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Paper Title : Prediction of Students Graduation Rate Using Mapreduce

ISSN : 2395-1303
Year of Publication : 2022
10.29126/23951303/IJET-V8I1P5

Authors: Christian Yonathan S, Imam Halim Mursyidin, Dede Irawan, Doni Prasetyo

         


Abstract
Colleges are now in competitive competition. Every college tries to improve academic quality and accreditation. One of the accreditation assessments of tertiary institutions is that students graduate on time, with criteria for passing fast, graduating right, passing late, and dropping out. This research was conducted using a classification method that was applied to predict the final grade of students. This study proposes the K-Nearest Neighbor (K-NN) algorithm with the most important attribute is GPA for each semester. In this study, using Hadoop-MapReduce tools with data selection contained in the Forlap Dikti Indonesia, for students Budi Luhur University Jakarta in 2009-2011. The information generated will display the graduation rate of students, from this research the academic side can make decisions regarding higher education policies

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Keywords
-— Hadoop, Mapreduce, KNN, Graduation, Student