Prediksi Kelulusan Siswa SDN 016528 BP. Mandoge dengan Metode Naïve Bayes

Authors

  • Cetryn Ayu Diah Lestari Sekolah Tinggi Manajemen Informatika dan Komputer Royal
  • Juwita Sari Sekolah Tinggi Manajemen Informatika dan Komputer Royal
  • Sri Wulandari Sekolah Tinggi Manajemen Informatika dan Komputer Royal

Keywords:

Graduation, Data Mining, Naïve Bayes

Abstract

Graduation marks the completion of a certain level of schooling. This study aims to predict the graduation of students at SDN 016528 BP Mandoge based on their abilities. The goal of this research is to reduce the rate of student failure to graduate by making predictions based on examination scores collected by the institution. The method used in this study is Naive Bayes, a technique in Data Mining that utilizes probability and statistics to predict future outcomes based on previous data. This method was chosen due to its advantage in predicting graduation rates from concrete data, ensuring the results are reliable and applicable for future predictions. The dataset used in this study includes graduation data for SDN 016528 BP Mandoge students for the 2019/2020 academic year, comprising 171 students, with 120 students used for training data and 51 students for testing data, achieving a model accuracy of 98%.

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Published

2024-07-31

How to Cite

Lestari, C. A. D., Sari, J., & Wulandari, S. (2024). Prediksi Kelulusan Siswa SDN 016528 BP. Mandoge dengan Metode Naïve Bayes . Journal Of Artificial Intelligence And Data Engineering, 1(1), 21–27. Retrieved from https://journal.beta-academia.com/index.php/jaide/article/view/15