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Thamrin Thamrin
Institut Bisnis Informasi Teknologi Dan Bisnis
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Implementation System for Cluster Analysis and Data Sentiment Using the K-Means Method to Determine the Most Discussed Topics Wanra Tarigan; Djoni; Thamrin; Lismardiana
Jurnal Penelitian Pendidikan IPA Vol 12 No 3 (2026): In Progress
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v12i3.14838

Abstract

The Community Activities Restrictions Enforcement (CARE) government rule, that is currently a matter of public concern, was implemented in 2021. Community Activities Restrictions Enforcement (CARE) highlights the community's pros and cons. Twitter and YouTube are social media that facilitate direct user expression. The material offered on social media platforms Twitter and YouTube is likewise quite diversified. Therefore, an automatic approach for topic detection is required, such as Mini Batch K-means Clustering, which facilitates user access to information. This study employs the Mini Batch method, which utilizes just a limited set of data for the clustering procedure. Based on testing with the Sum of Squared Error, this study's clustering results for tweet data including the phrase Community Activities Restrictions Enforcement (CARE) produced 12 cluster groups. The clustering results will be represented using Word Cloud, and the system will display the percentage of words based on Word Cloud.
Co-Authors Agus Susanto Andi Andi Deva Djohan Djoni Duffin IKA PUSPA SATRIANNY Jasael Simanullang Kosasih, Hengky Lismardiana Nasib Novita Widjaya Rafika S. Sembiring Rafika Sari Br Sembiring Ratih Amelia Stefvy, Stefvy Tina Linda Tulus Pramita Sihaloho Victor Saputra Ginting Wanra Tarigan Wijaya, Elyzabeth Wily Julitawaty