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28,296 Article Results

Analysis of mobile banking adoption in Ghana: do education levels differ?

10.11591/ijaas.v14.i3.pp828-837
Isaac Asampana , Lawrence Kwami Aziale , Henry Matey Akwetey , Hannah Ayaba Tanye
This study investigates the role of educational attainment in mobile banking (m-banking) adoption in Ghana, leveraging data from 598 respondents through a multi-group analysis. By integrating the technology acceptance model (TAM) and the theory of planned behavior (TPB) into a structural equation modelling framework, the research examines key factors such as subjective norms, perceived usefulness, ease of use, trust, and self-efficacy. Results reveal significant differences in adoption behaviors between lower- and higher-educated users. Subjective norms strongly influence higher-educated individuals, while perceived ease of use drives adoption among lower-educated users. Perceived usefulness positively affects higher-educated users but has a negative impact on lower-educated respondents. The findings highlight the moderating effect of education level on the adoption process, offering theoretical and practical insights into targeted strategies for enhancing financial inclusion in developing economies. These results underscore the importance of user segmentation in fostering broader acceptance and utilization of m-banking technologies.
Volume: 14
Issue: 3
Page: 828-837
Publish at: 2025-09-01

Self-development moderates the impact of digital literacy and talent on human error

10.11591/ijaas.v14.i3.pp682-692
Achmad Mirza , Isnurhadi Isnurhadi , Muhammad Ichsan Hadjri
Effective public services are important for increasing community satisfaction and organizational credibility. This study aims to explore the influence of digital literacy, underutilized talent, and human error on the effectiveness of public services, with self-development as a moderating variable. This study was conducted with employees of the Trade Office of South Sumatra Province. The research method used was quantitative data analysis, which was performed using partial least squares structural equation modeling (PLS-SEM). The results of this study show that digital literacy and self-development play an important role in reducing human error and increasing the effectiveness of public services. These findings have practical implications for human resource management in the public sector, focusing on improving digital literacy and employee self-development. 
Volume: 14
Issue: 3
Page: 682-692
Publish at: 2025-09-01

Optimizing retail systems: using big data and power business intelligence for performance insights

10.11591/ijaas.v14.i3.pp945-954
Huu Dang Quoc , Ha Le Viet
In the rapid development of information technology, using enterprise data to support timely management decisions is crucial in helping businesses operate effectively and improve competitiveness. This study uses Microsoft power business intelligence (MPBI) to analyze data in retail systems, allowing managers to grasp the business situation in real time, track advanced sales, optimize inventory control, and analyze customer behavior and supply chain visibility. From the data generated by the business, the study uses the streaming extract transform load (ETL) model to support real-time data aggregation, then converts to the MPBI data visualization system to convert data into visual charts, helping businesses easily monitor, track, analyze, and make decisions to promote business activities. The study proposes a data structure to organize retail information storage. It proposes a system of calculation formulas and data synthesis, making integrate and convert tabular data into visual charts. Through analysis of real data from the LH83 retail system, the study shows the feasibility of implementing a data visualization system and the difficulties encountered when businesses want to deploy this model.
Volume: 14
Issue: 3
Page: 945-954
Publish at: 2025-09-01

Fuzzy logic controller-based protection of direct current bus using solid-state direct current breaker

10.11591/ijaas.v14.i3.pp859-868
Eswaraiah Giddalur , Askani Jaya Laxmi
Low-voltage direct current (LVDC) microgrids are increasingly utilized due to their efficiency and compatibility with distributed energy resources (DERs) and direct current (DC) loads, eliminating the need for multiple energy conversions. However, the protection of LVDC systems presents significant challenges, including high fault currents and the vulnerability of electronic devices. Traditional electromechanical circuit breakers are inadequate due to their slow response times. This work presents a protection approach for the DC bus in LVDC microgrids that combines a fuzzy logic controller (FLC) with a solid-state circuit breaker (SSCB). The FLC is designed to detect and respond to faults rapidly by processing input variables such as current magnitude and rate of change of current. The FLC controls the SSCB, which interrupts fault currents quickly and reliably. The proposed system demonstrates optimized fault-clearing times within milliseconds, significantly enhancing the protection and reliability of LVDC microgrids. This novel solution protects critical electronic components while also ensuring the microgrid's operational integrity. The FLC approach is utilized for optimizing fault-clearing duration within milliseconds.
Volume: 14
Issue: 3
Page: 859-868
Publish at: 2025-09-01

Comprehensive structured analysis of machine learning in safety models

10.11591/ijaas.v14.i3.pp627-638
Mohd Shukri Abdul Wahab , Syed Tarmizi Syed Shazali , Noor Hisyam Noor Mohamed , Abdul Rani Achmed Abdullah
Machine learning (ML) integration into various industries has revolutionized operations recently, enhancing efficiency and predictive capabilities. However, the rapid adoption of ML models also presents significant safety concerns that are highly demanded. To achieve this, scholarly articles from reputable databases such as Scopus and Web of Science (WoS) focus on studies published between 2022 and 2024, which were extensively searched. The study's flow is based on the PRISMA framework. The database found (n=40) that the final primary data was analyzed. The findings were divided into three themes: i) safety and risk management, ii) ML and artificial intelligence (AI) applications in safety, and iii) smart technology for safety. The conclusion highlights the need for continuous monitoring and updating of the safety protocols to keep in step with the growing ML landscape. This review contributes to the understanding of ML safety. It offers global lessons that can guide future research and policy-making efforts to ensure ML technologies' safe and ethical use.
Volume: 14
Issue: 3
Page: 627-638
Publish at: 2025-09-01

Searchable encryption based on a chaotic system and AES algorithm

10.11591/ijaas.v14.i3.pp975-984
Fairouz Sherali , Falah Sarhan
Cloud computing provides on-demand access to computing resources, such as storage and processing power. This technology allows businesses to scale efficiently while reducing infrastructure costs. However, protecting the security and privacy of data has grown to be a top priority. This is where enhancing cloud security with searchable encryption (SE) is crucial. SE effectively secures users’ sensitive data while preserving searchability on the cloud server side. It enables the cloud server to search via encrypted data without disclosing information in plaintext data. SE uses different encryption methods to encrypt data before uploading it to servers. The advanced encryption standard (AES) is a common algorithm for encrypting this data. In this paper, a novel SE method has been presented. The technique exploits the properties of the chaotic map to generate an AES key, which makes the AES algorithm more secure for encrypting the searchable index and uploaded files. We implement and test our method with real data from files. The experimental results show that the proposed method can significantly satisfy a higher level of security as compared to other schemes.
Volume: 14
Issue: 3
Page: 975-984
Publish at: 2025-09-01

Machine learning techniques for solar energy generation prediction in photovoltaic systems

10.11591/ijpeds.v16.i3.pp2055-2062
J. Sumithra , J. C. Vinitha , M. J. Suganya , M. Anuradha , P. Sivakumar , R. Balaji
For photovoltaic (PV) systems to be as effective and dependable as they possibly can be, it is vital to make an accurate prediction of the amount of power that will be generated by the sun. Using machine learning, it is now much simpler to forecast the amount of solar energy that will be generated. These approaches are more accurate and are able to adapt to the ever changing conditions of the nature of the environment. We take a look at the most recent machine learning algorithms for predicting solar energy and examine their methodology, as well as their strengths and drawbacks, in this paper. Using performance metrics like root mean squared error (RMSE), mean absolute error (MAE), and mean squared error (MSE) makes it possible to evaluate important algorithms like support vector machines, decision trees, and linear regression. The results show that machine learning could help make predictions more accurate, lower the amount of uncertainty in operations, and help people make decisions in real time for PV systems. The study also points out important areas where research is lacking and suggests ways to move forward with the use of machine learning in systems that produce renewable energy.
Volume: 16
Issue: 3
Page: 2055-2062
Publish at: 2025-09-01

Performance evaluation of multicarrier quadrature phase shift keying-based system under noisy channel conditions

10.11591/ijaas.v14.i3.pp693-701
Deepa Narayana Reddy , Aishwarya Nagaraju , Deepti Hosakere Prabhakara , Deekshitha Beeraganahalli Srinivas , Gandlaparthi Navyatha
A comprehensive analysis of quadrature phase shift keying (QPSK) modulation in both single input single output (SISO) and multiple input multiple output (MIMO) systems is conducted using MATLAB. The investigation focuses on evaluating QPSK performance with metrics such as signal-to-noise ratio (SNR) and bit error rate (BER) across diverse channel conditions. Furthermore, the study extends to encompass the integration of QPSK with orthogonal frequency division multiplexing (OFDM), with a particular emphasis on assessing spectral efficiency and error rate implications. To validate the accuracy of the simulations, QPSK and QPSK-OFDM configurations are implemented on the WiComm-T hardware platform, enabling a direct comparison of real-world performance metrics against simulation results. By offering practical insights and recommendations for the deployment of robust communication systems, this research underscores the inherent advantages of integrating OFDM with QPSK across both SISO and MIMO configurations.
Volume: 14
Issue: 3
Page: 693-701
Publish at: 2025-09-01

Sulphur corrosion in transformer insulating oils: its effects, detection methods, and mitigation strategies

10.11591/ijaas.v14.i3.pp784-792
Nur Izyan Husnina Zulkefli , Sharin Ab Ghani , Mohd Shahril Ahmad Khiar , Imran Sutan Chairul , Nor Hidayah Rahim , Nur Farhana Mohd Azlan
Oil-immersed transformers are subjected to electrical, thermal, and mechanical stresses over time, which inevitably affect the insulating oil and paper insulation. The presence of sulphur corrosion also degrades the insulating oil and paper insulation. Sulphur corrosion in insulating oils has been a prevalent problem for many years, as it culminates in the failure of oil-immersed transformers. The longevity of oil-immersed transformers is dependent on the integrity of the insulating oil and paper insulation, which can deteriorate owing to sulphur corrosion. The occurrence and accumulation of copper sulphide (Cu2S) can result in transformer malfunctions, which is a significant issue for transformer manufacturers and operators. This paper provides a concise overview of the effects of sulphur corrosion, its detection methods, as well as its mitigation strategies. It is believed that this paper will enhance the understanding of sulphur corrosion in insulating oils, provide the best practices for sulphur corrosion management, and serve as guidance on enhancing transformer reliability and performance.
Volume: 14
Issue: 3
Page: 784-792
Publish at: 2025-09-01

Redesign the layout of the raw material warehouse from randomized storage to class-based storage

10.11591/ijaas.v14.i3.pp773-783
Nur Iftitah , Qurtubi Qurtubi , Danang Setiawan , Vembri Noor Helia
The company has a problem of ineffectiveness in the layout of the raw material warehouse due to the use of storage methods that ignore factors such as the type, dimensions, and condition of the goods. This reduces the optimal function of the warehouse and increases the time to retrieve goods. This research aims to redesign the suitable and practical layout of the raw material warehouse by considering its form and function, as well as filling methodological gaps from previous research. The method used is class-based storage. Based on ABC analysis, the category with the highest value is class C goods, with 73 units. Meanwhile, from the fast, slow, non-moving (FSN) analysis, class F (fast-moving) goods have the highest frequency of movement, with a movement percentage of 63% for 10 units of goods. The warehouse slotting analysis shows an increase in the number of shelves from nine to 15 shelves with five different shelf models and layout changes in raw material warehouses 1 and 2. The class-based storage method results in a more organized layout, efficient movement of goods, and faster picking time to optimize warehouse functions.
Volume: 14
Issue: 3
Page: 773-783
Publish at: 2025-09-01

Numerical study of non-linear twisted blades for tidal turbines improvement

10.11591/ijaas.v14.i3.pp894-906
Nu Rhahida Arini , Philips Ade Putera Atmojo , Deni Saputra , Dendy Satrio
Despite the growing demand for renewable energy, the utilization of tidal energy remains underdeveloped due to efficiency limitations in turbine design. Addressing this gap, this study investigates the performance of horizontal-axis tidal turbines (HATT) by comparing two foil designs, National Advisory Committee for Aeronautics (NACA) 2415 and OptA, to optimize energy extraction efficiency. The research employs computational fluid dynamics (CFD) simulations using OpenFOAM to evaluate the effects of foil modifications and non-linear twist distributions on turbine performance across varying tip speed ratios (TSR). The results indicate that the OptA foil significantly improves turbine performance, achieving a 41.4% increase in torque and a 40.2% increase in power coefficient (CP) at TSR 5, which was identified as the optimal operating condition. The OptA foil enhances velocity distribution, reduces flow separation, and improves vortex behavior, leading to greater efficiency and stability. These findings confirm that foil selection and blade design modifications play a critical role in HATT optimization.
Volume: 14
Issue: 3
Page: 894-906
Publish at: 2025-09-01

A bibliometric review of lean principles in highway pavement for productivity improvement

10.11591/ijaas.v14.i3.pp639-649
Pooja P. Gohil , MohammedShakil S. Malek , Deep Shaileshkumar Upadhyaya
A past study of 25 years reveals the positive impact of lean principles on highway pavement productivity. This bibliometric review extracted 389 papers from the Scopus database that revolved around three terms, “lean principles,” “highway pavement,” and “productivity improvement,” and used VOSviewer for scientometric analysis and scientific mapping. Study reveals that addressing this topic on a global scale is of chief significance, given the potential variations in indices of the issue across different countries or provinces. This research undertakes a comprehensive qualitative analysis that highlights diverse indicators that exert influence on the productivity of pavements. Additionally, this analysis also seeks to propose potential avenues for future research within lean construction. An intensive investigation provides four unique clusters of words that have been formed through the process of keyword science mapping within the context of the lean principles, which are road segment, techniques, productivity improvement, and lean. Last but not least, 4 pointers are recommended that will help stakeholders and policymakers assess pavement performance practices, identify areas for improvement, and execute targeted interventions to improve productivity.
Volume: 14
Issue: 3
Page: 639-649
Publish at: 2025-09-01

The impact of fast charging technology on battery longevity in electric vehicles

10.11591/ijaas.v14.i3.pp936-944
Perattur Nagabushanam , Kalagotla Chenchireddy , Radhika Dora , Thanikanti Sudhakar Babu , Vadthya Jagan , Varikuppala Manohar
Fast charging technology has revolutionized the electric vehicle (EV) industry by addressing range anxiety and significantly reducing charging times. However, this convenience introduces challenges concerning battery longevity, as high charging currents and elevated temperatures accelerate battery degradation. This paper investigates the mechanisms through which fast charging impacts lithium-ion batteries, including thermal stress, lithium plating, and mechanical wear. It synthesizes findings from various studies, highlighting how fast charging can shorten battery lifespan by up to 20-30% compared to standard charging methods. Strategies to mitigate these effects, such as advanced materials, adaptive charging protocols, and efficient thermal management systems, are discussed. Furthermore, the paper emphasizes the importance of standards and policies to promote sustainable fast charging practices. By balancing charging speed with long-term battery health, the EV industry can achieve widespread adoption while ensuring sustainability. This work aims to provide a comprehensive understanding of the trade-offs associated with fast charging and offers actionable insights for improving EV battery durability.
Volume: 14
Issue: 3
Page: 936-944
Publish at: 2025-09-01

Artificial neural network based sensorless position estimation and direct torque control for stepper motor

10.11591/ijaas.v14.i3.pp702-710
Nagasridhar Arise , Thiruveedula Madhu Babu , Srinidhi Gollapudi , Tarun Kumar Dommeti , Abhishek Kummari , Mahith Shambukari
This study describes and illustrates how sensorless location estimation is achieved through the application of artificial neural network (ANN) control. Control stepper motor torque directly. Using stepper motors directly leads to a lot of problems; therefore, automated control systems are now commonly preferred. Stepper motors have several drawbacks when used directly, including the potential for steps to occasionally be missing while the motors are running. When physical sensors are not available, the proposed method estimates rotor position and speed using electrical signals and ANN algorithms. Simulation and experiment results demonstrate accurate position estimation (±1.5°) and efficient torque control. The sensorless direct torque control (DTC)-ANN approach increases the performance, reliability, and cost of stepper motors in robotics, computer numerical control (CNC) machines, and 3D printing.
Volume: 14
Issue: 3
Page: 702-710
Publish at: 2025-09-01

Test rig development for load test of pipe saddle support

10.11591/ijaas.v14.i3.pp886-893
Muhammad Arif Rayhan , Mohd Shukri Yob , Mohd Juzaila Abd Latif , Ojo Kurdi , Fudhail Abdul Munir
Pipe saddle support is a structure commonly used to support horizontal steel pipe. It prevents direct contact between the pipe and the support. Pipe saddle support can experience displacement due to pipe movement and insufficient stress analysis. Given these concerns, conducting a load test is essential to determine the stress on pipe saddle supports. However, a universal testing machine (UTM) is not suitable for this purpose due to the size limitation. Therefore, this study proposed a test rig setup for the pipe saddle support load test. The test rig consists of a portal frame secured by an underground locking system featuring a strong floor. Additionally, an actual pipe is utilized to replicate actual loading conditions on the pipe saddle support. The applied load is measured using a load cell, with a custom-designed bracket to ensure precise load transfer. Finally, the pipe saddle support specimen is bolted to a base support to maintain stability during the load test. Stress analysis using finite element analysis (FEA) demonstrated that the test rig is suitable for conducting load tests on the specimens with a maximum force of 80 kN. FEA confirmed that the test rig operates within a safety factor of 1.3.
Volume: 14
Issue: 3
Page: 886-893
Publish at: 2025-09-01
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