IMPLEMENTATION OF THE NAÏVE BAYES METHOD TO DETERMINE STUDENT INTEREST IN GAMING LAPTOPS

Rico Fadly Nasution, NPM 2007100014 (2023) IMPLEMENTATION OF THE NAÏVE BAYES METHOD TO DETERMINE STUDENT INTEREST IN GAMING LAPTOPS. Tugas_ Akhir (Artikel) Sinkron : Jurnal dan Penelitian Teknik Informatika, 8 (3). pp. 1709-1723. ISSN 2541-2019 (e-ISSN) / 2541-044X (p-ISSN)

	Text COVER AND SERTIFIKAT.pdf Download (872kB)
	Text ARTIKEL.pdf Download (600kB)

Abstract

The development of the times resulted in the development of technology to date. With the existence of technology, many people have used technology to help their daily activities. In this study, the author will discuss the technology that is often used by students to help them with their assignments, namely laptops. Laptop is a technology that has been widely used by students, teachers and the public. Having a laptop can make things easier. Until now, each laptop brand continues to develop their laptop production laptops with good specifications. Until now, almost all laptop brands have made gaming laptops that are actually intended for people-people who play games. But with good specifications, gaming laptops can also be used for daily activities. With an attractive design and good specifications, of course you can attract student and public interest in gaming laptops. Therefore the authors made a study of student interest in gaming laptops. With good design and specifications on gaming laptops, the author aims to classify the number of students who are interested and not interested in gaming laptops. The classification will be carried out using the Naïve Bayes method with the number of sample data used as many as 100 student data in data mining. The classification results obtained were 55 students (55% representation) interested in gaming laptops and 45 students (45% representation) had no interest in gaming laptops. The results show that not all students are interested in gaming laptops, even though they have laptops design and great specs. Keywords: Classification, Data Mining, Gaming Laptops, Naïve Bayes, Students

Item Type:	Article
Uncontrolled Keywords:	Classification, Data Mining, Gaming Laptops, Naïve Bayes, Students
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > T Technology (General)
Divisions:	Fakultas Sains Dan Teknologi > Informatika Komputer
Depositing User:	Unnamed user with email repository@ulb.ac.id
Date Deposited:	17 Nov 2023 03:08
Last Modified:	17 Nov 2023 03:08
URI:	http://repository.ulb.ac.id/id/eprint/503

Actions (login required)

View Item