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Tri A. Sundara
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The Indonesian Journal of Computer Science
Published by STMIK Indonesia Padang
ISSN : 25497286     EISSN : 25497286     DOI : https://doi.org/10.33022
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering Engineering
The Indonesian Journal of Computer Science (IJCS) is a bimonthly peer-reviewed journal published by AI Society and STMIK Indonesia. IJCS editions will be published at the end of February, April, June, August, October and December. The scope of IJCS includes general computer science, information system, information technology, artificial intelligence, big data, industrial revolution 4.0, and general engineering. The articles will be published in English and Bahasa Indonesia.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 1,114 Documents
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Comparative Evaluation of Inception V3 and YOLOv8 for Strawberry Plant Diseases Classification Using Deep Learning Models Tin Tin Wai; Aye, Maung; Hla, Tin Tin
The Indonesian Journal of Computer Science Vol. 14 No. 1 (2025): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i1.4750

Abstract

Plant diseases and pests threaten agricultural productivity, with leaf diseases causing major crop losses. Early detection is essential to mitigate these impacts. This study presents a system for detecting strawberry leaf diseases using deep learning-based Convolutional Neural Networks (CNNs) by utilizing two pre-trained models, Inception V3 and YOLOv8, to classify leaves as healthy or diseased. A custom dataset of 5,192 images, comprising one healthy class and four disease-infected categories (leaf blight, blotch, scorch, and spot), is used. Inception V3 achieved 93.8% accuracy, while YOLOv8 outperformed it with 95.4% accuracy, a mAP of 78.6%, and precision, recall, and F1-scores of 89%, 88%, and 89%, respectively. With a compact size of 12 MB and a rapid inference time of 10 ms per image, YOLOv8 is highly suitable for real-time applications. These findings highlight YOLOv8's potential to improve agricultural productivity and food security through precise and efficient disease detection.
Performance Analysis and Optimization of a Microstrip Parallel Coupled Line Bandpass Filter for C-Band Satellite Receiver Applications Moe Myint Aung; Hla, Tin Tin
The Indonesian Journal of Computer Science Vol. 14 No. 1 (2025): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i1.4751

Abstract

The design and optimization of a microstrip parallel coupled line bandpass filter (BPF) for C-band satellite receiver applications are the main focus of this work. Various filter orders (third order to seventh order) were analyzed and compared based on key performance parameters, including insertion loss, return loss, bandwidth, and shape factor. The optimized fifth order filter was selected as the most suitable due to its low insertion loss of -0.625 dB, deep return loss of -31.443 dB, and adequate bandwidth of 565 MHz, ensuring efficient signal transmission with minimal reflection. The calculated shape factor of 1.7 indicates a sharp roll-off, enabling effective rejection of out-of-band interference while maintaining a well-defined passband. The proposed design achieves a balance between performance, complexity, and real-world applicability, making it a reliable and efficient solution for C-band satellite communication systems.
Model Hybrid COBIT 2019 dan PLS-SEM untuk Mengukur Determinan Efektifitas Informasi Tata Kelola TI Bansoma, Meinahen; Hanna M. Baun
The Indonesian Journal of Computer Science Vol. 14 No. 2 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i2.4754

Abstract

In terms of improving the quality and service of the University through the role of tech-nology, it is important to measure the maturity of IT Governance management. However, there are still many organizations with IT governance management that are not aligned with the goals of the University. Therefore, this study will measure the influence of in-formation determinants on innovation and performance to assess the maturity of IT man-agement. This research was conducted at Citra Bangsa University (UCB) Kupang, East Nusa Tenggara. The PLS-SEM model is used to measure the effect of innovation and per-formance, while the IT maturity analysis will use the 2019 COBIT model. In this study, to get responses from respondents, questionnaires were distribut-ed containing hypotheses about the influence of information determi-nants on innovation and performance. As a re-sult, 98 questionnaires with complete criteria were collected, these responses were then ana-lyzed using PLS-SEM. After analyzing the influence of information determinants, then proceed to assess the maturity of IT management in the present. The results show that APO04 and BAI11 get an average gap score at level 1 with values from the DSS01, BAI04, APO11, APO12, APO02 processes at levels 0 and 1. This shows that IT manage-ment still needs improvement in order to create harmony between management IT with the University's Goals, Vision, Mission and strate-gy.
Design Of Enterprise Architecture Of FEAF Standards On The Academic Information System Based On Website Fahmi, Irwan
The Indonesian Journal of Computer Science Vol. 14 No. 2 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i2.4758

Abstract

Academic Information System (SIAKAD) is a crucial element in supporting efficiency and effectiveness academic data management in educational institutions. Research This aims To analyze and apply Federal Enterprise Architecture Framework (FEAF) standards on designing Information Systems Academics at MA Bumi The Kingdom by using a website-based platform. FEAF was chosen as framework Work To ensure integration, interoperability, and sustainability of SIAKAD. Methods study This involves analysis of user needs, business process identification, and data modeling. The implementation of FEAF is integrated in stage design system, combining aspects such as business, data, applications, and technology architecture. The results of the study show that Application of FEAF in Information Systems MA Bumi Academic The Kingdom gives clarity supporting structure planning, development and maintenance of systems in a more systematic way. Implementation website based provides greater accessibility good and more interactive user experience. The application of FEAF also allows more good alignment between business needs and information technology, as well as increasing the system's adaptation ability to change environmental education. Success project This shows that implementation of the FEAF standard can become a strong foundation for designing Information Systems Sustainable and responsive academics in the formal education environment such as MA Bumi Persada. This research makes an important contribution in developing information systems that can increase efficiency and quality academic data management in educational institutions.
Enhancing Data Security: A Hybrid Approach of AI-Driven Steganography and Encryption Fadhil, Ammar
The Indonesian Journal of Computer Science Vol. 14 No. 2 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i2.4759

Abstract

In the era of technological development and the Internet, the volume of data transmitted in digital networks is constantly increasing. Ensuring data security has become one of the important challenges in our time. Encryption processes protect data security, but they are often exposed and attract attention. Steganography models are a technique that hides sensitive data but lacks cryptographic protection. The study proposes a hybrid security approach that combines encryption strength and data hiding to be secure against digital attacks. The proposed method takes advantage of one of the artificial intelligence techniques represented by deep learning, which depends on dynamically changing weights during encryption and embedding in the image. This allows us to obtain strong security and high imperceptibility. In the proposed approach, security is enhanced through several layers, the first of which is dynamic changes to generate random numbers and variable encryption as a result of the dynamics of the encryption key and finally hiding the data in a way that cannot be detected. The experimental results showed the merit of the proposed approach through the strength of the results such as the uniformity of the histogram peaks and high entropy = 8 and high imperceptibility represented by BSNR = 91dB. Our research contributes to enhancing data security and countering cyber attacks by exploiting artificial intelligence techniques. Future work has been proposed that opens up horizons for studies using other artificial intelligence techniques such as machine learning and improving real-time data processing in the digital network.
Leveraging Large Language Models for Multi-Domain Malware and Vulnerability Detection Magyar, Attila
The Indonesian Journal of Computer Science Vol. 14 No. 2 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i2.4769

Abstract

This study presents the application of deep learning methodologies, particularly leveraging GPT-2, to enhance various aspects of cybersecurity, including source code vulnerability detection, malware detection, and mobile malware security. The first part introduces a method for identifying security vulnerabilities in C/C++ source code by fine-tuning a GPT-2 model on diverse open-source code datasets. The results show that the GPT-2 model, using default tokenizers and encoders, performs comparably to other deep learning methods in vulnerability detection. The second part explores the use of GPT-2 for improving malware detection, proposing a novel approach that classifies malware through opcode snippets and textual features. Fine-tuning GPT-2 on a diverse dataset of malware and benign software demonstrates enhanced detection accuracy and reduced false positives. Lastly, the study investigates mobile malware detection, proposing a framework that combines static and dynamic analysis using deep learning to detect unseen malware variants. The framework is evaluated on a comprehensive dataset, showing improved accuracy and fewer false positives than traditional methods. This integrated approach highlights the potential of deep learning, particularly GPT-2, to address the challenges of modern cybersecurity, offering robust solutions across multiple domains.
Electrical Characteristics of PN Junction Structure for GaAs, InP and InSb based III-V Compounds Tin Tin Hla; Kyawt Khin; Hnin Ngwe Yee Pwint
The Indonesian Journal of Computer Science Vol. 14 No. 2 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i2.4771

Abstract

The electrical properties of the pn junction structure for GaAs, InP and InSb based III-V compounds using the numerical equation are provided by a computer-aided simulation method. The band model predicts the electrical properties of III-V compound semiconductors. The analytical description of the immobile space charge layer (ISPL) related to immobile charge concentration, the amount of electric field intensity and the barrier potential height under unbiased, forward-biased and reverse-biased conditions has been investigated. And then the specific explanation of electron and hole distributions in the bulk region due to the majority carrier injection under forward biasing has been evaluated by using boundary conditions. The J-V characteristics of Group III-V compounds are observed using mathematical computation based on diffusion current density and recombination current density of the pn junction structure.
Performance Evaluation of Dual Active Bridge DC-DC Boost Converter Khin San Myint; May Su Hlaing; Tin Tin Hla
The Indonesian Journal of Computer Science Vol. 14 No. 2 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i2.4773

Abstract

This research presents a detailed performance analysis of a Dual Active Bridge (DAB) DC-DC converter, focusing on the impact of MOSFET on-resistance (Rds(on)) on converter efficiency and output characteristics. Using MATLAB simulink model, this work implements proportional-integral (PI) controllers for improved output current and voltage stability and pulse width modulation (PWM) for voltage regulation. To assess their impact on converter losses and overall performance, simulations are run using different MOSFET Rds(on) values. The results highlight the relationship between Rds(on) and efficiency, demonstrating how lower MOSFET on-resistance leads to lower losses and better converter performance. To measure the improvements, losses are computed, and the output voltage and current under various Rds(on) situations are displayed. This study offers insightful information for improving the performance and efficiency of power converters. Additionally, it compares the performance of PWM alone and PWM and PI together. The effect of frequency on the converter is then also explained.
Critical Success Factors for the Implementation of an EDRMS in the Government of The Gambia: A PMBOK 7th Edition Approach Jallow, Fatoumatta Binta; Raharjo, Teguh; Trisnawaty, Ni Wayan
The Indonesian Journal of Computer Science Vol. 14 No. 2 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i2.4775

Abstract

The successful implementation of an Electronic Document and Records Management System (EDRMS) in the public sector faces significant challenges, particularly in developing countries like The Gambia. Poor system integration, data security risks, resistance to change, and lack of leadership support hinder adoption. This study applies the PMBOK 7th Edition framework to identify critical success factors (CSFs) for EDRMS implementation. Using a Systematic Literature Review (SLR), this research analyzes key factors, including system compatibility, cybersecurity, legal compliance, and stakeholder engagement. Findings indicate that a structured project management approach enhances adoption by ensuring effective integration, risk mitigation, and user acceptance. The study provides practical recommendations for policymakers and IT managers to optimize digital record management strategies. Future research should explore case studies and emerging technologies such as AI and blockchain to strengthen EDRMS adoption.
Implementation of Business Process Improvement (BPI) to Enhance Stock Opname and Purchasing Efficiency at XYZ Coffee Nur Azizyah Putri Dewita; Adam Hermawan; Rangga Gelar Guntara
The Indonesian Journal of Computer Science Vol. 14 No. 2 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i2.4776

Abstract

This study discusses the implementation of Business Process Improvement (BPI) through the adoption of a Point of Sale (POS) system and organizational restructuring to optimize stock-taking and purchasing processes at Soulja Coffee. The research employs the DMAIC (Define, Measure, Analyze, Improve, Control) approach to analyze and improve key business processes. The findings indicate that the purchasing process time decreased by up to 70%, from 4 hours 25 minutes – 5 hours 30 minutes to 1 hour 16 minutes – 2 hours 22 minutes per week. The Cost of Goods Sold (COGS) decreased from 54.9% in November to 38.2% in January, while Operating Expenses (OPEX) dropped from 34.6% to 16.4%, reflecting significant cost efficiency. The POS system enables real-time stock monitoring, reduces manual errors, and accelerates the procurement process. Organizational restructuring, including the establishment of a Finance & Purchasing division, shortened purchase approval times from 10 minutes to 3 minutes, improving responsiveness and transparency. Thus, the implementation of BPI at Soulja Coffee has proven effective in enhancing time efficiency, reducing operational costs, and supporting sustainable business growth.

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