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International Journal of Informatics and Communication Technology (IJ-ICT)
Published by Institute of Advanced Engineering and Science
ISSN : 22528776     EISSN : 27222616     DOI : -
Core Subject : Science,
Computer Science & IT
International Journal of Informatics and Communication Technology (IJ-ICT) is a common platform for publishing quality research paper as well as other intellectual outputs. This Journal is published by Institute of Advanced Engineering and Science (IAES) whose aims is to promote the dissemination of scientific knowledge and technology on the Information and Communication Technology areas, in front of international audience of scientific community, to encourage the progress and innovation of the technology for human life and also to be a best platform for proliferation of ideas and thought for all scientists, regardless of their locations or nationalities. The journal covers all areas of Informatics and Communication Technology (ICT) focuses on integrating hardware and software solutions for the storage, retrieval, sharing and manipulation management, analysis, visualization, interpretation and it applications for human services programs and practices, publishing refereed original research articles and technical notes. It is designed to serve researchers, developers, managers, strategic planners, graduate students and others interested in state-of-the art research activities in ICT.
Arjuna Subject : -
Articles 25 Documents
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Search results for , issue "Vol 13, No 3: December 2024" : 25 Documents clear
Security analysis and evaluation of mobile banking applications in Nigeria Imam, Abdullahi Yahya; Usman, Hamisu Ibrahim; Abba, Abdulrazaq
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 13, No 3: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v13i3.pp354-361

Abstract

Rapid fintech adoption across the world is so ubiquitous. To facilitate more adoption in Nigeria, recently the Central Bank of Nigeria (CBN) introduced several policies that support cashless banking. Nowadays, Nigerian banks users could perform most of their daily transactions from any desired location using mobile banking applications. In the literature, there are insufficient studies that comprehensively evaluate the security strength or risks of these applications. Generally, insecure mobile banking applications could lead to financial fraud, violations of privacy, identity theft and eroded user confidence. Considering the situation, there is need to conduct research which comprehensively assess security of the applications. Consequently, in this paper we analyzed and evaluated the security of identified popular mobile banking applications in Nigeria. We conducted the analysis work using automated and manual static analysis methods. Then, we evaluated the security of the applications using multi-criteria decision-making technique. Our results revealed that most of the applications have several security challenges in form of vulnerabilities and insecure coding practices. Hence, our findings have shown the applications need further improvements for better security and safety.
Application of artificial intelligence in modern public administration: new opportunities and challenges Shvets, Kateryna; Onyshchenko, Andrii; Kudin, Volodymyr; Korchak, Nataliia; Ivanii, Olena
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 13, No 3: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v13i3.pp509-518

Abstract

Humanity is entering a technological era of convergence of artificial intelligence (AI), cyber and biotechnology, robotics and additive manufacturing, which creates unprecedented opportunities and risks on a global scale. AI has quickly become an important topic for global development. Not only the corporate sector but also governments are interested in creating a favourable environment for these technologies. This article explores the role and impact of AI in the context of modern public administration. The authors assess how AI opens up new opportunities for improving public services and the efficiency of management processes. Particular emphasis is placed on the ability of AI to analyse large amounts of data to inform decision-making, improve interaction with citizens, and optimise internal management processes. Potential challenges are also discussed, including ethical issues, privacy concerns, and automation risks. The article proposes strategies for a balanced implementation of AI in public administration, with a special emphasis on the need to develop skills and competencies among civil servants to use these technologies effectively.
Optimizing warehouse management system with blockchain and machine learning predictive data analytics Hande, Kapil N.; Chandak, Manoj B.
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 13, No 3: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v13i3.pp362-369

Abstract

Blockchain technology is proving to be a disruptive technology in many areas of supply chain, manufacturing, medical, agriculture, and so on. Warehouses are an inevitable part of the supply chain. Issues like space optimization, route optimization, quick item pick-up, demand forecasting, and transaction management are of importance to address in warehouse management systems (WMS). Traditional database systems have limitations of interoperability among different entities involved in warehouses. This paper presents an innovative application of blockchain technology and machine learning (ML) to build a smart warehouse management system in Web3 (SWMW3). We developed a decentralized application (DApp) using Web3.0 principles, integrating ReactJS for the frontend, express for the backend, and blockchain through smart contracts. This integration enhances security and transparency by storing WMS operational data in the blockchain and automating payments and verifications through smart contracts. Additionally, we implemented a ML model for predicting the total time from order receipt to delivery, leveraging historical data to optimize workflow, reduce delays, and improve overall efficiency. This combination of blockchain for secure transactions and ML for predictive analytics generates a robust, efficient, and optimized management system for the warehouse.
Transformer-based abstractive indonesian text summarization Aurelia, Miracle; Monica, Sheila; Girsang, Abba Suganda
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 13, No 3: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v13i3.pp388-399

Abstract

The volume of data created, captured, copied, and consumed worldwide has increased from 2 zettabytes in 2010 to over 97 zettabytes in 2020, with an estimation of 181 zettabytes in 2025. Automatic text summarization (ATS) will ease giving points of information and will increase efficiency at the time consumed to understand the information. Therefore, improving ATS performance in summarizing news articles is the goal of this paper. This work will fine-tune the BART model using IndoSum, Liputan6, and Liputan6 augmented dataset for abstractive summarization. Data augmentation for Liputan6 will be augmented with the ChatGPT method. This work will also use r ecall-oriented understudy of gisting evaluation (ROUGE) as an evaluation metric. The data augmentation with ChatGPT used 10% of the clean news article from the Liputan6 training dataset and ChatGPT generated the abstractive summary based on that input, culminating in over 36 thousand data for the model’s fine-tuning. BART model that was finetuned using Indosum, Liputan6, and augmented Liputan6 dataset has the best ROUGE-2 score, outperforming ORACLE’s model although ORACLE still has the best ROUGE-1 and ROUGE-L score. This concludes that fine-tuning the BART model with multiple datasets will increase the performance of the model to do abstractive summarization tasks.
Implementing gamification in campus canteen using MDA framework: an overview Wibowo, Florentia Novena; Wang, Gunawan
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 13, No 3: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v13i3.pp422-427

Abstract

This study describes the creation of a mobile-based gamification design for an online canteen system. Long lunch queues make students feel uncomfortable ordering food in the canteen, although student comfort is very important. The increasing number of students causes long queues, resulting in significantly shorter lunch hours and causing discomfort for students. To address this issue, the campus might develop an online canteen using gamification. Gamification is a method that applies gaming knowledge to create experiences that encourage and engage people in non-game environment. Compared to traditional canteen systems, an online canteen that uses gamification can provide students with new experiences by offering attractive rewards, increasing motivation to order food and beverages online, and minimizing the perception of long lineups. Although this proposed design has not yet been tested, researchers believe it has practical applications.
Personalized learning model based on machine learning algorithms Jin, Zhang; Kamsin, Amirrudin
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 13, No 3: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v13i3.pp470-475

Abstract

Machine learning algorithms have been widely applied in the field of personalized learning within educational information technology. By leveraging big data analysis and data mining techniques, machine learning can help identify patterns and trends in students' learning behaviors, preferences, and performance. This information can then be used to tailor educational resources and experiences to meet the individual needs and unique characteristics of each learner. Machine learning has made great progress and achievements in the teaching process of universities, but there are also some shortcomings. Such as data dependence, over-fitting and under-fitting, explanatory problems, need a lot of computing resources, data bias, sensitive to outliers, cannot solve all problems, and the challenge of data privacy, through the analysis of machine learning algorithm model, efforts to find ways to expand the dimension of personalized learning classroom, meet the students in learning objectives, learning content, learning methods of the special characteristics and unique needs, to guide students to actively explore and research, obtain innovation and appropriate learning results.
Thermal imaging-based identification of facial features in noisy environment Mahajan, Palak; Abrol, Pawanesh; Lehana, Parveen Kumar
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 13, No 3: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v13i3.pp333-343

Abstract

Face identification is amongst the most efficacious and extensive applications in biometrics involving extraction and locating facial features. With identification being monotonous task attributable to reliance on parameters like varied cameras, fluctuating backgrounds, and exposure to the environment in which an individual is present. Thermal imaging is endeavoring to resolve the accuracy issue of apparent imaging, such as lighting and brightness intensity, among all biometric variables. This paper presents a study of thermal imaging and effective methods involved in the feature extraction process for facial features with thermal imaging under the influence of varied noise. A novel face dataset is created TID comprising 27 thermal images and its corresponding visual band image using Fluke 480 Ti Pro camera. The study analyses detection efficiency of six feature extraction techniques in visible and thermal bands in facial features identification. Also, the influence of noise in the thermal band within the region of interest using feature points FIN, FOUT has been estimated. Throughout TID dataset, ORB extraction technique has been able to identify strongest inlier features FIN to a maximum extent with detection around the nose, eyes, and mouth. Further, results indicate feature detection in thermal images being invariant to effect of noise for detecting facial features.
Utilizing deep learning algorithms for the resolution of partial differential equations Nouna, Soumaya; Nouna, Assia; Mansouri, Mohamed; Boujamaa, Achchab
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 13, No 3: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v13i3.pp370-379

Abstract

Partial differential equations (PDEs) are mathematical equations that are used to model physical phenomena around us, such as fluid dynamics, electrodynamics, general relativity, electrostatics, and diffusion. However, solving these equations can be challenging due to the problem known as the dimensionality curse, which makes classical numerical methods less effective. To solve this problem, we propose a deep learning approach called deep Galerkin algorithm (DGA). This technique involves training a neural network to approximate a solution by satisfying the difference operator, boundary conditions and an initial condition. DGA alleviates the curse of dimensionality through deep learning, a meshless approach, residue-based loss minimisation and efficient use of data. We will test this approach for the transport equation, the wave equation, the Sine-Gordon equation and the Klein-Gordon equation.
Blockout 2024: digital mobilization movements’ role in raising global awareness and fostering change Sutikno, Tole; Handayani, Lina
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 13, No 3: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v13i3.pp436-444

Abstract

Blockout 2024, a social media mobilization campaign, gained traction in response to celebrities’ and powerful people’s silence following the Met Gala in New York. Users who have remained silent or unconcerned about the humanitarian situation in Gaza are encouraged to block influencers’ accounts. The review seeks to investigate the Blockout 2024 phenomenon and how it affects celebrities’ social media. This review examines the impact of social media on power dynamics. On social media platforms such as TikTok, Instagram, and X, users have blocked the accounts (especially celebrities’ account) of those who have not responded to the humanitarian disaster. The movement emphasizes the importance of implementing change and making underrepresented voices heard in digital environments. While some celebrities have expressed their support, others have chosen to remain silent, which has resulted in criticism and lost followers. Finally, the Blockout 2024 campaign has gained significant traction on social media platforms such as X, Instagram, and TikTok. Users of social media are becoming more aware of their responsibility to denounce crimes and fight for justice, as evidenced by this group effort. The Blockout 2024 movement has highlighted the potential of digital mobilization to raise global awareness, address humanitarian crises, and hold influencers accountable.
Mastering information security through standard implementation Ahmedi, Basri; Ibrahimi, Aferdita
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 13, No 3: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v13i3.pp428-435

Abstract

This paper aims to enhance information security within an organization, considering the perennial concern for security in organizations utilizing ICT applications. Educational institutions also exhibit deficiencies in the domain of data security. The adoption of international organization for standardization (ISO) 27001-2013 served to pinpoint potential vulnerabilities and non-compliance with safety standards, aiming to minimize associated risks. Through this framework, an assessment of data security within public educational institutions in our country was conducted, focusing on a public university as a case study. Given the sensitive nature of this field, guidance is provided on identifying security-related issues based on ISO 27001 standards and on-ground situations. Surveys were employed, aligning with the required standards, to scan the prevailing situation. Data from surveys at public academic institution were collected and analyzed using the SPSS application. The findings underscore instances where security protocols can prevent or mitigate abuses, consequently enhancing the overall level of data security. Emphasizing education as a pivotal recommendation, this study advocates for educating personnel who handle sensitive data, derived from the application of these standards. This paper accounts for potential risks that could expose organizational weaknesses and thoroughly elucidates the steps and procedures undertaken in this approach, substantiated by illustrated examples.

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