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Pre FIC: Predict ability of Faculty Instructional Performance through Hybrid Prediction Model
Published Online: March-April 2021
Pages: 18-19
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No DOIAbstract
: The Higher Education Institutions have amplifiedthepracticeofincorporatingdatamininginextractinginformation from the data comparing to informational setting. AsoneoftheregardedquestofHEIs,predictingfacultyinstructionalperformance has simplified; and the accuracy of the result has becomemorereliable through the usage of dataminingalgorithmsandtechniques.Thisstudyproposedahybridmodelinpredicting the instructive display of staff in the fourStateUniversitiesandColleges(SUC)inCaragaRegion,Philippinesbyintegratingk-meanssegmentationontheC4.5algorithmpriortoprediction.Atotalof597recordsofstudent-respondents was used for reenactment using the 10-foldscrossvalidationscheme.Simulationresultshowedthatwithintegrationofk-meansalgorithm,theidentifiedpredictionaccuracy of 86.09% using C4.5 estimation alone has extended to87.93%.Futureresearchersmayutilizeotherhybridalgorithmsinthe questonimprovingthe composing ofeducationaldatamining.
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