<![CDATA[This study analyzes public sentiment and emotional dynamics related to the issue of “Pertamina Fuel Imports” across 1,429 online news headlines (December 2024 - November 2025). To address the absence of a standard corpus, this research developed a custom Indonesian-language lexicon in the energy domain to identify sentiment more accurately and contextually. The analysis results indicate a dominance of neutral coverage (86.35%), followed by negative (13.37%) and positive (0.28%) sentiment. In emotionally charged news, negative sentiment is highly dominant, with the frequency of emotions ranked as follows: anger (129), disgust (112), sadness (80), and fear (71), in stark contrast to the minimal presence of trust (5). Emotional trends shifted from anger related to issues of institutional integrity in the first half of 2025 to sadness and fear due to the tangible impact of fuel shortages in the second half of 2025. Statistical testing found no significant correlation between news volume and the proportion of negative sentiment (r = 0.2081; p > 0.05), confirming that public negativity is driven by the substance of the issue rather than the quantity of news coverage. As a practical implication, media outlets are encouraged to adopt solution-oriented journalism. The use of objective diction and data-driven narratives is crucial to reduce speculation, lower fear-related emotions, and rebuild public trust. REFERENSI Arioputro, S., Nugroho, A., Studi, P. S., & Komunikasi, I. (2024). Framing Media Tempo.Co Terhadap Berita Mengenai Pembangunan IKN. Interaksi Online, 13(1), 15-34. https://ejournal3.undip.ac.id/index.php/interaksi-online/article/view/48451 Bany, A. K. N. (2022). Analisis Sentimen Dan Deteksi Emosi Dengan Pendekatan Lexicon Pada Judul Berita Media Online Mengenai Covid-19 Di Indonesia. https://repository.uinjkt.ac.id/dspace/handle/123456789/64434 Ismandianto, I., Wahidar, T. I., & Devitriana, N. (2022). NILAI BERITA PADA PEMBERITAAN BISNIS PORTAL BERTUAHPOS.COM. Medium, 9(2), 136-147. https://doi.org/10.25299/medium.2021.vol9(2).7911 Ivan Lanin. (2025). Roda Emosi Plutchik. In L. Ivan (Ed.), Wikipedia. https://id.wikipedia.org/wiki/Berkas:Roda-Emosi-Plutchik.png. Kencana, W. H., Situmeang, I. V. O., Meisyanti, Rahmawati, & Nugroho, H. (2022). Penggunaan Media Sosial dalam Portal Berita Online. IKRAITH-HUMANIORA, 6(2), 136-145. https://doi.org/https://doi.org/10.37817/ikraith-humaniora.v6i2 Putri, A. S., Jannah, E., Vionanda, D., & Syafriandi. (2025). Implementation of Text Mining for Emotion Detection Using The Lexicon Method (Case Study: Tweets About Pemilu 2024). UNP Journal of Statistics and Data Science, 3(1), 100-107. https://doi.org/10.24036/ujsds/vol3-iss1/348 Subarkah, P., Kusuma, B. A., & Arsi, P. (2024). Sentiment Analysis On Renewable Energy Electric Using Support Vector Machine (Svm) Based Optimization. JITK (Jurnal Ilmu Pengetahuan Dan Teknologi Komputer), 10(2), 252-260. https://doi.org/10.33480/jitk.v10i2.5575 Wafa, I. (2025). Simak Sumber Utama Publik Indonesia dalam Mencari Berita 2025. GoodStats. https://data.goodstats.id/statistic/simak-sumber-utama-publik-indonesia- dalam-mencari-berita-2025-7TOae Wijaya, H., Sutjipto, V. W., Sary, M. P., & Komunikasi, I. (2025). Objektivitas Berita Kompas.com dalam Rubrik “Indeks Terpopuler” dalam Pemberitaan “100 Hari Kerja Prabowo-Gibran.” Sosial Dan Politik, 2(3), 138-146. https://doi.org/10.62383/demokrasi.v2i3.1079]]>
