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Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm
Published 2008“…Among Information Technology graduates, Java programming assignments is an essential part of learning programming as it trains the student to solve programming assignments so that they can improve their programming skills that is useful in their professional life after graduation. …”
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Teaching and learning via chatbots with immersive and machine learning capabilities
Published 2019“…Each of these chatbots focuses on different programming concepts or constructs. These chatbots support learning of Java via problem-solving steps through “learning by doing”. …”
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Developing an intelligent system to acquire meeting knowledge in problem-based learning environments
Published 2006“…This project adapts the original MALESAbrain definitions and algorithm to create an intelligent learning tool; then, testing the tool in a students' meeting to discuss "To build up programming skills for computer science students, do you agree JAVA is a proper language in the first year foundation, course for computer science students"? …”
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Object-Oriented Programming semantics representation utilizing agents
Published 2011“…Learning programming from source code examples is a common behavior among novices. …”
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Laptop price prediction using decision tree algorithm / Nurnazifah Abd Mokti
Published 2024“…The project involves data collection, data preparation, and the implementation of the decision tree algorithm for price prediction. The decision tree's effectiveness and accuracy in predicting laptop prices are evaluated through rigorous testing and validation. …”
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Diagnosis and recommender system for diabetes patient using decision tree / Nurul Aida Mohd Zamary
Published 2024“…The phase of this project is divided into data preprocessing, implementation of the decision tree algorithm, and evaluation of the algorithm and prototype. …”
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Face classification for three major ethnic of Orang Asli using Back Propagation Neural Network / Nor Intan Shafini Nasaruddin
Published 2012“…The image classification prototype is developed by using JAVA programming language which is based on supervised learning algorithm, Backpropagation Neural Network. …”
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Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
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Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud
Published 2023“…Practical implications In terms of managerial implications, the findings in this research help to frame the adoption of a more advanced analytical approach to forecasting, using a Machine Learning algorithm, in solving a newsvendor problem. …”
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Electric vehicle battery state of charge estimation using metaheuristic-optimized CatBoost algorithms
Published 2025“…Three distinct metaheuristic algorithms were investigated: Barnacles Mating Optimizer (BMO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Whale Optimization Algorithm (WOA), each integrated with CatBoost to optimize critical parameters including learning rate, tree depth, regularization, and bagging temperature. …”
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Prediction models of heritage building based on machine learning / Nur Shahirah Ja'afar
Published 2021“…To overcome these limitations, this research has proposed five machine learning algorithms namely Linear Regression, Lasso, Ridge, Random Forest and Decision Tree. …”
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XAIRF-WFP: a novel XAI-based random forest classifier for advanced email spam detection
Published 2024“…Traditional machine learning algorithms such as Logistic Regression (LR), K-Nearest Neighbors (KNN), Decision Trees (DT), and Support Vector Machines (SVM) have been employed to mitigate this challenge. …”
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A review of the inter-correlation of climate change, air pollution and urban sustainability using novel machine learning algorithms and spatial information science
Published 2021“…The study also revealed that machine learning algorithms such as random forest, gradient boosting machine, and classification and regression trees (CART) accurately predict air pollution hazard when integrated with spatial models. …”
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