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All Journal DISTANCE: Journal of Data Science, Technology, and Computer Science
Andre Edlin Siahaan
STMIK Pelita Nusantara
Computer Science & IT

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Application of the Naive Bayes Algorithm to Predict New Student Admissions at Mulia Pratama Vocational School in the Digital Age Andre Edlin Siahaan; Agustina Simangunsong
DISTANCE: Journal of Data Science, Technology, and Computer Science Vol 1 No 1 (2021): December : 2021
Publisher : Putaka Timur Publisher

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Abstract

The development in the era of globalization and the rapid progress in the field of information technology has had a considerable influence both in the field of education. Several problems can be explained related to the achievement of results in predicting the results of new student admissions at SMK Mulia Pratama in the digital era. The promotion is quite complicated because there is no target for the results of new student admissions so the promotion does not know the achievement of new student admissions who are registered for each promotion. To solve this problem, the naive Bayes method is used. Naïve Bayes is an algorithm that can be used to predict the results of new student admissions that can be categorized as achieved or not achieved. The data was used in this study from January to December 2018. From the results of the application of the nave Bayes method, the highest probability value is in class P(X). Receipt of acceptance prediction = No so that it can be concluded that the results of acceptance are included in the classification of "No" meaning that every new acceptance improves.
Co-Authors Simangunsong, Agustina