Informatics and Software Engineering

The Perception of Senior High School Students Towards E-Learning in Bolgatanga Municipality, Ghana

2025-01-26T09:16:25+07:00

Electronic learning (e-learning) is a comparatively new phenomenon in Ghana and students are grappling with the idea of adopting e-learning. The Technology Acceptance Model (TAM) was used in this study to investigate the perception of senior high school students toward e-learning. The study employed the quantitative research approach. The probability sampling method was used to select a total of three hundred and sixty (360) students from a sample frame to constitute the sample size for the study. A closed-ended structured questionnaire was used to gather data on students' perceived usefulness of e-learning and students' perceived ease of use of e-learning which was then analyzed using SPSS. The results revealed student’s strong agreement that, attitude to using an e-learning system is based on student’s perception of ease of use (POEU). Similarly, the study showed that students strongly agreed that students’ perception of usefulness (PU) of e-learning systems forecasts user attitudes toward using an e-learning system.

LRT System Security Analysis: Threats and Solutions for Implementation in Indonesia

2025-02-27T07:48:50+07:00

The security of the Light Rail Transit (LRT) system is a significant concern as its utilization continues to grow in Indonesia. As a viable solution to urban congestion, the LRT encounters various challenges, including cyberattacks and technical issues that could disrupt operations and jeopardize passenger safety. This study aims to analyze these threats and propose solutions using the ISO-31000:2018 framework. The research employs a Systematic Literature Review (SLR) methodology to assess risks based on their likelihood and potential impact. The findings indicate that the primary threats include phishing attacks, ransomware, and signal system failures. However, this study has limitations, as it is based exclusively on secondary data, which may not fully reflect local conditions. The originality of this research lies in its application of ISO-31000:2018 within the local context and its provision of practical recommendations for operators and policymakers. Moreover, it paves the way for future studies to conduct more comprehensive, field-based research.

Information System for the Development of Web-Based Fixed Asset Modules at PT. Prima Solusi Computindo

2025-03-30T09:13:18+07:00

Prima Solusi Computindo (Radsoft) faces challenges in managing fixed assets, resulting in inefficiencies due to manual and non-integrated record-keeping processes. This study aims to design and implement a web-based information system for fixed asset management to enhance efficiency and accuracy. This system was developed using HTML, CSS, Javascript, SQL database, and the C# framework. The research utilizes the Waterfall development model, encompassing requirements analysis, system design, implementation, and testing phases. The results indicate that the developed system effectively integrates asset management processes, including record-keeping, depreciation tracking, and reporting. This integration simplifies the management team's decision-making regarding asset utilization. Additionally, the web-based system enables real-time access across departments, improving transparency and data accuracy. As a recommendation, the company should provide training for system users to maximize the features available. Future developments include integrating the system with other modules, such as accounting and inventory, to enhance its overall functionality.

Information System for Submitting Payment for Operational Costs of PT Selamat Makmur in Tangerang

2025-05-26T16:51:53+07:00

Challenges arise from the manual submission of operational cost payments using Microsoft Excel. This manual process is susceptible to issues in payment submissions, complicates the tracking of approved payments, and lacks automated payment reminders. The author utilizes two approaches: the Data Collection method and the Software Development method. The Data Collection method entails conducting observations, interviews, and literature reviews. In regards to software development, the waterfall model is highlighted for its straightforward, sequential implementation. By adopting this system, PT. Selamat Makmur aims to streamline the submission and payment of operational costs, reduce errors, and improve transparency and accuracy throughout the company's operational cost management. This system is also vital for ensuring the efficient functioning of the cosmetic production process and supporting the company's growth in a competitive market.

Unified Predictive Modeling: Enhancing Accuracy with DBNs, Fuzzy ARTMAP, and SVMs

2025-06-17T13:25:59+07:00

Amid the global surge in artificial intelligence, the field of machine learning is advancing rapidly, and selecting the most suitable algorithm for prediction tasks remains a crucial challenge. This paper introduces a novel ensemble model that combines three machine learning algorithms—Deep Belief Networks (DBNs), Fuzzy ARTMAP, and Support Vector Machines (SVMs)—to enhance predictive performance. Each machine learning model possesses unique strengths, and by integrating these models, it is possible to overcome individual model limitations and achieve more accurate and reliable predictions. DBNs excel at learning hierarchical representations and capturing complex patterns, Fuzzy ARTMAP is proficient in handling imprecise and ambiguous data, and SVMs are renowned for their robustness in high-dimensional spaces. Thus, the integrated framework leverages the complementary strengths of each model while mitigating their weaknesses. In this study, the proposed ensemble model's predictive power was validated through experiments on image data collected from actual construction sites for construction automation research. The prediction performance of the proposed ensemble model was evaluated and compared with that of individual models such as DBNs, Fuzzy ARTMAP, and SVMs, demonstrating its superiority. The experimental results showed that the proposed model outperformed each individual algorithm in terms of prediction accuracy, clearly illustrating the effectiveness of the ensemble approach.