Computer & Science Industrial Engineering Journal
Vol 11 No 2 (2024): Comasie Vol 11 No 2

IMPLEMENTASI DATA MINING UNTUK MEMPREDIKSI PENGARUH MEDIA SOSIAL TERHADAP SEMANGAT BELAJAR ANAK

Rahayu, Shintya (Unknown)
Koko Handoko (Unknown)



Article Info

Publish Date
09 Jan 2025

Abstract

In the digital era, the internet has become essential to daily life for all age groups, including children. Social media platforms like WhatsApp, YouTube, and TikTok are now integral to daily life, serving communication, news dissemination, entertainment, and promotional purposes. However, excessive use can lead to addiction and negatively impact learning, especially among children at the Al-Ikhlas Orphanage. This study employs data mining with the Naïve Bayes algorithm to analyze survey data on social media usage and its impact on learning enthusiasm. Naïve Bayes was selected for its high classification and prediction accuracy. Using RapidMiner software, the study found that social media significantly influences children's learning enthusiasm, achieving an accuracy rate of 85%. For the "strongly agree" class, precision is 92.86% and recall is 86.67%, while for the "disagree" class, precision is 66.67% and recall is 80.00%. The results indicate a significant influence of social media on children's learning enthusiasm.

Copyrights © 2024






Journal Info

Abbrev

comasiejournal

Publisher

Subject

Computer Science & IT

Description

Journal Comasie is a journal that combines 3 science namely informatics engineering, information systems and industrial engineering. The theme and scope can be seen in the scope section. This journal was created as a means of publicizing the results of research conducted by lecturers and students. ...