Open AccessImplementation of Data Mining In Predicting the Study Period of Student Using the Naïve Bayes Algorithm
Author(s) -
Sri Wahyuni,
Murni Marbun
Publication year - 2020
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/769/1/012039
Subject(s) - naive bayes classifier , bachelor , accreditation , bayes' theorem , period (music) , mathematics education , value (mathematics) , research object , computer science , algorithm , mathematics , statistics , machine learning , medical education , geography , medicine , bayesian probability , physics , archaeology , regional science , support vector machine , acoustics
The period of study of students is one of the parameters in the assessment of accreditation of university. Pembangunan Panca Budi University as one of the best institutions in North Sumatra needs to predict the period of study of students in order to know the strategies implemented so that students graduate on time. This study predicts the period of study using the Naïve Bayes Data Mining Algorithm method to students of the Pembangunan Panca Budi University of Computer System study program bachelor program with a study period of 4 years. Application designed using Naïve Bayes algorithm that works based on the shortest distance between two objects by determining the value of k. The value of k is a parameter to determine the closest distance between a new object and an old object. The data used as variables are student academic data, GPA for the first from 4 semesters, the average value of the National Examination during high school, and majors during high school. The results of the study showed that the data mining application that was designed could predict the period of study of students at the Pembangunan Panca Budi University.