cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Tri A. Sundara
Contact Email
tri.sundara@stmikindonesia.ac.id
Phone
+628116606456
Journal Mail Official
ijcs@stmikindonesia.ac.id
Editorial Address
Jalan Khatib Sulaiman Dalam 1, Padang, Indonesia
Location
Kota padang,
Sumatera barat
INDONESIA
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 1,106 Documents
 107   108   109   110   111 
Why Generative AI Will Not Replace University Lecturers: A Human-Centred Perspective Murimo Bethel Mutanga; Revesai, Zvinodashe; Samuel Chikasha; Tarirai Chani
The Indonesian Journal of Computer Science Vol. 14 No. 6 (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.v14i6.5037

Abstract

The integration of artificial intelligence (AI) into higher education has prompted widespread speculation about the potential obsolescence of university lecturers. While AI systems demonstrate impressive capabilities in content delivery, assessment, and personalisation, this research critically examines the assumption that they can replace human educators. This issue is particularly complex, given that effective higher education involves not only the transmission of information but also the development of cognitive, emotional, ethical, and social aspects. Despite advances in AI technologies, current discourse often neglects the irreplaceable human functions that underpin transformative education. Addressing this gap, the study adopts a human-centred framework to investigate essential lecturer capabilities, limitations of AI systems, and the design of optimal human-AI collaboration. Using qualitative methods, including stakeholder interviews and comparative institutional analysis, the findings reveal ten educational domains where human capabilities remain indispensable, from emotional support and ethical mentorship to adaptive teaching and research integration. AI excels in routine, scalable tasks, yet lacks empathy, moral agency, and contextual understanding. Consequently, this research proposes a collaborative model in which AI enhances rather than replaces lecturers, thereby supporting educational quality and student development. The findings have significant implications for institutional policy, faculty development, and the ethical integration of AI in education, affirming the enduring and transformative role of human educators in the digital age.
Hybrid-Based Multi-Object Tracking for Football Sport Htun, Zin Mar; Theingi Myint
The Indonesian Journal of Computer Science Vol. 14 No. 6 (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.v14i6.5039

Abstract

Tracking is now popular in real world. Precise tracking of objects in real-time videos is a challenging task. With billions of fans, football is a rapidly expanding sport that has proven essential to many nations and their citizens in particular. None of the numerous great target tracking algorithms have surfaced in recent years primarily deep learning and correlation filtering that can track players in soccer game videos with high accuracy. In this paper, the proposed system is used You Only Look Once version 8-nano (YOLOv8n) for Multi-Object Detection (MOD) to get higher detection accuracy results. Moreover, this system is based on the hybrid method for tracking. The hybrid method is combined with stacked Long Short Term Memory (LSTM) and Fairness of Detection and Re-identification in Multipe Object Tracking (FairMOT). The experimental analysis shows that the proposed system is efficiently and better accuacy because the best detection results with YOLOv8n is 93% for precision, 91% for recall and 92% for mAP(50) with own dataset. After using the proposed system, the average of the Multi Object Tracking Accuracy (MOTA) is 80 % at IoU-Threshold 0.5, the average of the Multi Object Tracking Precision (MOTP) is 89% at IoU-Threshold 0.8 and the average of the final mAP is 96% at IoU- Threshold 0.5 by using hybrid method for tracking.
The Rise of Quantum Computing and Its Impact on Cybersecurity Vareta, Passmore; Muzenda, Hillary; Nyamupaguma, Tanyaradzwa; Dube, Yangekile; Ndlovu, Belinda
The Indonesian Journal of Computer Science Vol. 14 No. 6 (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.v14i6.5040

Abstract

As technology continues to evolve, cybersecurity measures tend to be vulnerable to the computational power of quantum computers. These computers perform calculations faster than classical computers. This ability to solve tasks within polynomial time threatens current cybersecurity practices through Shor's and Grover's algorithms. Classical computers rely on mathematical hardness assumptions and are vulnerable to quantum attacks. This paper scrutinizes the double effects of quantum computing on cybersecurity and its ability to support post-quantum resistant technologies. A systematic literature review (SLR) of 24 peer-reviewed articles (2021-2025) obtained from IEEE Xplore, SpringerLink, ACM, and Google Scholar was conducted, and the results identified three integral themes. Firstly, 80% of quantum computing threats studies analysed prove that Shor's algorithm can efficiently factorise large integers, rendering Rivest Shamir Alderman and Elliptic Curve Cryptography obsolete. Secondly, 65% of the studies show that Post-Quantum Cryptography (PQC) offers quantum-resilience in the foreseeable future. In comparison, 25% of Quantum Key Distribution (QKD) papers show practical barriers like signal loss and standardization delays. 15% of studies reveal the urgent need for regulatory and ethical concerns. Key results highlight the urgent need for hybrid cryptographic systems that combine quantum key distribution and post-quantum cryptography, as proposed by 40% of recent publications. 46% of studies show that Europe leads quantum cybersecurity research, driven by collaborative policy efforts. This study suggests practical recommendations for accelerated adoption of NIST-standardised PQC algorithms, investment in QKD infrastructure for critical sectors, and multidisciplinary collaboration to address technical, legal, and ethical gaps. This paper provides a roadmap for mitigating quantum threats and leveraging quantum technologies to transform cybersecurity resilience in the digital era.
Prototipe Sistem Keamanan Kunci Pintu Rumah Otomatis Dengan Pengenalan Wajah Berbasis IoT Niam Tamami; Achmad Rizky Ramadhani; Hary Oktavianto; Rifqi Nabila Zufar
The Indonesian Journal of Computer Science Vol. 14 No. 6 (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.v14i6.4998

Abstract

Dalam era digital yang semakin berkembang, teknologi telah mengubah sistem keamanan dengan menggantikan kunci pintu konvensional dengan kunci pintu pintar yang canggih. Teknologi seperti pengenalan wajah, sidik jari, dan sensor gerak memberikan tingkat keamanan yang lebih tinggi dibandingkan dengan kunci tradisional. Kunci pintu konvensional rentan terhadap risiko pembobolan, kehilangan, atau duplikasi oleh pelaku kejahatan. Sebagai solusi, penulis ingin menciptakan kunci pintu pintar yang dapat membuka pintu dengan pengenalan wajah, Personal Identification Number (PIN), dan melalui Telegram bot. Pengenalan wajah pada kunci pintu pintar memastikan bahwa hanya pemilik atau orang yang terdaftar yang dapat membuka pintu. Fitur tambahan berupa penggunaan PIN memberikan lapisan keamanan ekstra. Jika PIN yang salah dimasukkan sebanyak tiga kali, alarm akan berbunyi untuk memberikan peringatan. Selain itu, jika sistem pengenalan wajah tidak dapat mengenali wajah yang sedang dipindai, kamera akan mengambil gambar dan mengirimkannya ke Telegram bot di smartphone pengguna. Dengan penerapan kunci pintu pintar ini, diharapkan keamanan dan kemudahan akses yang lebih baik dibandingkan dengan kunci pintu konvensional. Hasil pengujian menunjukkan bahwa sistem ini dapat bekerja dengan akurasi pengenalan wajah sebesar 79% dan respon alarm bekerja secara real-time melalui integrasi Telegram bot.
Digital Forensic-Ready Voting Model Muyambo, Edmore; Baror, Stacey; Makura, Sheunesu
The Indonesian Journal of Computer Science Vol. 14 No. 6 (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.v14i6.5019

Abstract

The increasing digitalization of elections through internet-based voting (e-voting) systems introduces both opportunities for enhanced accessibility and threats to electoral integrity. Existing electronic voting systems often lack built-in forensic capabilities necessary to detect, preserve, and prove incidents of vote rigging or cyber manipulation. This paper proposes a Digital Forensic-Ready Voting Model (DFRVM) that integrates forensic-by-design principles, blockchain technology, and legal admissibility frameworks to ensure accountability, transparency, and verifiability in the electoral process. The model emphasizes proactive evidence collection, real-time monitoring, and tamper-evident audit trails to strengthen post-election dispute resolution.
An Integrated Feedforward Neural Network for Categorical Prediction of Greenhouse Tomato Yield under Nigeria’s Climatic, Soil, and Agronomic Parameters James, Idara; Ibanga, Ubon; Udoeka, Ifreke; Asuquo, Doris
The Indonesian Journal of Computer Science Vol. 14 No. 6 (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.v14i6.5029

Abstract

Accurate prediction of tomato yield in greenhouse environments is essential for sustainable agriculture, particularly under Nigeria’s unique climatic, soil, and agronomic conditions. This study presents an integrated Feedforward Neural Network (FNN) model for the categorical prediction of greenhouse tomato yield, classified into low, medium, and high. The model integrates heterogeneous datasets encompassing climatic, soil, and agronomic features through a unified network architecture, data preprocessing, regularization, and cross-validation, which are employed to enhance generalization and predictive accuracy. The FNN, chosen for its simplicity and computational efficiency, achieved an overall accuracy of 93%, with strong precision, recall, and F1-scores across yield categories. These results highlight the potential of the proposed model for data-driven yield prediction and sustainable greenhouse management in Nigeria.
Peningkatan Akurasi dan Efisiensi Operasional Sistem Reservasi dengan Metode RAD di Wilayah Yogyakarta Pratama, Andre; Sutarman
The Indonesian Journal of Computer Science Vol. 14 No. 6 (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.v14i6.5042

Abstract

The event venue rental system in the Yogyakarta region, which still relies on manual processes, creates operational inefficiencies and information limitations for customers. To address this issue, this research develops an Online Event Venue Booking System using the Rapid Application Development (RAD) approach. The development is validated using the Mixed Methods approach. This system successfully implemented the main functions of place exploration and place owner management. The effective implementation of this web-based system critically addresses issues of inefficiency and recording errors through automation. Overall, the resulting system is able to optimize operational management efficiency and significantly improve the ease of the ordering process for customers.
Next-Generation Smart Irrigation: A Fully Autonomous LoRa-Enabled Valve Controller with Multi-Year Battery Life Haryono
The Indonesian Journal of Computer Science Vol. 14 No. 6 (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.v14i6.5043

Abstract

Jagorawi Golf & Country Club currently relies on manual operation of its irrigation valves, a process that is labor-intensive and often inefficient. To address this, we introduce an automated valve-control system integrating LoRa long-range communication, motorized valves, and a 30,000 mAh battery designed to support remote operation through a smartphone or web interface. The system enables both manual remote control and fully automated scheduling while maintaining exceptional energy efficiency, achieving up to about 2 year of continuous operation without recharging. Power modeling incorporates two activity cycles: a 2-second cycle every 60 seconds drawing 50 mA for 0.8 s and 10 mA for the remaining time, and a daily 5-minute cycle consuming 1000 mA for the first second, decreasing linearly to 25 mA over the next 60 seconds, and stabilizing at 80 mA thereafter. Outside these operations, the device consumes only 1 mA in passive mode. The combination of low-power LoRa communication, optimized actuation profiles, and deep-sleep microcontroller strategies significantly reduces energy demands while improving reliability, consistency, and water-management efficiency over traditional human-operated systems.
Concurrency Control in Distributed Databases: A Systematic Review Lloyd Moluma, Tshidiso; Esiefarienrhe, Bukohwo Michael
The Indonesian Journal of Computer Science Vol. 14 No. 6 (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.v14i6.5045

Abstract

This paper provides a comprehensive review of concurrency control techniques used in distributed database systems. It focuses on recent developments by examining articles and other academic documents published between 2016 and 2025. Using PRISMA 2020 guidelines, 197 scientific and academic studies were screened across major databases, and 10 articles met the final criteria for detailed analysis. The review classifies concurrency control approaches into four areas: types of locks, performance, accuracy, and efficiency. Each classification is then evaluated based on throughput, latency, detection accuracy, scalability, and technique applied to enhance these metrics. The findings demonstrate that traditional algorithms maintain consistent performance in general conditions but often struggle under heavy contention. Contrastingly, multi-version concurrency control and optimistic techniques improve scalability but introduce high abortion rates. Emerging adaptive techniques that depend on workload profiling show increasing promises for dynamic environments. The review highlights these trends and outlines future research direction for resilient distributed systems.
A Neural network model for the prediction of cattle prices in South African livestock actions Kgopa, Alfred
The Indonesian Journal of Computer Science Vol. 14 No. 6 (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.v14i6.5046

Abstract

Abstract – This study developed a neural network model for predicting cattle prices in South African livestock auctions based on breed (B), weight (W), time/season (T) and price (P) variables. Using the online auction dataset from 2023 - 2025, the model analyzed nonlinear relationships influencing price fluctuations, producing realistic per-cattle predictions ranging between ZAR 7,000 - ZAR 17,500, with projected increases up to ZAR 22,000 in future weeks. The results demonstrate the model’s capacity to capture market dynamics shaped by breed attributes, seasonal demand fluctuations, and animal mass. The results illustrate that artificial intelligence-led techniques, including neural networks, can substantially improve market prediction accuracy, enhance profitability, and inform strategic decisions in the livestock sector. Furthermore, this study provides a foundation for future research to expand predictive modelling beyond cattle, contributing to the development of a comprehensive livestock price prediction system that integrates multiple animal types under a unified intelligent forecasting framework.

Page 110 of 111 | Total Record : 1106

 107   108   109   110   111 

Filter by Year

2022 2025


Reset
Filter By Issues
All Issue Vol. 14 No. 6 (2025): The Indonesian Journal of Computer Science Vol. 14 No. 5 (2025): The Indonesian Journal of Computer Science Vol. 14 No. 4 (2025): The Indonesian Journal of Computer Science Vol. 14 No. 3 (2025): The Indonesian Journal of Computer Science Vol. 14 No. 2 (2025): The Indonesian Journal of Computer Science Vol. 14 No. 1 (2025): The Indonesian Journal of Computer Science (IJCS) Vol. 13 No. 6 (2024): The Indonesian Journal of Computer Science (IJCS) Vol. 13 No. 5 (2024): The Indonesian Journal of Computer Science (IJCS) Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science (IJCS) Vol. 13 No. 3 (2024): The Indonesian Journal of Computer Science (IJCS) Vol. 13 No. 2 (2024): The Indonesian Journal of Computer Science (IJCS) Vol. 13 No. 1 (2024): The Indonesian Journal of Computer Science (IJCS) Vol. 12 No. 6 (2023): The Indonesian Journal of Computer Science (IJCS) Vol. 12 No. 5 (2023): The Indonesian Journal of Computer Science (IJCS) Vol. 12 No. 4 (2023): The Indonesian Journal of Computer Science (IJCS) Vol. 12 No. 3 (2023): The Indonesian Journal of Computer Science Vol. 12 No. 2 (2023): The Indonesian Journal of Computer Science Vol. 12 No. 1 (2023): The Indonesian Journal of Computer Science Vol. 11 No. 3 (2022): The Indonesian Journal of Computer Science Vol. 11 No. 2 (2022): The Indonesian Journal of Computer Science Vol. 11 No. 1 (2022): The Indonesian Journal of Computer Science More Issue