Classification of MTI Student Thesis Documents at Bina Darma University Palembang Using Naïve Bayes

Dhea Noranita, Putri and Tri Basuki, Kurniawan and Edi, Suryanegara and Yesi Novaria, Kunang and Misinem, Misinem (2022) Classification of MTI Student Thesis Documents at Bina Darma University Palembang Using Naïve Bayes. Journal of Data Science, 2022 (17). pp. 1-12. ISSN 2805-5160 (Submitted)

Text Vol.2022_017.pdf Download (704kB)

Abstract

One of the resources that students might use as a guide when conducting research is the university library. A research thesis written by former students serves as reference material. Students must arrange the thesis documents following the concept or topic of their research because they are typically organized by faculty and department. Researchers, therefore, attempt to classify student thesis documents according to themes or subjects so that students can be more precise in their search for references to themes or topics that relate to the research they will do. The title, abstract, and important keta from the thesis document will be used as the study's data, which will then be classified using the best classification technique, the Naive Bayes Classification (NBC) approach. The learning stage and the testing stage are the two steps used in the naive Bayes classifier method's classification process. After establishing the Category and the quantity of data learning documents, probability calculations were then carried out for each category.

Item Type:	Article
Subjects:	H Social Sciences > H Social Sciences (General) H Social Sciences > HF Commerce
Divisions:	Faculty of Information Technology
Depositing User:	Unnamed user with email masilah.mansor@newinti.edu.my
Date Deposited:	15 Dec 2022 09:43
Last Modified:	15 Dec 2022 09:43
URI:	http://eprints.intimal.edu.my/id/eprint/1692

Actions (login required)

View Item