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Mikailalsys Journal of Advanced Engineering International
Published by Lembaga Yasin Alsys
ISSN : 30468914     EISSN : 30469694     DOI : https://doi.org/10.58578/mjaei
Core Subject : Science, Engineering,
Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Electrical & Electronics Engineering Engineering Mechanical Engineering
Mikailalsys Journal of Advanced Engineering International [3046-8914 (Print) and 3046-9694 (Online)] is a double-blind peer-reviewed, and open-access journal dedicated to disseminating all information contributing to the understanding and development of the fields of engineering and technology across various disciplines. MJAEI aims to be a platform for researchers, scientists, and practitioners in various engineering disciplines to share their knowledge and innovative ideas, foster cross-disciplinary collaboration, and contribute to technological and scientific advancements. We invite authors from around the world to contribute to the advancement of engineering and technology fields. MJAEI publishes three editions a year in March, July and November.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 56 Documents
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Participation of Clients in the E-Banking Practices of Nepalese Commercial Banks Sah, Rajesh Kumar; Karn, Binod Lal; Sahani, Suresh Kumar
Mikailalsys Journal of Advanced Engineering International Vol 2 No 1 (2025): Mikailalsys Journal of Advanced Engineering International
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mjaei.v2i1.4526

Abstract

The aim of present research was to analyze the different e-banking services provided by Nepalese commercial bank in terms of customers’ participation. Nowadays, almost all commercial banks and financial intermediaries provide internet banking services for their customers in order to reduce cost and time. This study conducted to understand the different technological advancement used by the Nepalese commercial bank in their day-to-day operation. Data for this research came from both primary and secondary sources: responses from a questionnaire and many secondary sources. Present investigation was conducted utilizing a survey technique using a questionnaire as the data collecting tool. To get understanding of consumers' involvement in the Nepalese banking sector, structured sets of questions including Likert scale questions, yes/no questions, multiple choice questions were asked. According to the findings of this study, decision-makers should take into consideration the importance of centering their attention on the alertness, and faith of clients. This can be accomplished by enhancing safety measures, implementing proper e-legislation, and offering electronic bills or assurance for each and every transaction. The ultimate goal is to instill a greater sense of confidence in those who use such services and to encourage a culture of internet banking usage throughout Nepal. The findings of this study indicate that both the environment in which the application for online banking is used and the program itself are in need of further enhancement. The bank should always place a strong emphasis on encouraging consumer participation in the use of online banking services, rather than only focusing on the implementation of latest technological advancements.
Intelligent Incident Response Systems Using Machine Learning Joseph, Jennifer E; Aleke, Ngozi Tracy; Onyeanisi, Onyinyechukwu Prisca
Mikailalsys Journal of Advanced Engineering International Vol 2 No 1 (2025): Mikailalsys Journal of Advanced Engineering International
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mjaei.v2i1.4540

Abstract

The increasing complexity and volume of cyber threats have placed significant pressure on traditional incident response (IR) systems, necessitating the adoption of more advanced technologies to detect, analyze, and mitigate attacks efficiently. One such technology is machine learning (ML), which offers the potential to transform incident response by automating threat detection, prioritizing incidents, and dynamically adjusting responses based on evolving attack patterns. This paper explores the integration of machine learning into intelligent incident response systems, focusing on its applications, benefits, and challenges. Through an in-depth examination of machine learning techniques—such as supervised learning, unsupervised learning, deep learning, and reinforcement learning—we highlight how these models can enhance various stages of incident response, including detection, triage, automated remediation, and post-incident analysis. Additionally, we discuss case studies showcasing the effectiveness of ML in real-world IR scenarios and identify key challenges, such as data quality, adversarial attacks, and model interpretability. The paper also proposes potential future directions, including hybrid ML models, human-in-the-loop systems, and advances in explainable AI, to further improve the reliability and transparency of ML-driven IR systems. Ultimately, this research aims to provide a comprehensive understanding of how machine learning can augment incident response efforts and enhance cybersecurity resilience in the face of increasingly sophisticated threats.
Generalized K-Fibonacci Sequence of Q- Matrix Kumar, Nand Kishor; Sahani, Suresh Kumar
Mikailalsys Journal of Advanced Engineering International Vol 2 No 1 (2025): Mikailalsys Journal of Advanced Engineering International
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mjaei.v2i1.4811

Abstract

This article explores the generalized K-Fibonacci sequence derived from matrices, extending the classical Fibonacci sequence to matrix representations. The properties and its applications are also described. The interplay of matrix algebra and generalized Fibonacci sequences offers insights into advanced sequence theory.
Impact of Agricultural Science Education on Youth Engagement in Agribusiness in Northeast Nigeria Daniel, Iliya; Yaro, Yusuf
Mikailalsys Journal of Advanced Engineering International Vol 2 No 1 (2025): Mikailalsys Journal of Advanced Engineering International
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mjaei.v2i1.4812

Abstract

This study investigates the impact of Agricultural Science education on youth engagement in agribusiness in Northeast Nigeria, focusing on its role in fostering entrepreneurial skills, enhancing practical training, and addressing challenges that hinder youth participation in agribusiness ventures. The research employed a questionnaire administered to 704 respondents, including 320 students and 384 youths, to assess the effectiveness of Agricultural Science education in preparing youth for agribusiness. The findings reveal that Agricultural Science education significantly contributes to the development of key entrepreneurial skills, equips students with essential knowledge, and cultivates an entrepreneurial mindset, encouraging youth to pursue agribusiness ventures. Despite these positive outcomes, challenges such as limited access to financial resources, inadequate infrastructure, and insufficient exposure to modern farming technologies impede youth engagement in agribusiness. The study also found that integrating modern agribusiness practices into the curriculum enhances students’ readiness to engage in agribusiness ventures. The study recommends improving hands-on training, incorporating modern agricultural technologies into the curriculum, increasing government support for agripreneurs, and fostering public-private partnerships to address the identified challenges. This research underscores the critical role of Agricultural Science education in promoting youth participation in agribusiness and its potential to contribute to the economic development of Northeast Nigeria.
Hybird PV-Wind System with Data Aquisation and Storage System Ojo, Oluwafemi Tayo
Mikailalsys Journal of Advanced Engineering International Vol 2 No 1 (2025): Mikailalsys Journal of Advanced Engineering International
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mjaei.v2i1.4851

Abstract

This project, conducted at the Department of Electrical Engineering, Ahmadu Bello University, Zaria, focuses on the design, hybridization, and analysis of an islanded microgrid system. The study begins with an evaluation of the performance of an existing standalone solar (PV) system. It then explores the integration of a wind energy system to form a hybrid energy system, enhancing reliability and efficiency. A key component of this project is the integration of a data acquisition system for real-time monitoring of weather conditions, including solar irradiance, wind speed, temperature, and humidity, alongside load profiling. Additionally, a data storage system is implemented to facilitate future referencing and analysis. This comprehensive approach aims to optimize the hybrid microgrid's performance, ensuring a stable and sustainable energy supply in off-grid settings.
Thermodynamic Studies on Adsorption of Methylene Blue and Congo Red Dyes Using Groundnut Shell and Sorghum Husk Biosorbents Hammari, Abubakar M.; Hammanadama, Faruk A.; Gadc, Ajuji I.
Mikailalsys Journal of Advanced Engineering International Vol 2 No 1 (2025): Mikailalsys Journal of Advanced Engineering International
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mjaei.v2i1.4919

Abstract

The effects of temperature on the adsorption of Methylene Blue (MB) and Congo Red (CR) dyes using groundnut shell (GS) and sorghum husk (SH) biosorbents were investigated. Adsorption capacities were determined through spectrophotometric analysis, and thermodynamic parameters including Gibbs free energy (ΔG), enthalpy (ΔH), and entropy (ΔS) were calculated. The study found that MB adsorption onto SH was spontaneous and endothermic, while other conditions exhibited non-spontaneous and exothermic behavior. These findings demonstrate the potential of GS and SH as viable, low-cost biosorbents for dye removal in wastewater treatment, highlighting their practical application in sustainable environmental remediation.
Impact of Microfinance on Small Business Growth and Economic Development in Low-Income Communities Karna, Poonam Kumari Labh
Mikailalsys Journal of Advanced Engineering International Vol 2 No 1 (2025): Mikailalsys Journal of Advanced Engineering International
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mjaei.v2i1.4977

Abstract

Microfinance provides small loans, savings accounts, and financial education to low-income communities. It promotes entrepreneurship, small business growth, and economic development. Its efficacy is disputed, with regional results varying. Microfinance's benefits, drawbacks, and future possibilities for small enterprises are examined in this article. Microfinance empowers women by expanding financial independence and employment engagement beyond economic inclusion. Microfinance Institutions (MFIs) provide lending, savings, and insurance to low- to moderate-income individuals and small companies, according to the World Bank. Micro-loans help entrepreneurs grow, create jobs, and stabilize finances in underdeveloped economies. Through diverse funding strategies, MFIs promote SMEs, advancing economic and social advancement. By enhancing education, healthcare, and economic self-sufficiency, microfinance improves long-term financial security. However, high capital costs and interest rates remain issues. Borrowers have financial limits because many MFIs are funded by commercial banks. This research examines microfinance's role in poverty reduction, obstacles, and its potential to create sustainable economic growth. Understanding its successes and weaknesses is crucial to enhancing its effectiveness and maintaining long-term financial inclusion in low-income communities.
The Impact of Artificial Intelligence on Risk Management in Banking and Finance Akinnagbe, Olayiwola Blessing; Akintayo, Taiwo Abdulahi; Adanna, Arinze Betsy
Mikailalsys Journal of Advanced Engineering International Vol 2 No 2 (2025): Mikailalsys Journal of Advanced Engineering International
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mjaei.v2i2.5195

Abstract

This research explores the transformative role of Artificial Intelligence (AI) in risk management within the banking and finance sector. It examines how AI technologies such as machine learning, natural language processing, and predictive analytics are enhancing risk assessment, fraud detection, and regulatory compliance. The study also highlights challenges such as data privacy, algorithmic bias, and the need for skilled professionals. The findings suggest that AI is revolutionizing risk management but requires careful implementation to mitigate associated risks.
AI-Powered Consumer-Generated Insights for Product Innovation Asunmonu, Ajoke A.
Mikailalsys Journal of Advanced Engineering International Vol 2 No 2 (2025): Mikailalsys Journal of Advanced Engineering International
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mjaei.v2i2.5335

Abstract

This research explores how AI-powered consumer-generated insights (CGI) enhance product innovation by analyzing unstructured data from reviews, social media, and visual content. Using natural language processing (NLP) and machine learning (ML), the study examines AI's role in identifying trends, accelerating development, and improving customer-centric design. Through case studies and data analysis, it evaluates AI's effectiveness while addressing challenges like data privacy and algorithmic bias. The findings aim to provide businesses with a practical framework for leveraging AI-driven insights responsibly, offering actionable strategies for faster, more innovative product development.
Trends, Effects, and Future Outlook for the Integration of Artificial Intelligence Technologies in the Energy Sector: The Role of Open Innovation Fatokun, Elijah Omoniyi
Mikailalsys Journal of Advanced Engineering International Vol 2 No 2 (2025): Mikailalsys Journal of Advanced Engineering International
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mjaei.v2i2.5391

Abstract

This paper explores the integration of Artificial Intelligence (AI) in the energy sector, focusing on its impact on operational efficiency, cost reduction, and environmental sustainability. It examines how open innovation fosters collaboration among energy companies, startups, and research institutions to accelerate AI adoption. Despite challenges such as data privacy, regulatory barriers, and infrastructure needs, AI technologies are poised to enhance energy optimization and support global goals like net-zero emissions and increased renewable energy penetration. The paper also looks ahead to the future of AI in energy, highlighting the potential of quantum computing, reinforcement learning, and advanced neural networks in driving further innovation.

Page 3 of 6 | Total Record : 56

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