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Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

Demand analysis of flood insurance by using logistic regression model and genetic algorithm by Sidi, P., Mamat, M.B., Sukono, ., Supian, S., Putra, A.S.

“…It is assumed that there are eight variables that influence the decision of purchasing flood assurance, include: income level, education level, house distance with river, building election with road, flood frequency experience, flood prediction, perception on insurance company, and perception towards government effort in handling flood. …”
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Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions by Saraswati, Galuh Wilujeng

“…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
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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.

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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Determining malaria risk factors in Abuja, Nigeria using various statistical approaches by Segun, Oguntade Emmanuel

“…The BBNs developed revealed that SES, household size and education level have the highest influence on reported cases as variations in response due to global sensitivity of network nodes. …”
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Technical efficiency performance of Malaysian public research universities: Fuzzy data envelopment analysis / Saber Abdelall Mohamed Ahmed by Saber Abdelall, Mohamed Ahmed

“…Based on past research supported by scholars in higher education studies, this study three input variables selected are the number of full-time-equivalent (FTE) staff, number of full-time-equivalent students and ratio of FTE international students to FTE students. …”
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The Effect of Entry Qualifications and Gender Towards Student Performance by M. M., Noor, K., Kadirgama, M. R. M., Rejab, M. Y., Taib

“…Entries qualifications are from Foundation Program, Higher Certificate of Malaysian Education (STPM) and Diploma Certificate. STPM is form six examinations in secondary school level. …”
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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.

“…The main purpose of this study was to predict the academic performance of students, their cumulative grade point average (CGPA) in particular, at postgraduate levels (e.g., master's degree), using and comparing different machine learning (ML) algorithms. …”
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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.

“…The main purpose of this study was to predict the academic performance of students, their cumulative grade point average (CGPA) in particular, at postgraduate levels (e.g., master's degree), using and comparing different machine learning (ML) algorithms. …”
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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.

“…The main purpose of this study was to predict the academic performance of students, their cumulative grade point average (CGPA) in particular, at postgraduate levels (e.g., master's degree), using and comparing different machine learning (ML) algorithms. …”
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Optimization Algorithms: A Comparison Study for Scheduling Problem at UIN Raden Fatah's Sharia and Law Faculty by Mustakim, ., Tri Basuki, Kurniawan, Misinem, ., Edi Surya, Negara, Izman, Herdiansyah

“…The rapid advancement of information and communication technology significantly impacts various sectors, including education, by enhancing administrative and academic processes through sophisticated algorithms and systems. …”
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Enhancing campus mobility: simulated multi-objective optimization of electric vehicle sharing systems within an intelligent transportation system frameworks by Aba Hussen, Omar S., Hashim, Shaiful J., Sulaiman Member, Nasri, Alhaddad, S.A.R., Ribbfors, Bassam Y., Umeda, Masanobu, Katamine, Keiichi

“…In addition to conventional decision variables, dynamic dual relocation thresholds and charge levels are introduced as decision variables to enhance optimization. …”
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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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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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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

“…Recently, predictive analytics research has grown in popularity in higher education because it provides helpful information to educators and potentially assists them in enhancing student achievement. …”
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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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Performance Prediction of Compulsory Subjects and Recommendation of Subject Options for China’s New College Entrance Examination by Long, Wang

“…Mathematics predictors centered on test anxiety, parents’ education levels, socioeconomic status (SES) and peer relationships, while English hinged on annual family income, parental involvement, and past English performance. …”
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Development of an explainable machine learning model for predicting depression in adults with type 2 diabetes mellitus: a cross-sectional SHAP-based analysis of NHANES 2009-2023 by Tang, Yan, Jia, Lei, Zhou, Junjun, Dou, Jin, Qian, Jingjuan, Yi, Xin, Soh, Kim Lam

“…The XGBoost model demonstrated the highest discriminative ability, with a validation area under the receiver operating characteristic curve of 0.888, accuracy of 0.834, F1-score of 0.715, sensitivity of 0.577, and specificity of 0.979, surpassing the performance of the other algorithms evaluated. SHapley Additive exPlanations analysis revealed gender, poverty-to-income ratio, sleep duration, smoking status, educational levels, race, age, high cholesterol, hypertension, and insulin use as the most influential predictors. …”
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Investigating computational thinking among primary school students in Terengganu using visual programming by Osmanullrazi, Abdullah

“…The findings of this study reveal that although the participants’ CT skills competency in the animation phase is in the Basic level, there is improvement of CT skills competency to the Developing level in the game phase. …”
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