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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) JOIV : International Journal on Informatics Visualization IJOEM: Indonesian Journal of Elearning and Multimedia Finger : Jurnal Ilmiah Teknologi Pendidikan
Hamzah, Raseeda
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Computer Science & IT Education Engineering Languange, Linguistic, Communication & Media Social Sciences Other

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Semi-supervised spectral clustering using shared nearest neighbor for data with different shape and density YouSheng, Gao; Abdul Rahim, Siti Khatijah Nor; Hamzah, Raseeda; Ang, Li; Aminuddin, Raihah
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i2.pp2283-2290

Abstract

In the absence of supervisory information in spectral clustering algorithms, it is difficult to construct suitable similarity graphs for data with complex shapes and varying densities. To address this issue, this paper proposes a semisupervised spectral clustering algorithm based on shared nearest neighbor (SNN). The proposed algorithm combines the idea of semi-supervised clustering, adding SNN to the calculation of the distance matrix, and using pairwise constraint information to find the relationship between two data points, while providing a portion of supervised information. Comparative experiments were conducted on artificial data sets and University of California Irvine machine learning repository datasets. The experimental results show that the proposed algorithm achieves better clustering results compared to traditional K-means and spectral clustering algorithms.
Convolutional neural network modelling for autistic individualized education chatbot Hamzah, Raseeda; Jamil, Nursuriati; Ahmad, Nor Diana; Syed Zainal Ariffin, Syed Mohd Zahid
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i1.pp109-118

Abstract

The traditional education system for autistic kids needs integration with computer technology that embraces artificial intelligence to help school instructors and management. An application that enables the teacher to retrieve information from a trusted source is essential since the information is only sometimes available on time. Thus, developing a chatbot application that utilizes natural language processing can enhance the management of autistic schools and will help individualized education for autistic students. This research uses a deep learning model that utilizes a convolutional neural network to develop a chatbot as a teaching assist tool for teachers. The results show that the chatbot has achieved ˜0.03% loss when trained with different epoch numbers. In terms of usability, the chatbot achieves mean system usability scores of 80.48 ± 13.03. This may open opportunities for more effective individualized education for students with special needs and increase the potential to improve inclusive education for disabled students. It is useful to include future actions that enable the simplification of the use of this chatbot tool in a wide range of contexts. To close the education gap for children with disabilities, chatbots could help people with communication disabilities and could also significantly enhance the rate of communication.
DualVitOA: A dual vision transformer-based model for osteoarthritis grading using x-ray images Ruiyun, Qiu; Abdul Rahim, Siti Khatijah Nor; Jamil, Nursuriati; Hamzah, Raseeda
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 2: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i2.pp925-932

Abstract

Knee osteoarthritis (OA) is a primary factor contributing to reduced activity and physical impairment in older individuals. Early identification and treatment of knee OA can assist patients in delaying the advancement of the condition. Currently, knee OA is detected early using X-ray images and assessed based on the Kellgren-Lawrence (KL) grading system. Doctors' assessments are subjective and can vary among different doctors. The automatic knee OA grading and diagnosis can assist doctors and help doctors reduce their workload. A new novel network called dual-vision transformer (ViT) OA is proposed to automatically diagnose knee OA. The network utilizes pre-processing technologies to process the data before doing classification operations using the Dual-ViT network. The suggested network outperformed neural networks like ResNet, DenseNet, visual geometry group (VGG), inception, and ViT in terms of accuracy and mean absolute error (MAE), and achieved an accuracy of 78.4 and MAE of 0.471, demonstrating its effectiveness.
Learning Evaluation Using Block Programming on Object-Oriented Programming Materials to Improve Cognitive Skills Huda, Kirana Syafa; Alfitri, Latifahny Aridia; Hamzah, Raseeda; Riza, Lala Septem
IJOEM Indonesian Journal of E-learning and Multimedia Vol. 4 No. 3 (2025): Indonesian Journal of E-learning and Multimedia (October 2025)
Publisher : CV. Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/ijoem.v4i3.473

Abstract

Background: Vocational students in Indonesia face low cognitive performance due to curricula that emphasize memorization and shallow understanding. In programming subjects such as Object-Oriented Programming (OOP), students often manage to write syntactically correct code but struggle with conceptual mastery. This limits their ability to develop higher-order thinking skills such as analysis, evaluation, and creation.Aims: This study aims to evaluate the use of block programming in OOP materials and its impact on improving students’ cognitive abilities in class X PPLG 3 at SMKN 4 Bandung.Methods: A quantitative approach was applied using a one-group pretest–posttest experimental design. Research instruments included expert validation sheets, cognitive evaluation tests, and student response questionnaires. Data were collected from 34 students to measure learning improvementResults: The findings revealed a significant increase in student performance, with average scores rising from 27.03 (pretest) to 85.47 (posttest). The N-Gain score reached 0.80 (80.29%), categorized as “high.” Student responses toward block programming media reached 93.61%, showing strong engagement. The integration of block programming with Problem-Based Learning (PBL) provided a contextualized and intuitive approach, transforming abstract OOP concepts into more tangible visual representations.Conclusion: Block programming is effective as a learning evaluation medium in OOP. It supports cognitive development, enhances student engagement, and simplifies complex concepts. This study recommends the broader use of block programming in evaluating OOP learning to create interactive and measurable experiences.
A Comparative Study of Image Retrieval Algorithm in Medical Imaging Abdullah, Yang Muhammad Putra; Bakar, Suraya Abu; Hj Wan Yussof, Wan Nural Jawahir; Hamzah, Raseeda; Hamid, Rahayu A; Satria, Deni
JOIV : International Journal on Informatics Visualization Vol 8, No 3-2 (2024): IT for Global Goals: Building a Sustainable Tomorrow
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.3-2.3447

Abstract

In recent times, digital environments have become more complex, and the need for secure, efficient, and reliable identification systems is growing in demand. Consequently, image retrieval has emerged as a critical area focusing on artificial intelligence and machine learning applications. Medical image retrieval has become increasingly crucial in today's healthcare field, as it involves accurate diagnostics, treatment planning, and advanced medical research. As the quantity of medical imaging data grows rapidly, the ability to efficiently and accurately retrieve relevant images from extensive datasets becomes critical. Advanced retrieval systems, such as content-based image retrieval, are imperative for managing complex data, ensuring that healthcare professionals can access the most relevant information to improve patient outcomes and advance medical knowledge. This paper compares three algorithms: Scale Invariant Feature Transform, Speeded Robust Features, and Convolutional Neural Networks in the context of two medical image datasets, ImageCLEF and Unifesp. The findings highlight the trade-offs between precision and recall for each algorithm, providing invaluable insights into selecting the most suitable algorithm for specific tasks. The study evaluates the algorithms based on precision and recall, two critical performance metrics in image retrieval.
Development of Virtual Reality Media for Earthquake Simulation Ulum, Muhammad Bahrul; Prasetyaningsih, Prasetyaningsih; Akbar, Anthonio; Hamzah, Raseeda; Wahyudin, Wahyudin; Riza, Lala Septem
FINGER : Jurnal Ilmiah Teknologi Pendidikan Vol. 4 No. 3 (2025): Finger : Jurnal Ilmiah Teknologi Pendidikan November 2025
Publisher : CV. Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/finger.v4i3.460

Abstract

Background: Indonesia has a high risk of earthquakes, necessitating innovative approaches to disaster mitigation education.Aims: This study aims to develop Virtual Reality (VR)-based learning media to enhance students’ understanding and preparedness, particularly among students, in facing earthquake scenarios.Methods: The development process comprises four main stages: identifying educational content, designing interactive scenarios, creating 3D assets and interactive elements, and developing the virtual reality application using Unity.Results: The developed interactive VR media includes a tutorial feature, selectable earthquake location scenario (classroom, library, laboratory), and adjustable earthquake magnitude settings. It enables users to experience immersive and safe earthquake simulations while actively practicing appropriate  emergency response procedures.Conclusion: The application of VR-based learning media offers substantial potential to enhance disaster literacy, increase student engagement, and create more meaningful learning experiences. The implementation of this media in educational settings is expected not only to strengthen a culture of disaster awareness but also to contribute to reducing casualties and losses caused by earthquakes in the future.
Co-Authors Abdul Rahim, Siti Khatijah Nor Abdullah, Yang Muhammad Putra Ahmad, Nor Diana Akbar, Anthonio Alfitri, Latifahny Aridia Aminuddin, Raihah Bakar, Suraya Abu Deni Satria Hamid, Rahayu A Hj Wan Yussof, Wan Nural Jawahir Huda, Kirana Syafa Jamil, Nursuriati Lala Septem Riza Li Ang, Li Muhammad Bahrul Ulum Prasetyaningsih Prasetyaningsih, Prasetyaningsih Ruiyun, Qiu Syed Zainal Ariffin, Syed Mohd Zahid Wahyudin Wahyudin YouSheng, Gao