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All Journal JOMLAI: Journal of Machine Learning and Artificial Intelligence
Rafika Dewi
STIKOM Tunas Bangsa, Pematangsiantar, Indonesia
Computer Science & IT Engineering

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Classification of Internet Addiction Levels in Students Using the Naïve Bayes Algorithm Fakhriyah Zulfah Parinduri; Rafika Dewi; Susiani Susiani
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 1 No. 3 (2022): September
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (489.824 KB) | DOI: 10.55123/jomlai.v1i3.965

Abstract

The presence of the internet on students has a big influence on science and technology which makes the internet as an additional insight to find the information needed, apart from being a source of information, students also access the internet as a means of entertainment. So that it makes students last longer in front of gadgets or computers continuously. The purpose of this study is to determine whether students are indicated by internet addiction and provide input to STIKOM Tunas Bangsa to make policies that use the internet as a learning process so that internet addiction does not occur excessively. Because it is very influential in the learning process to add insight about science and technology to students. The subjects carried out by this study were students who were studying at STIKOM Tunas Bangsa. Therefore, the research was conducted using the Naïve Bayes algorithm classification, in which the data was obtained using a questionnaire distributed to students. The subjects carried out by this study were students who were studying at STIKOM Tunas Bangsa. Therefore, the research was conducted using the Naïve Bayes algorithm classification, in which the data was obtained using a questionnaire distributed to students. It is hoped that this research can be information for students to be able to maintain self-control in utilizing various entertainments on the internet.
Co-Authors Fakhriyah Zulfah Parinduri Susiani Susiani