MACHINE LEARNING USING SCIKIT-LEARN FOR CLASSIFY STUDENTS GRADUATION

Purwono Prastetyawan

Abstract


In this article we discuss the use of scikit-learn, library of machine learning with python, to classify the study period of students with graduated category on time or not. The proposed classification method is using Naive Bayes Classifier, K-Nearest Neighbor, Support Vector Machine, Decision Trees, and others Classifiers. Discussion includes which method is better to apply to the dataset obtained from the pre-processing of student data from the college in Lampung from 2008 to 2013. The information obtained can be used as a model to predict the first 2-year-old students, whether with the same class pattern will pass on time or not. This is needed to provide early warning to the students to improve themselves.

Keywords—Machine Learning; Classification; Scikit-Learn;


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ICSTIEM: International Conference on Sosial Technological, Innovation, Economics and Management, Penerbit Fakultas Ilmu Sosial dan Ilmu Politik (http://www.jurnal.saburai.ac.id/index.php/ICSTIEM/index).