Open AccessPrediction of student graduation accuracy using decision tree with application of genetic algorithms
Author(s) -
Arif Maulana
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1073/1/012055
Subject(s) - graduation (instrument) , selection (genetic algorithm) , genetic algorithm , scope (computer science) , decision tree , institution , computer science , decision tree learning , asset (computer security) , machine learning , algorithm , mathematics , political science , computer security , law , programming language , geometry
Many of students who can’t complete the study promptly is a problem that needs to be faced with a fast and effective way. In the student’s education system is an important asset to the note the graduation rate of students promptly. Predicting graduation is very important for the institution to determine the strategic policies for the institution. The scope of the study is limited in performing accurate comparison between studies that only use Genetic Algorithm method and the research-based Genetic Algorithm using forward selection. Here we can conclude that the value of the highest accuracy is there in the Genetic Algorithm-based method Forward selection. Thus the Genetic Algorithm method with the selection of attribute-based Forward Selection is the best method for solving a problem in the prediction accuracy of graduation.