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Antonny Antonny
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Control & Systems Engineering Decision Sciences, Operations Research & Management Energy Engineering Industrial & Manufacturing Engineering

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Journal : Journal of Industrial Engineering Management

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APPLICATION OF PREDICTION TIME OF GRADUATION USING THE NAÏVE BAYES ALGORITHM WITH THE PYTHON PROGRAM Priskila Christine Rahayu; Eric Jobiliong; Antonny Antonny
Journal of Industrial Engineering Management Special edition of Seminar Nasional Teknik dan Manajemen Industri 2020
Publisher : Center for Study and Journal Management FTI UMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33536/jiem.v0i0.773

Abstract

Accreditation is a process to ensure the quality of a university and study program. There are several factors that determine the quality standard of accreditation. One of them is the time of graduation. However, there is no means that can be used to predict early student graduation time. Therefore, this study aims to create a means that can predict early graduation time. In this study, data mining methods were used, namely the Naïve Bayes algorithm. After that, data processing and application development will be carried out using the Python program. The data used in the data mining process is three years of historical data and the data used for the trial are active student data for the second and third years. There are 5 types of patterns with an accuracy value of 81%, 87%, 92%, 92%, and 95%.
Co-Authors Eric Jobiliong Rahayu, Priskila Christine