ANALISIS SENTIMEN BERDASARKAN KOMENTAR POSTINGAN REELS INSTAGRAM @SAHABATICW "RAPOR NOL 1 TAHUN PRABOWO - GIBRAN"

Mulyanto, Bayu Sukma Putra and Sukma, Bayu (2026) ANALISIS SENTIMEN BERDASARKAN KOMENTAR POSTINGAN REELS INSTAGRAM @SAHABATICW "RAPOR NOL 1 TAHUN PRABOWO - GIBRAN". Undergraduate thesis, Universitas Muhammadiyah Malang.

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Abstract

This study aims to evaluate Instagram users' sentiments toward the Reels video uploaded by the @sahabaticw account entitled *"Rapor Nol 1 Tahun Prabowo–Gibran" (Zero Report Card: One Year of Prabowo–Gibran).* The study seeks to identify public opinion by classifying comments into three sentiment categories—positive, neutral, and negative—and to assess the relevance of the comments to discussions regarding the performance of the Prabowo–Gibran administration. The research examines comments posted on the Reels video by various Instagram users, some of which are relevant to the government's performance while others are not. Therefore, the study aims to identify the attitudes and tendencies expressed by users in their comments, with a particular focus on opinions regarding the performance of the Prabowo–Gibran administration. This research employs a quantitative descriptive content analysis approach and involves two independent coders to ensure the consistency and reliability of the coding process. A total of 122 comments were analyzed. The first coder classified 44 comments (36.1%) as positive, 31 comments (25.4%) as neutral, and 47 comments (38.5%) as negative. Meanwhile, the second coder classified 37 comments (30.3%) as positive, 30 comments (24.6%) as neutral, and 55 comments (45.1%) as negative. The relatively balanced distribution of data across sentiment categories and evaluation aspects contributed to the model's ability to identify sentiment polarity more consistently. To facilitate the coding process, the researchers used a coding sheet containing comments from various accounts along with predefined indicators and rating scales. The findings of this study are expected to provide an empirical overview of public opinion patterns in digital communication spaces and contribute to the development of research on political communication and social media analysis in the context of contemporary political discourse.

Item Type: Thesis (Undergraduate)
Student ID: 201910040311323
Keywords: Sentiment Analysis, Holsti's Reliability Formula, Spiral of Silence Theory, Social Media, Instagram
Subjects: H Social Sciences > H Social Sciences (General)
J Political Science > JA Political science (General)
Divisions: Faculty of Social and Political Science > Department of Communication Science (70201)
Depositing User: 201910040311323 bayusukma
Date Deposited: 20 Jul 2026 04:08
Last Modified: 20 Jul 2026 04:08
URI: https://eprints.umm.ac.id/id/eprint/32248

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