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Predicting students’ STEM academic performance in Malaysian secondary schools using educational data mining by Termedi @ Termiji, Mohammad Izzuan

“…Four different data mining classification algorithms which are Random Forest, PART, J48 and Naive Bayes will be used on the dataset. …”
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Combining cluster quality index and supervised learning to predict students’ academic performance by Suhaila Zainudin, Rapi’ah Ibrahim, Hafiz Mohd Sarim

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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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The analysis of road traffic fatality pattern for Selangor, Malaysia case study by Radzuan, N. Q., Mohd Hasnun Ariff, Hassan, Abu Kassim, K. A., Ab. Rashid, A. A., Intan Suhana, Mohd Razelan, Nur Aqilah, Othman

“…However, both of them also have few dissimilarities such as crash time of occurrence, day of occurrence, number of vehicles involved in a crash, and type of vehicle first hit for the crash. Supervised machine learning algorithm in Orange data mining software was considered in this analysis. …”
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An early warning system for students at risk using supervised machine learning by Yam, Zheng Hong, Mohd Norshahriel, Abd Rani, Nabilah Filzah, Mohd Radzuan, Lim, Huay Yen, Sarasvathi, Nagalingam

“…The system will detect or forecast symptoms of dropout or potential dangers ahead of time, allowing educational institutions to anticipate problems and provide adequate educational services through appropriate intervention and response. A dashboard system will be created with a descriptive data mining model that can examine and make early judgments on at-risk students before they become highrisk. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

Using Text Analytics on Social Media Posts to Identify Cues or Features of Depressive Behavior by Ibrahim A.H., Cob Z.C., Drus S.M., Latif A.A., Radzi H.M., Anwar R.M.

“…This study used the cross-industry process for data mining (crisp-dm) methodology for developing the depression detection model. …”

Validation of deep convolutional neural network for age estimation in children using mandibular premolars on digital panoramic dental imaging / Norhasmira Mohammad by Mohammad, Norhasmira

“…The advancement of technologies in medical imaging facilitates the development of computer-based applications in which machine learning is used to leverage data mining in the medical industry to improve the reliability and speed of diagnosis while also increasing reproducibility. …”
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