Matches in SemOpenAlex for { <https://semopenalex.org/work/W4313444395> ?p ?o ?g. }
Showing items 1 to 72 of
72
with 100 items per page.
- W4313444395 endingPage "651" @default.
- W4313444395 startingPage "639" @default.
- W4313444395 abstract "Educational data mining (EDM) is a process of determining meaningful and useful knowledge from large amounts of data that are dug up from educational locations. The purpose of EDM is to discuss tools, techniques, and design research for gleaning meaning from large data sets on the fly. EDM is a research area that applies to machine learning, data mining, and pattern recognition techniques. Predicting student performance is an application of EDM to analyse student results. The paper aims to predict students’ results and compare different classification algorithms, considering educational data from Shadan Women’s College of Engineering and Technology from the past four years in a directive to predict and analyse students’ performance by identifying different data mining techniques such as J48 and logistic regression algorithms using the WEKA tool. This paper will contribute to constructing classification models for the ‘SWCET’ data set consisting of 627 different instances with eight different attributes for the first year, second year 376 instances, third year 360 instances, and final year 344 instances. It evaluates and compares implementation results to improve prediction accuracy. This study's findings, in particular, provide more insight for evaluating student performance with 100% accuracy using J48 and the logistic regression algorithm, which yields 99.84%. The student's performance will be advantageous to developing the quality of education and knowledge to drop the failure rate. All these things will help to improve the quality of the college." @default.
- W4313444395 created "2023-01-06" @default.
- W4313444395 creator A5035590321 @default.
- W4313444395 creator A5076421999 @default.
- W4313444395 date "2023-01-01" @default.
- W4313444395 modified "2023-10-14" @default.
- W4313444395 title "Analysis of SWCET Student’s Results Using Educational Data Mining Techniques" @default.
- W4313444395 cites W2373555655 @default.
- W4313444395 cites W2550211657 @default.
- W4313444395 cites W2566084804 @default.
- W4313444395 cites W2891982616 @default.
- W4313444395 cites W2992983027 @default.
- W4313444395 cites W3033604406 @default.
- W4313444395 doi "https://doi.org/10.1007/978-981-19-2358-6_58" @default.
- W4313444395 hasPublicationYear "2023" @default.
- W4313444395 type Work @default.
- W4313444395 citedByCount "0" @default.
- W4313444395 crossrefType "book-chapter" @default.
- W4313444395 hasAuthorship W4313444395A5035590321 @default.
- W4313444395 hasAuthorship W4313444395A5076421999 @default.
- W4313444395 hasConcept C111472728 @default.
- W4313444395 hasConcept C111919701 @default.
- W4313444395 hasConcept C119857082 @default.
- W4313444395 hasConcept C12267149 @default.
- W4313444395 hasConcept C124101348 @default.
- W4313444395 hasConcept C138885662 @default.
- W4313444395 hasConcept C151956035 @default.
- W4313444395 hasConcept C154945302 @default.
- W4313444395 hasConcept C177264268 @default.
- W4313444395 hasConcept C199360897 @default.
- W4313444395 hasConcept C2522767166 @default.
- W4313444395 hasConcept C2777598771 @default.
- W4313444395 hasConcept C2779530757 @default.
- W4313444395 hasConcept C41008148 @default.
- W4313444395 hasConcept C52001869 @default.
- W4313444395 hasConcept C52003472 @default.
- W4313444395 hasConcept C98045186 @default.
- W4313444395 hasConceptScore W4313444395C111472728 @default.
- W4313444395 hasConceptScore W4313444395C111919701 @default.
- W4313444395 hasConceptScore W4313444395C119857082 @default.
- W4313444395 hasConceptScore W4313444395C12267149 @default.
- W4313444395 hasConceptScore W4313444395C124101348 @default.
- W4313444395 hasConceptScore W4313444395C138885662 @default.
- W4313444395 hasConceptScore W4313444395C151956035 @default.
- W4313444395 hasConceptScore W4313444395C154945302 @default.
- W4313444395 hasConceptScore W4313444395C177264268 @default.
- W4313444395 hasConceptScore W4313444395C199360897 @default.
- W4313444395 hasConceptScore W4313444395C2522767166 @default.
- W4313444395 hasConceptScore W4313444395C2777598771 @default.
- W4313444395 hasConceptScore W4313444395C2779530757 @default.
- W4313444395 hasConceptScore W4313444395C41008148 @default.
- W4313444395 hasConceptScore W4313444395C52001869 @default.
- W4313444395 hasConceptScore W4313444395C52003472 @default.
- W4313444395 hasConceptScore W4313444395C98045186 @default.
- W4313444395 hasLocation W43134443951 @default.
- W4313444395 hasOpenAccess W4313444395 @default.
- W4313444395 hasPrimaryLocation W43134443951 @default.
- W4313444395 hasRelatedWork W2141452888 @default.
- W4313444395 hasRelatedWork W2890871066 @default.
- W4313444395 hasRelatedWork W2961085424 @default.
- W4313444395 hasRelatedWork W2962970583 @default.
- W4313444395 hasRelatedWork W3108967136 @default.
- W4313444395 hasRelatedWork W3176795340 @default.
- W4313444395 hasRelatedWork W3185179407 @default.
- W4313444395 hasRelatedWork W4248765614 @default.
- W4313444395 hasRelatedWork W4313247650 @default.
- W4313444395 hasRelatedWork W4365813386 @default.
- W4313444395 isParatext "false" @default.
- W4313444395 isRetracted "false" @default.
- W4313444395 workType "book-chapter" @default.