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Penerapan Metode Naive Bayes Classifier (Nbc) Untuk Klasifikasi Kondisi Internal Program Studi
Author(s) -
Indhitya R. Padiku
Publication year - 2021
Publication title -
jurnal teknik
Language(s) - English
Resource type - Journals
ISSN - 2715-7660
DOI - 10.37031/jt.v19i1.118
Subject(s) - naive bayes classifier , bayes' theorem , computer science , classifier (uml) , machine learning , artificial intelligence , statistics , bayesian probability , mathematics , support vector machine
The low interest of prospective students in study programs at universities could be influenced by internal factors within the study program. These factors become the main variables in assessing the condition of the study program. For this reason, it is necessary to classify the internal conditions of the study program. A good method is needed in terms of accuracy and minimal misclassification to obtain the final classification results of the assessment. The purpose of this research is to classify the internal conditions of the study program. Classification of the internal conditions of the study program was carried out using the Naive Bayes Classifier (NBC) method which is a simple form of Bayesian Network with the assumption that all features are independent of each other. The NBC method shows an overall superior performance in terms of accuracy and misclassification rate. The NBC method can be used to determine the internal conditions of the study program, which could help identify factors that need to be addressed to increase the interest of prospective students enrolling in the study program.

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