IMPLEMENTASI DATA MINING UNTUK MEMPREDIKSI PENGARUH MEDIA SOSIAL TERHADAP SEMANGAT BELAJAR ANAK
DOI:
https://doi.org/10.33884/comasiejournal.v11i2.9046Keywords:
Data Mining, Naïve Bayes, RapidMiner, Learning Enthusiasm, Social MediaAbstract
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.
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