Optimasi Naïve Bayes Dan Algoritma Genetika Untuk Prediksi Penerimaan Beasiswa Pendidikan Pada SMP Utama

Nining Suryani, Evy Priyanti

Abstract


Educational scholarships are one of the efforts to sustain students in getting a better education. Not a few students drop out in the middle of the road or cannot continue their education at the same level or higher level. Selection according to the criteria for scholarship recipients is important so that scholarships are on target. Similar to Depok Primary Middle School, educational scholarships are provided by schools based on 9 criteria for scholarship recipients, namely parent status, parent work, rented house, home appliances, vehicles, parents 'savings, parents' jewelry, cellphones and pocket money. With the number of prospective scholarship recipients there is an algorithm needed to accurately predict students who are entitled to scholarships. With the naïve bayes algorithm, accuracy is 77.50% in predicting scholarship recipients based on the criteria found in students. The use of genetic algorithms is done to get a more optimal level of accuracy. This is evidenced by the accuracy of 83.33%.


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DOI: https://doi.org/10.31294/jtk.v5i2.5343

Copyright (c) 2019 Nining Suryani, Evy Priyanti

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ISSN: 2442-2436 (print), and 2550-0120


 dipublikasikan oleh LPPM Universitas Bina Sarana Informatika Jakarta

Jl. Kramat Raya No.98, Kwitang, Kec. Senen, Kota Jakarta Pusat, DKI Jakarta 10450
Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License