PREDIKSI PENERIMA BEASISWA UNIVERSITAS MUHAMMADIYAH PRINGSEWU DENGAN MENGGUNAKAN ALGORITMA NAÏVE BAYES

Published: Dec 30, 2022

Abstract:

Scholarship assignment is an operations management problem facing university administrators, which is usually resolved based on the administrator's personal experience. This research proposes an incentive method inspired by dynamic programming to replace the traditional decision-making process in scholarship assignments. The aim is to find the optimal scholarship assignment scheme with the highest equity while taking into account practical constraints and equity requirements. The methodology used in determining scholarship recipients at Pringsewu Muhammdiyah University uses the Naïve Bayes algorithm. The research results show that the Naïve Bayes algorithm with K-10 and K-Fold Cross Validation with k=10 has an accuracy of 95.01%. This shows that Naïve Bayes is an algorithm that can predict.

Keywords:
1. Datamining
2. Naïve Bayes
3. Prediction
4. Scholarship
Authors:
1 . Bambang Triraharjo
2 . Roby Novianto
3 . Baskoro
How to Cite
Triraharjo, B., Novianto, R., & Baskoro. (2022). PREDIKSI PENERIMA BEASISWA UNIVERSITAS MUHAMMADIYAH PRINGSEWU DENGAN MENGGUNAKAN ALGORITMA NAÏVE BAYES. Sienna, 3(2), 48–58. Retrieved from https://jurnal.umko.ac.id/index.php/sienna/article/view/1055

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