AULIA SALSABILA, NPM 2009100012 (2024) IMPLEMENTATION OF THE NAÏVE BAYES ALGORITHM TO PREDICT NEW STUDENT ADMISSIONS. Tugas_Akhir (Artikel) Building Of Informatics, Technology And Science (Bits), 6 (1). pp. 421-429. ISSN 2685-3310 (e-ISSN)/ 2684-8910 (p-ISSN)
![[img]](http://repository.ulb.ac.id/style/images/fileicons/text.png) |
Text
COVER FULL.pdf Download (3MB) |
|
Text
ARTIKEL.pdf Download (661kB) |
Abstract
New student admissions are critical to the success of an educational institution because they determine the existence and financial sustainability of that institution. The number of prospective students who register changes every year. The school cannot anticipate the number of students who will come. Additionally, data on prospective students who enroll is collected annually without being analyzed to extract valuable information. The school must make predictions to estimate the number of new students in the next school year. Predictions are essential for effective planning, both in the long and short term. This research aims to apply the Naïve Bayes algorithm with Gaussian type to predict new student admissions. To find out whether the Naïve Bayes algorithm works well, an evaluation matrix is used. The methods applied include the dataset collection process, data preprocessing, split data training and testing, feature engineering, the implementation of Naïve Bayes, and results evaluation. The dataset is divided into 70% training data and 30% testing data. The research results show an accuracy score of 86.11% during training and an accuracy score of 90.62% during model testing, with an increase of 4.51%. These results show that there is no indication of overfitting in the machine learning algorithm used. The evaluation matrix produces an accuracy score of 90.62%, precision of 100%, recall of 90.62%, and f1-score of 95.08%. From the results of the evaluation matrix scores, it can be concluded that the naive Bayes algorithm with Gaussian type succeeded in predicting new student admissions well. Keywords : Admission; Gaussian; Naïve Bayes; New Student; Prediction
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Admission; Gaussian; Naïve Bayes; New Student; Prediction |
| Subjects: | Z Bibliography. Library Science. Information Resources > ZA Information resources |
| Divisions: | Fakultas Sains Dan Teknologi > Sistem Informasi |
| Depositing User: | Unnamed user with email repository@ulb.ac.id |
| Date Deposited: | 27 Aug 2024 08:33 |
| Last Modified: | 27 Aug 2024 08:33 |
| URI: | http://repository.ulb.ac.id/id/eprint/967 |
Actions (login required)
 |
View Item |
