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The IJICS (International Journal of Informatics and Computer Science)
Published by Sekolah Tinggi Manajemen Informatika dan Komputer Budi Darma
ISSN : 25488449     EISSN : 25488384     DOI : https://doi.org/10.30865/ijics
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering
The The IJICS (International Journal of Informatics and Computer Science) covers the whole spectrum of intelligent informatics, which includes, but is not limited to : • Artificial Immune Systems, Ant Colonies, and Swarm Intelligence • Autonomous Agents and Multi-Agent Systems • Bayesian Networks and Probabilistic Reasoning • Biologically Inspired Intelligence • Brain-Computer Interfacing • Business Intelligence • Chaos theory and intelligent control systems • Clustering and Data Analysis • Complex Systems and Applications • Computational Intelligence and Soft Computing • Cognitive systems • Distributed Intelligent Systems • Database Management and Information Retrieval • Evolutionary computation and DNA/cellular/molecular computing • Expert Systems • Fault detection, fault analysis and diagnostics • Fusion of Neural Networks and Fuzzy Systems • Green and Renewable Energy Systems • Human Interface, Human-Computer Interaction, Human Information Processing • Hybrid and Distributed Algorithms • High Performance Computing • Information storage, security, integrity, privacy and trust • Image and Speech Signal Processing • Knowledge Based Systems, Knowledge Networks • Knowledge discovery and ontology engineering • Machine Learning, Reinforcement Learning • Memetic Computing • Multimedia and Applications • Networked Control Systems • Neural Networks and Applications • Natural Language Processing • Optimization and Decision Making • Pattern Classification, Recognition, speech recognition and synthesis • Robotic Intelligence • Rough sets and granular computing • Robustness Analysis • Self-Organizing Systems • Social Intelligence • Soft computing in P2P, Grid, Cloud and Internet Computing Technologies • Stochastic systems • Support Vector Machines • Ubiquitous, grid and high performance computing • Virtual Reality in Engineering Applications • Web and mobile Intelligence, and Big Data
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "Vol. 9 No. 3 (2025): November" : 5 Documents clear
Book Tracking Methods In Libraries Using Online Public Access Catalog sipayung, liska; Megaria Purba; Abiomega Maria Manalu; Puji Nirwana
The IJICS (International Journal of Informatics and Computer Science) Vol. 9 No. 3 (2025): November
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Advances in information technology have encouraged libraries to transform from conventional service systems to digital-based services to improve the quality of information access for users. One problem still frequently encountered in libraries is the limited access for users to quickly and accurately search for books, especially in libraries with growing collections. This study examines the implementation of a book tracking method in libraries using the Online Public Access Catalog (OPAC) as the primary means of searching collections. The purpose of this study is to analyze the effectiveness of OPAC use in helping users find bibliographic information and book locations independently and efficiently. The research methods used included literature review, user needs analysis, digital catalog system design, and implementation of a web-based OPAC integrated with the library's collection database. The OPAC system is designed to support book searches based on various parameters, such as title, author, subject, and keywords, thus facilitating user access to relevant information. System testing was conducted through functional testing and usability evaluation to assess the accuracy of search results and user-friendliness of the interface. The results indicate that the implementation of OPAC can improve the speed and accuracy of the book tracking process, reduce search errors, and increase user satisfaction with library services. Furthermore, this system contributes to improving librarians' work efficiency and supporting more structured collection management. Therefore, the OPAC book tracking method can be a strategic solution to support the modernization of library services and the sustainable optimization of information access.
Development of a Social Communications Application Expert System for Youth Faith Analysis Purba, mesisren; Liskedame Yanti Sipayung; Puteri Fajar Addini; Tesalonika Pesta Siagian; Nurika Sari Siregar
The IJICS (International Journal of Informatics and Computer Science) Vol. 9 No. 3 (2025): November
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/ijics.v9i3.9437

Abstract

Monitoring adolescent faith development requires an objective and data-driven approach, whereas existing practices remain largely manual, subjective, and weakly documented. This study proposes a web-based expert system as a decision support tool for classifying levels of adolescent faith development. The novelty of this research lies in the integration of a rule-based inference engine using forward chaining with a structured, indicator-driven assessment framework. The system was developed using a structured software engineering approach, including UML-based functional modeling and an Entity Relationship Diagram (ERD) for database design. The expert system processes assessment data derived from four validated indicators: prayer practice, participation in communal activities, social attitudes, and faith reflection. Data were collected from 30 respondents through a web-based assessment module and analyzed using expert-defined inference rules. The classification results indicate that 33.3% of respondents were categorized as having good faith development, 46.7% moderate, and 20.0% low. Functional testing using black-box methods confirmed that all system features operated according to specifications, while expert validation confirmed the relevance and consistency of indicators and inference rules. These findings demonstrate that the proposed system produces measurable and consistent classification outcomes, contributing to the application of expert systems and web-based decision support technologies for objective adolescent development monitoring.
Analysis of Digital Image Forensics Authentication in Image Forgery Cases Dameria E Br Jabat; Megaria Purba; Mhd. Avin Winata; Sophia Widiana
The IJICS (International Journal of Informatics and Computer Science) Vol. 9 No. 3 (2025): November
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/ijics.v9i3.9440

Abstract

This document introduces a combined framework for validating digital images in forensic contexts by merging Error Level Analysis (ELA) with Convolutional Neural Networks (CNN). The innovation of this research resides in the direct integration of a conventional explainable forensic method alongside a datadriven deep learning approach to ensure both clarity and enhanced detection efficacy. ELA serves to identify JPEG compression irregularities as forensic indicators, whereas CNN is employed to extract significant hierarchical features for robust image categorization. Trials were performed on the CASIA v2.0 dataset, which comprises 10,002 authentic and altered images. The suggested two-stream architecture concurrently processes original images and ELA-generated maps, facilitating synergistic feature acquisition. The hybrid model secures an accuracy rate of 74.32%, illustrating a 7.2% enhancement over isolated ELA. Furthermore, the framework diminishes the false positive rate from 50.2% to 34.8% while maintaining high sensitivity (0.84) in identifying altered regions. From a machine learning angle, this research illustrates how manually crafted forensic attributes can boost CNN capabilities when merged at the input stage. From an image processing viewpoint, it confirms ELA as a potent preprocessing strategy for directing deep feature extraction. The proposed framework provides an equilibrium between precision and forensic transparency, making it ideal for real-world digital forensic practices, including application in environments with limited resources.
Implementation of K-Nearest Neighbor Algorithm for Scientific Determination of Aid Recipients at STM Agape Sinaga, Dedi Candro Parulian; Siahaan, R. Fanry; Tarigan, Nera Mayana Br; Lubis, Rodiah Hannum; Amallia, Dwi Novia
The IJICS (International Journal of Informatics and Computer Science) Vol. 9 No. 3 (2025): November
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/ijics.v9i3.9484

Abstract

Providing assistance to underprivileged families is an important social effort to enhance community welfare; however, the selection of aid recipients often encounters problems such as subjectivity, unstructured data, and time inefficiency when conducted manually. This study aims to develop and evaluate a decision support system for determining aid recipients at STM Agape using the K-Nearest Neighbor (KNN) algorithm to improve accuracy and objectivity in the selection process. The research methodology employed a quantitative classification approach, where data were collected from families based on predefined criteria, including family income, number of dependents, housing conditions, and the occupation of the head of the household. The dataset was divided into training and testing data, and all attributes were normalized prior to processing. The KNN algorithm was applied using Euclidean distance to measure similarity between data instances, classifying each family into “eligible” or “ineligible” categories. The results indicate that the proposed system achieved higher classification accuracy and more consistent decision outcomes compared to manual selection methods. Additionally, the implementation of KNN reduced processing time and minimized subjective bias in determining aid recipients. These findings demonstrate that the KNN-based system is effective as a decision support tool, enabling STM Agape to distribute social assistance in a more targeted, objective, transparent, and efficient manner.
Analysis of Data Security Resilience in Text Steganography on Indonesian Language Structure R. Fanry Siahaan; Dedi Candro P. Sinaga; Zanziqbar Alaydrus; Ikhwan Rafif Fadhil
The IJICS (International Journal of Informatics and Computer Science) Vol. 9 No. 3 (2025): November
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/ijics.v9i3.9487

Abstract

An in depth analysis of data security in text-based steganography is necessary to ensure the sustainability and security of the methodology used. The purpose of this study is to analyze the resilience of data security in text-based steganography. The analytical approach used involves identifying and assessing the vulnerabilities of text steganography methods using Indonesian sentence patterns. The initial stage of the research was to analyze previous works related to this field to understand previously identified vulnerabilities. The applied text embedding model is based on a dictionary consisting of 1,929 words grouped into seven word categories that correspond to sentence patterns in Indonesian, namely adj (adjective), adv (adverb), nom (noun), num (numeral), par (particle), pro (pronoun), and ver (verb). Each word class is arranged into a sentence structure and each has the same bit length, namely eight bits. The robustness analysis results show that single-word input data is still vulnerable to brute-force attacks or pattern analysis if the message embedding process uses a simple sentence structure. This is due to the relatively small search space, which makes it easier for attackers to guess the embedding pattern. Conversely, using sentence patterns consisting of more than two words significantly increases combinatorial complexity and expands the possibility space, making hacking attempts much more computationally difficult. Thus, the robustness of a steganographic system increases as the number of words in the sentence pattern increases, as the time and resources required to perform the attack become practically inefficient.

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