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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.

Examining the potential of machine learning for predicting academic achievement: A systematic review by Nazir, M., Noraziah, Ahmad, Rahmah, M., Sharma, Aditi

“…Predicting student academic performance is a critical area of education research. Machine learning (ML) algorithms have gained significant popularity in recent years. …”
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Examining the potential of machine learning for predicting academic achievement: A systematic review by Nazir, M., Noraziah, Ahmad, Rahmah, M., Sharma, Aditi

“…Predicting student academic performance is a critical area of education research. Machine learning (ML) algorithms have gained significant popularity in recent years. …”
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Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud by Shariff, S. Sarifah Radiah, Hud, Hady

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Evaluation of postgraduate academic performance using artificial intelligence models by Baashar, Y., Hamed, Y., Alkawsi, G., Fernando Capretz, L., Alhussian, H., Alwadain, A., Al-amri, R.

“…With these demands come the need for those institutions to develop strategies that can enhance students' learning experiences at various educational levels. …”
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Evaluation of postgraduate academic performance using artificial intelligence models by Baashar, Y., Hamed, Y., Alkawsi, G., Fernando Capretz, L., Alhussian, H., Alwadain, A., Al-amri, R.

“…With these demands come the need for those institutions to develop strategies that can enhance students' learning experiences at various educational levels. …”
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Evaluation of postgraduate academic performance using artificial intelligence models by Baashar, Y., Hamed, Y., Alkawsi, G., Fernando Capretz, L., Alhussian, H., Alwadain, A., Al-amri, R.

“…With these demands come the need for those institutions to develop strategies that can enhance students' learning experiences at various educational levels. …”
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Ensemble learning for multidimensional poverty classification by Azuraliza Abu Bakar, Rusnita Hamdan, Nor Samsiah Sani

“…Analysis of this study showed that Per Capita Income, State, Ethnic, Strata, Religion, Occupation and Education were found to be the most important variables in the classification of poverty at a rate of 99% accuracy confidence using Random Forest algorithm.…”
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An application of predicting student performance using kernel k-means and smooth support vector machine by Sajadin, Sembiring

“…In this study, psychometric factors used as predictor variables, thereare Interest, Study Behavior, Engaged Time, Believe, and Family Support.The rulemodel developed using Kernel K-means Clustering and Smooth Support Vector MachineClassification.Both of these techniquesbased on kernel methodsand relativelynew algorithms of data mining techniques, recently received increasingly popularity in machine learning community. …”
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Discriminative feature representation for Malay children’s speech recognition / Seyedmostafa Mirhassani by Mirhassani, Seyedmostafa

“…Three speech databases were used for the experiments including prolonged Malay vowels and Malay continuous speech database based on children’s speech and TIMIT database based on adult speeches. …”
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The Crop Price Prediction Using Machine Learning: Preliminary Stage by Ramya, T.K., Shreedhara N, Hegde, Mohd Norshahriel, Abd Rani

“…A predictive system, a statistical method combining machine learning and data collecting, is used in many applications, including healthcare, retail, education, and government sectors. …”
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Tangible interaction learning model to enhance learning activity processes among children with dyslexia by Jamalai@Jamali, Siti Nurliana

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Predictive modelling of student academic performance using machine learning approaches : a case study in universiti islam pahang sultan ahmad shah by Nurul Habibah, Abdul Rahman

“…The predictive algorithm can also be added to the Learning Management System along with a dashboard so that it is easier to do analyses in the future.…”
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Artificial Intelligence (AI) to predict dental student academic performance based on pre university results by Abdullah, Adilah Syahirah, Ahmad Amin, Afifah Munirah, Lestari, Widya, Sukotjo, Cortino, Utomo, Chandra Prasetyo, Ismail, Azlini

“…The dataset input variables will include student’s gender, age during admission, scholarship, parents’ level of education, pre-university result, Professional Exams result, and final CGPA. …”
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Determining malaria risk factors in Abuja, Nigeria using various statistical approaches by Segun, Oguntade Emmanuel

“…Based on cross-validation analysis, the score-based algorithm outperformed the constraint-based algorithms in the structural learning. …”
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Predicting Post-Internship Employability Using Ensemble Machine Learning Approach by Aiza Azlin, Kahlik, Abdulrazak Yahya, Saleh

“…Employing a machine learning approach on a dataset comprising student records from Universiti Malaysia Sarawak spanning from 2019 to 2021, we compared the performance of various algorithms, including ensemble methods. …”
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Enhancing understanding of programming concepts through physical games by Raja Yusof, Raja Jamilah, Habib, Ahsan

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The basics of multi-layer feedforward neural networks / Nurul Aityqah Yaccob and Farizuwana Akma Zulkifle by Yaccob, Nurul Aityqah, Zulkifle, Farizuwana Akma

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Computational Thinking : Experiences of Rural Pupils in Sarawak Primary School by Nur Hasheena, Anuar

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

“…Data mining has been widely applied in educational area recently and it is commonly called Educational Data Mining (EDM). …”
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