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All Journal Manaruko: Jurnal Pengabdian Masyarakat Jurnal Nasional Teknologi Informasi dan Aplikasinya
Syalsabilla Valentisyesa
Universitas Multi Data Palembang
Computer Science & IT Economics, Econometrics & Finance Education Engineering Social Sciences Other

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Analisis Sentimen Pengguna X dan YouTube Terhadap Carmen Hearts2Hearts Menggunakan Metode IndoBERT Fellycia Caroline; Syalsabilla Valentisyesa; Muhammad Rizky Pribadi
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 4 No. 3 (2026): JNATIA Vol. 4, No. 3, Mei 2026
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JNATIA.2026.v04.i03.p23

Abstract

The rapid growth of social media has increased the amount of public opinion expressed online, particularly on platforms such as X and YouTube, where users actively share their views regarding public figures and entertainment topics. This study aims to analyze public sentiment toward Carmen, a member of the K-pop group Hearts2Hearts, using the IndoBERT model for sentiment classification. Data were collected from X and YouTube comments through web scraping techniques and combined into a single dataset to obtain more diverse opinions. The research process involved several stages, including text preprocessing, manual sentiment labeling, dataset splitting, model training, and evaluation. The preprocessing stage consisted of duplicate data removal, case folding, noise removal, tokenization, stopword removal, and stemming to improve data quality before classification. The dataset was categorized into three sentiment classes: positive, neutral, and negative, then divided into training and testing data using an 80:20 ratio. The IndoBERT model was trained using transformer-based deep learning to understand the context of Indonesian-language text more effectively. Evaluation results showed that the model achieved an accuracy of 72.41%, precision of 75.82%, recall of 72.41%, and F1-score of 71.15%, indicating that IndoBERT performs effectively in classifying sentiment on Indonesian social media data despite challenges such as informal language and ambiguous expressions.
Edukasi Pencegahan Phising Melalui Peningkatan Literasi Keamanan Siber Di SMP Negeri 61 Palembang Siti Fatimah Az Zahrah; Migel Orvin Febryan; Siska Amelia; Syalsabilla Valentisyesa; Joseph Eduard Uly Loni; Iis Pardesan; Dafid
Manaruko: Jurnal Pengabdian Masyarakat Vol. 5 No. 1 (2026): Manaruko: Jurnal Pengabdian Masyarakat
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/manaruko.v5i1.99

Abstract

Cybercrime in the form of phishing has become a growing threat among students due to the high intensity of internet and social media usage without adequate digital security awareness. This community service activity aimed to improve students' understanding of phishing prevention through cyber security literacy education at SMP Negeri 61 Palembang. The activity involved 26 junior high school students and was conducted using educational methods consisting of material presentations, interactive discussions, case studies, and simple simulations. The materials covered the definition of phishing, types of attacks, identification of suspicious links, protection of personal data, and preventive measures in digital activities. The results showed that participants experienced increased understanding and awareness regarding phishing threats and digital security practices. Participants were also able to identify phishing characteristics and apply preventive actions in daily internet usage. This activity concluded that interactive cyber security education can effectively improve digital literacy and foster safer digital behavior among students.
Co-Authors Dafid Fellycia Caroline Iis Pardesan Joseph Eduard Uly Loni Migel Orvin Febryan Muhammad Rizky Pribadi Siska Amelia Siti Fatimah Az Zahrah