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All Journal PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat Jurnal Ilmiah METADATA
Tresna Yudha Prawira
Universitas Muhammadiyah Brebes
Religion Agriculture, Biological Sciences & Forestry Economics, Econometrics & Finance Education Law, Crime, Criminology & Criminal Justice Public Health Social Sciences

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SENTIMENT ANALYSIS OF THE NATIONAL MANDATE PARTY (PAN) IN YOUTUBE COMMENTS USING THE TF-IDF AND COSINE SIMILARITY APPROACHES Tresna Yudha Prawira; Fitri Ayuning Tyas; Azhar Basir
Jurnal Ilmiah METADATA Vol. 8 No. 1 (2026): Edition January 2026
Publisher : LPPM YPITI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47652/metadata.v8i1.937

Abstract

This study analyzed public sentiment towards the National Mandate Party (PAN) on YouTube comments using the Term Frequency Inverse Document Frequency (TF-IDF) approach and cosine similarity. The aim of the study was to map the tendency of public opinion into three categories: positive, negative, and neutral, and to evaluate the performance of this method compared to a simple lexicon-based approach. Comment data is obtained through the YouTube Data API, then processed through the stages of text cleanup, normalization, stopword removal, and stemming using Sastrawi. Word representation is formed with TF-IDF, while sentiment classification is done by calculating vector similarity using cosine similarity. The results of the analysis showed that neutral sentiment dominated at 63.2%, followed by negative sentiment at 20.7%, and positive sentiment at 16.1%.  The TF-IDF model  is able to classify neutral and negative comments quite well, although some positive comments are difficult to distinguish from neutral comments. These findings suggest that discussions about PAN on YouTube tend to be informative rather than emotional, with a higher tendency to criticize than support. In conclusion, the TF-IDF and cosine similarity methods are effective in providing an overview of public opinion with low computational complexity, while being a lightweight alternative to deep learning-based methods.
Family Link: Inovasi Edukasi Digital bagi Orang Tua dan Guru dalam Mengawasi Aktivitas Online Anak: Family Link: Digital Education Innovation for Parents and Teachers in Monitoring Children's Online Activities Yuniarti Lestari; Tresna Yudha Prawira; Umar Ghoni; Nur Wahyu Hidayat; Hidayatur Rakhmawati
PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat Vol. 11 No. 5 (2026): PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat
Publisher : Institute for Research and Community Services Universitas Muhammadiyah Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33084/pengabdianmu.v11i5.12154

Abstract

The increase in internet access among early childhood in rural areas is often not accompanied by adequate parental supervision skills, thereby increasing the risk of gadget addiction and exposure to negative content. This community service program aims to improve the digital literacy of parents and teachers at RA Al Manshur, Bangbayang Village, by optimizing parental mediation. The implementation method includes socialization on the urgency of digital supervision, technical training on using the Google Family Link application, and direct practical simulations guided by a team of lecturers and students. Participants consisted of 27 parents and 3 teachers. Evaluation results showed an average increase in participants' understanding of 35%, with 85% feeling more confident in monitoring their children's online activities. The program has reached 60% completion and has proven effective in equipping parents with the tools to create a safe, healthy digital environment for children.
Co-Authors Azhar Basir Fitri Ayuning Tyas Hidayatur Rakhmawati Nur Wahyu Hidayat Umar Ghoni Yuniarti Lestari