Article Per Year (5 Year)
p-Index From 2021 - 2026
1.532
P-Index
This Author published in this journals
All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Data Science Insights Journal of Sustainable Software Engineering and Information Systems
Wan Hussain Wan Ishak
Universiti Utara Malaysia
Computer Science & IT Engineering

Published : 9 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 9 Documents
Search

 1 
Evaluation of scratch and pre-trained convolutional neural networks for the classification of Tomato plant diseases Mohammad Amimul Ihsan Aquil; Wan Hussain Wan Ishak
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 10, No 2: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v10.i2.pp467-475

Abstract

Plant diseases are a major cause of destruction and death of most plants and especially trees. However, with the help of early detection, this issue can be solved and treated appropriately. A timely and accurate diagnosis is critical in maintaining the quality of crops. Recent innovations in the field of deep learning (DL), especially in convolutional neural networks (CNNs) have achieved great breakthroughs across different applications such as the classification of plant diseases. This study aims to evaluate scratch and pre-trained CNNs in the classification of tomato plant diseases by comparing some of the state-of-the-art architectures including densely connected convolutional network (Densenet) 120, residual network (ResNet) 101, ResNet 50, ReseNet 30, ResNet 18, squeezenet and Vgg.net. The comparison was then evaluated using a multiclass statistical analysis based on the F-Score, specificity, sensitivity, precision, and accuracy. The dataset used for the experiments was drawn from 9 classes of tomato diseases and a healthy class from PlantVillage. The findings show that the pretrained Densenet-120 performed excellently with 99.68% precision, 99.84% F-1 score, and 99.81% accuracy, which is higher compared to its non-trained based model showing the effectiveness of using a combination of a CNN model with fine-tuning adjustment in classifying crop diseases.
Personalized E-Portfolio: A Dynamic Web-based Tool for Students’ Professional Growth Muhammad Syamil bin Manaf; Wan Hussain Wan Ishak; Fadhilah Mat Yamin
Journal of Sustainable Software Engineering and Information Systems Vol. 1 No. 1 (2025): Journal of Sustainable Software Engineering and Information Systems
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/jsseis.v1i1.64

Abstract

Background of study: Electronic portfolios (e-portfolios) have become vital tools for students to document learning and build professional identity. Yet, many existing platforms are hindered by technical complexity, limited personalization, and low engagement. Aims and scope of paper: This paper introduces a personalized e-portfolio system designed to overcome these issues by applying agile and user-centered approaches, focusing on usability and adaptability in higher education. Methods: The system was developed using HTML, CSS, JavaScript, PHP, and phpMyAdmin through six agile phases: planning, design, development, testing, deployment, and review. User needs were gathered from students and lecturers, while 30 students evaluated the system using the Website Analysis and Measurement Inventory (WAMMI) across five usability factors. Result: Usability testing showed high satisfaction. Learnability (4.47), controllability (4.22), and efficiency (4.17) scored the highest, indicating that the system is intuitive and effective. Participants valued its role in reflection and personal branding, while suggesting improvements in visual design, customization, and integration with platforms like LinkedIn. Conclusion: The study confirms that agile and user-centered design can produce an adaptable e-portfolio system that enhances students’ professional growth and provides a scalable model for higher education institutions.
Development of a Web-Based Industrial Training Student Activity Management System Wan Hussain Wan Ishak; Siti Nur Aisyah binti Abdullah
Journal of Sustainable Software Engineering and Information Systems Vol. 1 No. 1 (2025): Journal of Sustainable Software Engineering and Information Systems
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/jsseis.v1i1.65

Abstract

Background of study: Industrial training is essential for bridging academic knowledge and workplace practice, equipping students with technical and soft skills required for future employment. However, traditional documentation methods such as manual logbooks are often inefficient, error-prone, and limit effective supervision and timely feedback. Aims and scope of paper: This paper presents the development of the Web-Based Industrial Training Student Activity Management System (WIT), designed to streamline industrial training management at the School of Computing, Universiti Utara Malaysia. The system aims to enhance communication, ensure accurate reporting, and support sustainable digital supervision. Methods: The WIT system was developed using the Waterfall Model, with stakeholder input incorporated at each stage of requirements, design, development, testing, and maintenance. Usability testing was conducted with 30 participants (students and staff) using the WAMMI framework, which evaluates five key usability dimensions. Result: The evaluation results demonstrated high levels of user satisfaction across all metrics: Attractiveness (91.67%), Controllability (97.5%), Helpfulness (94.17%), Efficiency (92.5%), and Learnability (96.67%). These findings confirm that WIT provides an effective, user-friendly platform for activity logging, reporting, and supervision. Conclusion: WIT successfully addresses challenges in traditional training management by promoting transparency, accountability, and efficient supervision. The system contributes to ICT-driven educational innovation and has strong potential for future scalability, including mobile integration and advanced analytics.
Personalized E-Portfolio: A Dynamic Web-based Tool for Students’ Professional Growth Muhammad Syamil bin Manaf; Wan Hussain Wan Ishak; Fadhilah Mat Yamin
Journal of Sustainable Software Engineering and Information Systems Vol. 1 No. 1 (2025): Journal of Sustainable Software Engineering and Information Systems
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/jsseis.v1i1.64

Abstract

Background of study: Electronic portfolios (e-portfolios) have become vital tools for students to document learning and build professional identity. Yet, many existing platforms are hindered by technical complexity, limited personalization, and low engagement. Aims and scope of paper: This paper introduces a personalized e-portfolio system designed to overcome these issues by applying agile and user-centered approaches, focusing on usability and adaptability in higher education. Methods: The system was developed using HTML, CSS, JavaScript, PHP, and phpMyAdmin through six agile phases: planning, design, development, testing, deployment, and review. User needs were gathered from students and lecturers, while 30 students evaluated the system using the Website Analysis and Measurement Inventory (WAMMI) across five usability factors. Result: Usability testing showed high satisfaction. Learnability (4.47), controllability (4.22), and efficiency (4.17) scored the highest, indicating that the system is intuitive and effective. Participants valued its role in reflection and personal branding, while suggesting improvements in visual design, customization, and integration with platforms like LinkedIn. Conclusion: The study confirms that agile and user-centered design can produce an adaptable e-portfolio system that enhances students’ professional growth and provides a scalable model for higher education institutions.
Development of a Web-Based Industrial Training Student Activity Management System Wan Hussain Wan Ishak; Siti Nur Aisyah binti Abdullah
Journal of Sustainable Software Engineering and Information Systems Vol. 1 No. 1 (2025): Journal of Sustainable Software Engineering and Information Systems
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/jsseis.v1i1.65

Abstract

Background of study: Industrial training is essential for bridging academic knowledge and workplace practice, equipping students with technical and soft skills required for future employment. However, traditional documentation methods such as manual logbooks are often inefficient, error-prone, and limit effective supervision and timely feedback. Aims and scope of paper: This paper presents the development of the Web-Based Industrial Training Student Activity Management System (WIT), designed to streamline industrial training management at the School of Computing, Universiti Utara Malaysia. The system aims to enhance communication, ensure accurate reporting, and support sustainable digital supervision. Methods: The WIT system was developed using the Waterfall Model, with stakeholder input incorporated at each stage of requirements, design, development, testing, and maintenance. Usability testing was conducted with 30 participants (students and staff) using the WAMMI framework, which evaluates five key usability dimensions. Result: The evaluation results demonstrated high levels of user satisfaction across all metrics: Attractiveness (91.67%), Controllability (97.5%), Helpfulness (94.17%), Efficiency (92.5%), and Learnability (96.67%). These findings confirm that WIT provides an effective, user-friendly platform for activity logging, reporting, and supervision. Conclusion: WIT successfully addresses challenges in traditional training management by promoting transparency, accountability, and efficient supervision. The system contributes to ICT-driven educational innovation and has strong potential for future scalability, including mobile integration and advanced analytics.
Assessing Student ICT Knowledge Through Survey and Hands-On Task Fadhilah Mat Yamin; Wan Hussain Wan Ishak; Abdullah Husin
Data Science Insights Vol. 1 No. 1 (2023): Journal of Data Science Insights
Publisher : PT. Visi Media Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63017/jdsi.v1i1.2

Abstract

To date, knowledge on information and communication technology (ICT) is a vital to all students. ICT knowledge is the skills of using appropriate ICT devices and software to accomplish a task. This knowledge is gain through practices and experience when using the ICT. Besides the academic excellence, ICT knowledge is another most important assets for any graduate before entering the job market. This is because ICT has become one of the key components of any organization's operations. This study aims to assess the level of ICT mastery among final year undergraduate students. This study employed two main methods of questionnaire and practical activities. The questionnaire aimed to assess students’ basic knowledge on ICT while the practical activities aimed to assess students’ actual skills. The findings from the questionnaire show that students believe that they have adequate knowledge on ICT. However, practical activities show that students' true mastery is still at a moderate level. Therefore, students need to enhance their ICT skills to enhance their value and capabilities in the job market. Students also should take the advantage of exploring and applying their ICT skills during their learning activities such as preparing, completing, and presenting their assignments. These are crucial exercises that can improve their ICT knowledge and skills.
Customer Satisfaction Towards Onsite Restaurant Interactive Self-Service Technology (ORISST) Por Eng Choo; Fadhilah Mat Yamin; Wan Hussain Wan Ishak
Data Science Insights Vol. 2 No. 1 (2024): Journal of Data Science Insights
Publisher : PT. Visi Media Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63017/jdsi.v2i1.15

Abstract

A recent development in the restaurant industry is the use of on-site restaurant interactive self-service technology (ORISST) by some operators who are moving away from traditional service methods. ORISST allows customers to manage dining services independently through interfaces such as self-service kiosks or tabletop tablets. However, the gap in understanding customer satisfaction regarding ORISST is notable as there is a lack of technology-related research in the restaurant industry. The research objectives of this study is to investigate the significant relationship between the four dimensions of SSTQUAL (functionality, design, enjoyment, customization) and customer satisfaction in using ORISST. In this study, quantitative research was conducted. Data was collected via google form from 293 STML students at UUM who had experience using ORISST. The findings of this study show that functionality, design and enjoyment have a significant positive relationship with customer satisfaction in using ORISST, with functionality being the most significant determinant. In contrast, customization has no significant relationship with customer satisfaction in using ORISST. All these findings may provide valuable suggestions to restaurant operators on how to properly implement ORISST to improve their business performance and attract more customers. This study has broadened the understanding of customer satisfaction towards ORISST which has yet to be fully explored.
Database-Specific Keyword Frequency Analysis in Merged Web Log Data: A Preprocessing Method Wan Hussain Wan Ishak; Nurul Farhana Ismail; Fadhilah Mat Yamin; Abdullah Husin
Data Science Insights Vol. 2 No. 1 (2024): Journal of Data Science Insights
Publisher : PT. Visi Media Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63017/jdsi.v2i1.16

Abstract

This study investigates the complex intricacies of web log data within the Electronic Resources module of the Perpustakaan Sultanah Bahiyah (PSB) website at Universiti Utara Malaysia (UUM). Serving as a cornerstone of academic infrastructure, the Electronic Resources module acts as a vital gateway, seamlessly connecting the UUM academic community to a vast repository of scholarly information. To tackle challenges posed by the size and complexity of web log data, the research employs a meticulous preprocessing method, involving the restructuring of raw data, outlier cleaning, and user session identification, laying the foundation for a comprehensive analysis. The study further explores the identification of search keywords embedded in the log file, employing a systematic process that transforms data into a structured format. The subsequent extraction of databases and keywords yields intriguing findings, prominently highlighting IEEE and Serial Solution databases. The analysis of 19,146 keywords associated with 11 databases offers valuable insights into user behavior, preferences, and the overall effectiveness of the Electronic Resources module. The identification of frequent keywords not only provides analytical insights but also serves to accelerate users' search processes, reducing cognitive load and fostering a more efficient research experience. This research contributes to the optimization of user experiences and the ongoing refinement of digital library services, aligning them with the evolving needs of the academic community
Comparative Analysis of Data Visualization Techniques for Rainfall Data Wan Hussain Wan Ishak; Fadhilah Yamin; Siti Sarah Maidin; Abdullah Husin
Data Science Insights Vol. 3 No. 2 (2025): Journal of Data Science Insights
Publisher : PT. Visi Media Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63017/jdsi.v3i2.204

Abstract

Rainfall data is essential for applications such as climate monitoring, agricultural planning, flood forecasting, and water resource management. However, the interpretation of this data is often hindered by its high volume, variability, and multi-scale temporal nature. Effective visualization is critical not only for summarizing complex datasets but also for uncovering patterns, detecting anomalies, and facilitating informed decision-making. Despite the availability of numerous visualization techniques, selecting the most suitable method for rainfall data, especially across varying temporal resolutions is a challenging task. This study presents a comparative analysis of widely used data visualization techniques in the context of rainfall data. The methodology was structured into three phases: understanding the nature of rainfall data, reviewing relevant visualization techniques, and conducting a comparative content analysis. A SWOT (Strengths, Weaknesses, Opportunities, and Threats) evaluation was used to assess each technique’s analytical potential, while a temporal suitability comparison was performed across five time granularities: yearly, monthly, weekly, daily, and hourly. Findings show that no single technique is universally effective. Instead, each method demonstrates specific strengths and limitations depending on the temporal scale and analytical objective. Line charts and bar charts are well-suited for lower-frequency data, while heat maps and scatter plots are more effective for high-resolution, time-sensitive patterns. Box plots and histograms provide valuable insights into data distribution and variability, whereas map-based visualizations excel in spatial analysis but require enhancements for temporal exploration. The study concludes that visualization effectiveness depends on aligning method selection with data characteristics and analytical goals. A thoughtful combination of techniques is often necessary to achieve clarity, reduce misinterpretation, and enhance decision support in rainfall data analysis.
Co-Authors Abdullah Abdullah Abdullah Husin Fadhilah Mat Yamin Fadhilah Mat Yamin Fadhilah Yamin Mohammad Amimul Ihsan Aquil Muhammad Syamil bin Manaf Nurul Farhana Ismail Por Eng Choo Siti Nur Aisyah binti Abdullah Siti Sarah Maidin