Comprehensive Insights Into Smart Contracts: Architecture, Sectoral Applications, Security Analysis, And Legal Frameworks,
2025
International Islamic University Malaysia, Malaysia
Comprehensive Insights Into Smart Contracts: Architecture, Sectoral Applications, Security Analysis, And Legal Frameworks, Farah Mazlan, Nur Faizah Omar, Nik Nor Muhammad Saifudin Nik Mohd Kamal, Ahmad Anwar Zainuddin
Journal of Informatics and Web Engineering
Most conventional contract systems have issues with middlemen, drawn-out implementation procedures, fraud risk, and human error. Considering this, the project uses smart contract technology to provide a decentralized, automated, and safe solution in an effort to address such inefficiencies and the trust issues they raise. Smart contracts enable self-execution of contracts whose conditions are expressed explicitly in lines of code by presenting solutions using blockchain technology. The concept behind a smart contract is that each party may carry out their portion of the duties without depending on a third party and the contract will automatically execute in the meantime. This …
Predicting Short-Range Weather In Tropical Regions Using Random Forest Classifier,
2025
HELP University, Malaysia
Predicting Short-Range Weather In Tropical Regions Using Random Forest Classifier, Sellappan Palaniappan, Rajasvaran Logeswaran, Anitha Velayutham, Bui Ngoc Dung
Journal of Informatics and Web Engineering
In this paper, we present a Random Forest classifier machine learning model for predicting short-range weather in in tropical regions like Malaysia. Our model uses environmental factors such as temperature, humidity, wind speed, and cloud cover to predict weather conditions like clear skies, rain, and thunderstorms. Tropical weather, influenced by high humidity, fluctuating temperatures, and frequent rainfall, present unique challenges for forecasting accurately. To address these challenges, we trained a Random Forest classifier on a synthetic (simulated) dataset comprising 1,500 samples, each representing a specific weather scenario. Our model achieved an accuracy of 98.66% in predicting short-term weather conditions, identifying …
A Comparative Study Of Oracle Erp Netsuite And Microsoft Dynamics 365 Contributions To Contemporary Business Development In India,
2025
Study World College of Engineering Coimbatore, India
A Comparative Study Of Oracle Erp Netsuite And Microsoft Dynamics 365 Contributions To Contemporary Business Development In India, Padmanabhan Subramanian, Ponmalar S
Journal of Informatics and Web Engineering
ERP systems centrally provide support to a company's business operations and are capable of providing solutions in the area of resource management, process streamlining, and making data-driven decisions. Acceptance of ERP systems is growing in India as companies begin to become more efficient and competitive. Among the most prominent players are Oracle ERP Netsuite and Microsoft Dynamics 365, both holding unique attributes which pose a challenge for businesses when choosing the right system. The aim of this paper of study is to compare between Oracle ERP Netsuite and Microsoft Dynamics 365 by exploring their contribution to business development in India. …
Improved Accuracy For Heart Disease Diagnosis Using Machine Learning Techniques,
2025
Sarvajanik University, India
Improved Accuracy For Heart Disease Diagnosis Using Machine Learning Techniques, Neeraja Joshi, Tejal Dave
Journal of Informatics and Web Engineering
This work primarily focuses on diagnosis of heart disease before explicit visit to the expert doctor. Machine learning based systems have been found useful in medical diagnosis applications because of their ability to learn human like expertise and to utilize acquired knowledge for diagnosis. This work is performs classification of heart disease utilizing subject’s vital parameters. Pathological laboratory results available after testing are not understood by common people and patients have to wait till they visit expert doctors for inference. In this paper, traditional methods like linear regression to various machine learning based systems including back propagation neural network, support …
Enhancing Financial Literacy: A Progressive Web Application Approach For Malaysian Youth,
2025
Multimedia University, Malaysia
Enhancing Financial Literacy: A Progressive Web Application Approach For Malaysian Youth, Jun-Xuan Kok, Sin-Ban Ho, Chuie-Hong Tan
Journal of Informatics and Web Engineering
Financial management is a crucial skill that individuals of all age ranges should acquire and master. It offers a transparent view of our financial status, enabling us to comprehend where our expenses are directed and manage every facet of our finances. Studies have indicated that Malaysian youth lack understanding in financial management. Nowadays, with so many people using the internet, we have the opportunity to share this expertise with a larger audience. Providing easily accessible materials for learning about and managing personal finances is essential to comprehending people's individual financial circumstances. In light of this, the purpose of this article …
Social Engineering Threat Analysis Using Large-Scale Synthetic Data,
2025
HELP University, Malaysia
Social Engineering Threat Analysis Using Large-Scale Synthetic Data, Sellappan Palaniappan, Rajasvaran Logeswaran, Shapla Khanam, Pulasthi Gunawardhana
Journal of Informatics and Web Engineering
We frequently hear news about compromised systems, virus attacks, spam emails, stolen bank account numbers, and loss of money. Safeguarding and protecting digital assets against these and other cyber-attacks are extremely important in our digital connected world today. Many organizations spend substantial amounts of money to protect their digital assets. One type of cyber threat that is rampant these days is social engineering attacks that work on human psychology. These attacks typically persuade, convince, trick and threaten naïve and innocent individuals to divulge sensitive information to the attackers. Consequently, traditional approaches have not been effective or successful in preventing these …
Hyperledger Fabric Blockchain For Securing The Edge Internet Of Things: A Review,
2025
International Islamic University Malaysia, Malaysia
Hyperledger Fabric Blockchain For Securing The Edge Internet Of Things: A Review, Muhammad Haziq Zulhazmi Hairul Nizam, Muhammad Afiq Ahmad Nizam, Muhammad Hadi Husaini Jummadi, Nik Nor Muhammad Saifudin Nik Mohd Kamal, Ahmad Anwar Zainuddin
Journal of Informatics and Web Engineering
Life has become more convenient, efficient, and productive in aspects like homes, healthcare, and other businesses’ due to applied IoT. Nonetheless, the proliferation of IoT has led to enormous data production, which has presented daunting tasks of providing sound protective security solutions. It is crucial to address the above challenges in order to protect the data assets in IoT systems. This work deals with the concern on how to extend Hyperledger Fabric to IoT, this being a very crucial aspect in allowing for secure techniques in the collection, storage and sharing of data. Hyperledger Fabric offers advanced capabilities of smart …
Machine Learning Approaches For Detecting Vine Diseases: A Comparative Analysis,
2025
National University of Sciences and Technology, Pakistan
Machine Learning Approaches For Detecting Vine Diseases: A Comparative Analysis, Waheed Ahmad, Eshill Azhar, Maham Anwar, Sarah Ahmed, Tayyaba Noor
Journal of Informatics and Web Engineering
This study investigates the classification of vine leaf diseases using convolutional neural networks (CNNs), focusing on three major diseases: powdery mildew, caused by fungus Uncinula necator, Red Blotches associated with pathogens such as Phomopsis viticola, Grapevine Leafroll Disease and leafroll associated Grape -linked virus (GLRaV). Accurate diagnosis of these high-risk diseases is critical to vine health and yields. We evaluated the performance of three CNN algorithms—MobileNetV2, ResNet50, and VGG16 —by comparing their training and validation accuracies, as well as loss over ten seasons. MobileNetV2 emerged as the most robust model, exhibiting high accuracy and low loss, indicating strong generalizability. ResNet50 …
Implementing Identity-Based Signature Schemes For Secure Data Transfer In Cloud Computing Environments,
2025
University of Plymouth, United Kingdom
Implementing Identity-Based Signature Schemes For Secure Data Transfer In Cloud Computing Environments, Paul Osinuga, Ji-Jian Chin, Terry Shue Chien Lau
Journal of Informatics and Web Engineering
In this paper, we present the implementation of the Cha-Cheon Identity-Based Signature (IBS) scheme to enhance secure data transfer in cloud computing environments. Cloud computing rely on traditional Public Key Infrastructure (PKI) systems, which is burdened by certificate management infrastructure. The primary focus of this research to simplify key and certificate management by leveraging identity-based elliptic curve cryptography (ECC) within the Cha-Cheon IBS framework. We show that the proposed IBS solution integrates seamlessly with Amazon Web Services (AWS), utilizing services like S3 for secure data storage and KMS for key management. By applying ECC, the Cha-Cheon scheme achieves efficient cryptographic …
Iot-Based Nerve Stimulator For Women’S Safety,
2025
SRM Valliammai Engineering College, India
Iot-Based Nerve Stimulator For Women’S Safety, K Revathi, W Gracy Theresa
Journal of Informatics and Web Engineering
Women deserve a right to live free from intimidation, mistreatment, unfair treatment, and eliminating hurdles from a hazardous workplace can help them reach their maximum potential both personally and as contributions to economies, societies, and the workplace. Physical, emotional, and environmental safety have a variety of effects on wellbeing, including stress management, emotional stability, and physical health. The Women Safety System with Nerve Stimulator is a comprehensive system that integrates essential components for women's safety using an Arduino Uno microcontroller. It has an SOS button for emergency activation, a temperature sensor for environmental monitoring, a pulse oximeter for tracking health, …
Lung Tumor Segmentation In Medical Imaging Using U-Net,
2025
SRM Institute of Science and Technology, India
Lung Tumor Segmentation In Medical Imaging Using U-Net, J Jayapradha, Su-Cheng Haw, Naveen Palanichamy, Senthil Kumar Thillaigovindhan, Mutaz Al-Tarawneh
Journal of Informatics and Web Engineering
Tumors are a deadly condition often triggered by a range of abnormal modifications and genetic abnormalities. Early tumor diagnosis is essential due to the highly concerned nature of the disease. Early detection and treatment of tumors can significantly reduce mortality rates. This paper presents a model for tumor segmentation in medical imaging that uses the U-NET architecture to increase precision. The model’s encoding and decoding processes have been applied with skip connections to boost performance while simplifying model training. Images were cropped around the lower abdominal regions, and all images used in the study were then resized to 256*256 pixels …
A Hybrid Deep Learning Vgg-16 Based Svm Model For Vehicle Type Classification,
2025
The University of Agriculture Peshawar, Pakistan
A Hybrid Deep Learning Vgg-16 Based Svm Model For Vehicle Type Classification, Muhammad Imran, Jafar Usman, Muntazir Khan, Abdullah Khan
Journal of Informatics and Web Engineering
Car classification is important in daily life because there are many distinct types of automobiles made by various manufacturers. Although there are numerous methods for classifying autos, machine learning technologies have not been widely utilized, resulting in low accuracy levels. The goal of this paper is to create a machine learning system that is especially made to categories models of two Pakistan's top automakers, Toyota, and Honda. Ten Toyota models such as Avalon, Land Cruiser, Camry, Corolla, C-HR, Highlander, Prius, Tundra, RAV4, and Yaris and a dataset of Honda automobiles, which also includes 10 models (Accord, Civic, CR-V, Fit, HR-V, …
Early Identification Of Parkinson's Disease Using Time Frequency Analysis On Eeg Signals,
2025
Multimedia University, Malaysia
Early Identification Of Parkinson's Disease Using Time Frequency Analysis On Eeg Signals, Tanvir Hasib, V Vijayakumar, Ramakrishnan Kannan
Journal of Informatics and Web Engineering
Parkinson's Disease (PD) is a progressive neurological disorder. It affects movement and can significantly impact quality of life. Early and accurate diagnosis is crucial for effective management and intervention. Traditional diagnostic methods can be time-consuming and less effective in the early stages of the disease. This study aims to develop an automated approach for identifying PD using time-frequency image analysis of electroencephalogram (EEG) signals. The goal is to enhance diagnostic accuracy and efficiency, facilitating early detection. EEG signals, often contaminated with artifacts such as eye blinks and muscle movements etc., were first cleaned. Time-frequency images were then plotted from the …
Debugprograde: Improving Automated Assessment Of Coding Assignments With A Focus On Debugging,
2025
Veer Narmad South Gujarat University, India
Debugprograde: Improving Automated Assessment Of Coding Assignments With A Focus On Debugging, Amit Patel, Hardik Joshi
Journal of Informatics and Web Engineering
In education, the evaluation of programming assignments is challenging, especially to do with the debugging aspect. Self-grading technologies are unable to capture the level of understanding of students and context-bound responses. In light of these, we created DebugProGrade to take what we normally know about grading and improve it with semantic analysis and keyword extraction. DebugProGrade identified 1000 first-year BCA students who in Google Forms provided their answers to evaluate error detection and solution proposals for a basic C programming assignment. For the explanations’ specificity and for the context-level evaluation, the system employs the SBERT embedding, namely, the sentence-transformer bidirectional …
Optimising Phishing Detection: A Comparative Analysis Of Machine Learning Methods With Feature Selection,
2025
Multimedia University, Malaysia
Optimising Phishing Detection: A Comparative Analysis Of Machine Learning Methods With Feature Selection, Mohamad Asraf Daniel, Siew-Chin Chong, Lee-Ying Chong, Kuok-Kwee Wee
Journal of Informatics and Web Engineering
Phishing is an act of cybersecurity attack that tricks people into sharing sensitive data. Due to the inefficiency of the current security technologies, researchers have been paying much attention to employing machine learning methods for phishing detection lately. In our proposed solution, the effectiveness of machine learning techniques with feature selection techniques for phishing detection is investigated. To be specific, Random Forest (RF) and Artificial Neural Network (ANN) are integrated with feature selection techniques, Principal Component Analysis (PCA) and Recursive Feature Elimination (RFE). The goal was to identify and classify the model with the highest accuracy. The experiments were evaluated …
Integrating Moral Values In Ai: Addressing Ethical Challenges For Fair And Responsible Technology,
2025
St. Xavier’s College (Autonomous), India
Integrating Moral Values In Ai: Addressing Ethical Challenges For Fair And Responsible Technology, Khushboo Shah, Hiren Joshi, Hardik Joshi
Journal of Informatics and Web Engineering
Today, Artificial Intelligence (AI) has become an integral part of our day-to-day life. From personal task to professional life everywhere we need AI. All the sectors like - transport, education, healthcare, agriculture, we find AI everywhere. Each coin has two side, similarly AI has its own pros and cons. Main challenge with AI is ethics. There is no doubt in the work efficiency of AI but ultimately, it’s a machine without emotions hence whatever the decision it takes it purely without ethical values. Sometimes, this type of decision may lead to disasters, especially in the industry where human life is …
Creating An Android-Based Calisthenics Application To Assist Students In Improving Their Physical Fitness,
2025
Universitas Kristen Duta Wacana, Indonesia
Creating An Android-Based Calisthenics Application To Assist Students In Improving Their Physical Fitness, Restyandito, Narendra Poetra Wisnoewardhana, Danny Sebastian
Journal of Informatics and Web Engineering
College students, particularly those heavily involved in coursework, frequently do not prioritize physical fitness. Regular exercise is essential for preserving physical fitness and facilitating demanding academic tasks. Although there are other fitness programs available, such as GYM, jogging, CrossFit, and Yoga, users sometimes fail to make full use of them because the content is confined to exercise videos and descriptions. This matter highlights the progress of the Android application Kali Tech, which specifically concentrates on organizing and documenting calisthenics workouts. This program employs the concept of gamification by utilizing student achievement levels to encourage students to be diligent in doing …
Machine Learning Model For Predicting Net Environmental Effects,
2025
HELP University, Malaysia
Machine Learning Model For Predicting Net Environmental Effects, Sellappan Palaniappan, Rajasvaran Logeswaran, Shapla Khanam, Zhang Yujiao
Journal of Informatics and Web Engineering
Environmental sustainability is a global challenge in the face of increasing incidences of disasters affecting communities worldwide. This requires predicting net environmental effects accurately. While various approaches exist, we need more sophisticated prediction models that account for both environmental and social factors. This study presents a proof-of-concept machine learning model for predicting net environmental effects using synthetic data. We developed a multiple linear regression model incorporating nine key features: renewable energy usage, carbon emissions, air quality index, water usage, biodiversity impact, land use, public awareness, and environmental attitudes. We generated a synthetic dataset of 1000 samples using probability distributions and …
Fiber Break Prevention Using Machine Learning Approaches,
2025
Multimedia University, Malaysia
Fiber Break Prevention Using Machine Learning Approaches, Zhan Heng Ng, Tee Connie, Kan Yeep Choo, Michael Kah Ong Goh, Nurul Ain Abdul Aziz, Hong Yeap Ngo
Journal of Informatics and Web Engineering
Modern fiber-optic communication systems are built around optical fiber, which allows data to be sent by emitting infrared light pulses. It is widely used by telecommunications firms and is essential to the smooth transmission of information in internet communication as well as the transmission of telephone signals. Nonetheless, optical fibers intrinsic fragility raises a problem, especially in areas where building projects are taking place. Especially nowadays construction-related impact and crushing pressures can cause physical damage that jeopardizes the fiber optic's integrity. Therefore, this research emphasizes the necessity of taking preventative and mitigating actions to reduce the possibilities of fiber optic …
Migraine Generative Artificial Intelligence Based On Mobile Personalized Healthcare,
2025
Multimedia University, Malaysia
Migraine Generative Artificial Intelligence Based On Mobile Personalized Healthcare, Michelle Ting-Ting Yong, Sin-Ban Ho, Chuie-Hong Tan
Journal of Informatics and Web Engineering
Migraine is a complicated genetic disorder characterized by episodes of moderate-to-severe headaches that are usually unilateral and are frequently accompanied by nausea and increased sensitivity to sound and light. A migraine attack induces intense pain, hindering an individual from engaging in daily activities and potentially persisting for hours or even days. By the growth of the Internet of Things, we have new opportunities to try to apply it to the medical field. To identify the origin of a migraine, specialists need access to a patient's medical history and a comprehensive understanding of migraine symptoms for effective treatment. Determining the true …
