Search Results - (( java application modified algorithm ) OR ( data education learning algorithm ))

Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

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E4ML: Educational Tool for Machine Learning by Sainin, Mohd Shamrie, Siraj, Fadzilah

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DESIGN AND DEVELOPMENT OF ANDROID-BASED LEARNING MEDIA FOR LEARNING ALGORITHM AND DATA STRUCTURE by Rosyid Ridlo, Al Hakim, Rianti Y., Kisworini, Aditia P., Hamid, Agung, Pangestu, Ariep, Jaenul, Yanuar Zulardiansyah, Arief

“…One of the learning techniques is in the form of algorithms and data structures. …”
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Clustering Student Performance Data Using k-Means Algorithms by Sultan Alalawi, Sultan Juma, Mohd Shaharanee, Izwan Nizal, Mohd Jamil, Jastini

“…The research approach known as educational data mining (EDM) focuses on using data mining techniques to extract massive data from the educational context and transform it into knowledge that can improve educational systems and decisions. …”
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Prevention And Detection Mechanism For Security In Passive Rfid System by Khor, Jing Huey

“…A GUI is created in a form of JAVA application to display data detected from tag. …”
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Tracking student performance in introductory programming by means of machine learning by Khan I., Al Sadiri A., Ahmad A.R., Jabeur N.

“…Big data; Decision trees; Education computing; Learning algorithms; Learning systems; Machine learning; Smart city; Students; Trees (mathematics); Educational data mining; Educational institutions; Hidden patterns; Introductory programming; Introductory programming course; Student performance; Student's performance; Weka; Data mining…”

Automatic generation of content security policy to mitigate cross site scripting by Mhana, Samer Attallah, Din, Jamilah, Atan, Rodziah

“…The algorithm is implemented as a plugin. It does not interfere with the web application original code. …”
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Minimizing Classification Errors in Imbalanced Dataset Using Means of Sampling by Khan I., Ahmad A.R., Jabeur N., Mahdi M.N.

Analyzing enrolment patterns: modified stacked ensemble statistical learning based approach to educational decision-making by Zun, Liang Chuan, Nursultan Japashov, Soon, Kien Yuan, Tan, Wei Qing, Noriszura Ismail

“…The study’s primary objectives were to identify the determinants that impacted urban upper-secondary students' enrolment in Additional Mathematics within the Kuantan District, Pahang, Malaysia, and to develop a novel modified stacked ensemble statistical learning-based algorithm based on potential determinants, following the Cross Industry Standard Process for Data Mining (CRISP-DM) data science methodology. …”
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Enhancing hyperparameters of LSTM network models through genetic algorithm for virtual learning environment prediction by Ismanto, Edi, Ab Ghani, Hadhrami, Md Saleh, Nurul Izrin

“…In today's technology-driven era, innovative methods for predicting behaviors and patterns are crucial. Virtual Learning Environments (VLEs) represent a rich domain for exploration due to their abundant data and potential for enhancing learning experiences. …”
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Approach For Optimizing Course Recommendation Based On Integrating Modified Felder-Silverman Learning Style Model With Meta-Heuristics Algorithm by Ashraf, Erum

“…Recommender systems filter courses but struggle with learning styles due to lack of standardized datasets and measurement approaches, hindering data collection in resource-constrained educational institutions. …”
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Students’ attitude towards video-based learning: machine learning analysis with rapid software / Abdullah Sani Abd Rahman ... [et al.] by Abd Rahman, Abdullah Sani, Meutia, Rita, Hamid, Yusnaliza, Abdul Rahman, Rahayu

“…This paper presents the fundamental design and easy implementation of machine learning for education domain useful for the inexpert data scientists in many fields.…”
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Learning analytic framework for students’ academic performance and critical learning pathways by Lyn, Jessica Tan Yen, Goh, Yong Kheng, Lai, An Chow, Ngeow, Yoke Meng

“…To address this, a unified learning analytics framework is proposed, aimed at deciphering complex student academic journeys and fostering data-informed decision-making for educational institutions. …”
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Educational Data Mining for Student Performance Prediction : A Systematic Literature Review (2015-2021) by Muhammad Haziq, Hassan, Chen, Chwen Jen

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Assessment and Evaluation of Different Machine Learning Algorithms for Predicting Student Performance by Alsariera Y.A., Baashar Y., Alkawsi G., Mustafa A., Alkahtani A.A., Ali N.

Virtual reality in algorithm programming course: practicality and implications for college students by Dewi, Ika Parma, Ambiyar, Mursyida, Lativa, Effendi, Hansi, Giatman, Muhammad, Efrizon, Hanafi, Hafizul Fahri, Ali, Siti Khadijah

“…The reliability of VR supports various variations in learning, including learning programming algorithms. …”
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The application of suitable sports games for junior high school students based on deep learning and artificial intelligence by Ji, Xueyan, Samsudin, Shamsulariffin, Hassan, Muhammad Zarif, Farizan, Noor Hamzani, Yuan, Yubin, Chen, Wang

“…They are obviously lower than those of other algorithms. ST-GCN action detection algorithm based on deep learning and artificial intelligence technology can significantly improve the accuracy of action recognition in junior middle school students’ sports activities, and provide an immediate and accurate feedback mechanism for physical education teaching. …”
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An Analysis of Students� Academic Performance Using K-Means Clustering Algorithm by Ahmad, M., Arshad, N.I.B., Sarlan, A.B.

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Rao-SVM machine learning algorithm for intrusion detection system by Abd, Shamis N., Alsajri, Mohammad, Ibraheem, Hind Raad

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Data Analytics on student response via social media on the educational landscape (learning, experience, humanization) during the COVID-19 pandemic by Zaiful Anuar, Muhamad Zarif

“…All comments from particularly selected posts are retrieved via a data extraction tool. Then, a sentiment analysis of the comments is carried out using machine learning algorithms such as Support Vector Machine to analyse the sentiments conveyed by the students via their comments. …”
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