Search Results - (( student classification clustering algorithm ) OR ( java implication based algorithm ))*

Combining cluster quality index and supervised learning to predict students’ academic performance by Suhaila Zainudin, Rapi’ah Ibrahim, Hafiz Mohd Sarim

“…The best cluster is further analysed using classification to predict students’ academic performance. …”
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Automatic Clustering of Students by Level of Situational Interest Based on Their EEG Features by Othman, E.S., Faye, I., Hussaan, A.M.

“…The formed clusters are then used as ground truth for classification purposes. …”
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An analysis of fuzzy clustering algortihms for suggestion of supervisor and examiner of thesis title by Suhaimi, Azrina

“…The index terms are then clustered using Fuzzy clustering algorithms based on similarity. …”
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A Multi-Criteria Decision-Making Approach for Targeted Distribution of Smart Indonesia Card (KIP) Scholarships by Komang, Aryasa

“…Third, the classification of scholarship recipient eligibility was performed by comparing the C5.0 and K-Nearest Neighbors (KNN) algorithms. …”
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An application of predicting student performance using kernel k-means and smooth support vector machine by Sajadin, Sembiring

“…The data collection from student academic databases and surveyed the psychometric factors of undergraduatestudentin semester 3 sessions 2007/2008 at Universiti Malaysia Pahang.Theresultof this study indicatesa positive correlation between the proposed predictor variables and the students performance.These predictor variables contributesignificantly in increasing or decreasing student performance that is equalto52.2%(R2=0.522).The studyalsofound the cluster model of students based on their performance. …”
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Classification and prediction analysis for weld bead surface quality using feature extraction and mahalanobis-taguchi system by Nolia, Harudin, Muhammad Ikmal Hafiz, Mohd Yusof, Zulkifli, Marlah@Marlan, Faizir, Ramlie, Wan Zuki Azman, Wan Muhamad, Mohd Yazid, Abu, Zamzuraida, Baharum

“…A comprehensive threshold analysis improves classification accuracy, minimizing the risk of misclassification. …”
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Enhancing teaching and learning through data-driven optimization of servicing code demand and lecturer allocation using WEKA analysis by Rochin Demong, Nur Atiqah, Mohamed Razali, Murni Zarina, Kamaruddin, Juliana Noor, Shamsuddin, Sazwan, Awang, Nor Ain, Kamarudin, Norjuliatie, Wan Othman, Noor Faradilla

“…Complementary K-Means clustering grouped the data into two major clusters, indicating that a clear differentiation between economic-based and entrepreneurship-based courses in terms of student enrolment volume and approval distribution. …”
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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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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush