Reality (VR) environment. The objective of this study is to develop a user-centered VR-based online learning interface that enhances interaction, usability, and learning comfort. This research applies the Design Thinking methodology, which consists of five stages: empathize, define, ideate, prototype, and test. User needs and usability issues were identified through observations and interviews, followed by interface design and prototype development of a VR learning environment featuring chat rooms, whiteboards, slide presentations, and virtual representations of teachers and students. Usability evaluation was conducted using the Maze platform to measure user success rates in completing predefined tasks. The results show that 80% of users completed tasks through the expected interaction paths, exceeding the minimum usability threshold of 70%, while 20% of users failed to complete the tasks, indicating areas for improvement. These findings demonstrate that the proposed UI/UX design effectively supports user interaction and usability in a VR-based learning environment. In conclusion, this study confirms that integrating Design Thinking into the UI/UX design process contributes to the development of effective and user-centered VR-based online learning systems, while also highlighting the importance of usability evaluation for refining immersive educational interfaces.
Implementation of IT Governance in the Design of Expert Systems for Improving Library User Services Muhammad Wahyudi; Darmeli Nasution
International Journal of Information Engineering and Science Vol. 1 No. 4 (2024): November : International Journal of Information Engineering and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijies.v1i2.117

Abstract

The integration of IT Governance and expert system design offers transformative benefits for enhancing library user services. This research employs the COBIT 5.0 framework to align IT strategies with library objectives while developing an expert system tailored for personalized recommendations. The findings indicate that the expert system significantly improves operational efficiency, service accuracy, and user satisfaction by using user profiles to recommend relevant materials and streamline the borrowing process. Testing revealed high user satisfaction levels, with 96.6% finding the system effective and 100% confirming its efficiency. Additionally, IT Governance ensures strategic integration between technological infrastructure and service quality objectives, enabling data-driven decision-making. The study also highlights challenges, such as the need for robust data management and user training, suggesting areas for future improvement. Recommendations include incorporating machine learning to enhance system intelligence, conducting regular evaluations to maintain system relevance, and testing the scalability of this approach across various types of libraries. By integrating IT Governance with an expert system, this research sets a strong foundation for modernizing library services to better meet user expectations in the digital era.
Automatic Passenger Counting System on Public Buses Using CNN YOLOv8 Model for Passenger Capacity Optimization Ari Dian Prastyo; Sharfina Andzani Minhalina; Surya Agung; Denty Nirwana Bintang; Muhammad Yordi Septian; Endang Purnama Giri; Gema Parasti Mindara
International Journal of Information Engineering and Science Vol. 1 No. 4 (2024): November : International Journal of Information Engineering and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijies.v1i4.121

Abstract

This study presents the development and evaluation of an automatic passenger counting system for public buses using the YOLOv8 algorithm based on Convolutional Neural Networks (CNN). Accurate passenger counting plays a crucial role in optimizing public transportation operations, as it enables effective capacity management, reduces operational costs, and improves overall passenger comfort. Conventional manual counting methods are often inefficient, time-consuming, and prone to human error, particularly in high-density urban transportation environments. Therefore, an automated and intelligent solution is required to support real-time monitoring and operational decision-making. The proposed system employs deep learning-based object detection to identify and count passengers from video streams captured by cameras installed inside buses. Two camera positions, namely front and rear views, were evaluated to assess system performance under different visual conditions. The experimental results show that the system achieves high detection accuracy in the front camera view, with a confidence score of 0.82, indicating reliable performance in scenarios with minimal object occlusion. In contrast, the rear camera view demonstrates slightly lower accuracy, with a confidence score of 0.76, mainly due to increased object overlap and variations in lighting conditions. These findings emphasize the importance of appropriate camera placement and environmental consideration in improving detection reliability. In addition, the implementation of the proposed system enables real-time monitoring of passenger flow, which supports dynamic scheduling, demand-based route planning, and efficient fleet management. Accurate passenger data allows transportation operators to optimize service allocation, reduce congestion, and enhance overall service quality. Overall, this study contributes to the development of intelligent transportation systems by demonstrating the practical applicability of deep learning-based passenger counting solutions. The proposed approach offers strong potential for real-world deployment in smart city environments, supporting the creation of more sustainable, efficient, and passenger-oriented public transportation services.

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