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All Journal Sinergi International Journal of Communication Sciences Sinergi International Journal of Law International Journal of Oil Palm
Aidatul Fitriyah
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Decision Sciences, Operations Research & Management Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice

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Harnessing AI for Climate Change Communication: Analyzing Public Perception through NLP and Machine Learning Rahman, Gohar; Aidatul Fitriyah
Sinergi International Journal of Communication Sciences Vol. 3 No. 2 (2025): May 2025
Publisher : Yayasan Sinergi Kawula Muda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61194/ijcs.v3i2.683

Abstract

This study explores how Artificial Intelligence (AI), particularly Natural Language Processing (NLP) and machine learning, can be leveraged to analyze public discourse on climate change and improve climate communication strategies. Focusing on four key questions, the research examines how AI classifies public sentiment, identifies dominant topics, detects framing structures, and generates actionable insights to inform targeted communication. Over one million climate-related posts were collected from Twitter and Facebook between January and June 2024. Sentiment analysis using a fine-tuned BERT model categorized posts into positive, negative, and neutral sentiments, while Latent Dirichlet Allocation (LDA) revealed key topics. Framing analysis employed supervised machine learning to classify posts into narrative frames, and AI-powered visualization tools were used for interpretation. The results indicate a polarized sentiment distribution: 45% negative, 35% positive, and 20% neutral. Negative posts centered on skepticism and political inaction, while positive posts supported renewable energy and activism. Thematic analysis highlighted five key topics: scientific evidence, activism, economic implications, political debate, and environmental justice. Framing analysis revealed four dominant frames—climate urgency, economic impact, political action, and environmental justice—that shape public perception. Temporal sentiment shifts aligned with major events, suggesting public discourse is responsive to political and activist developments. This research demonstrates the potential of AI to provide scalable, data-driven insights into public climate discourse. By integrating these insights into strategic planning, communicators can design more effective, emotionally resonant messages, enhancing public engagement and supporting collective climate action.
Feminism in Legislation: The Urgency of Legal Reform to Enhance Women's Representation in Indonesia's Legislative Institutions Aidatul Fitriyah
Sinergi International Journal of Law Vol. 3 No. 2 (2025): May 2025
Publisher : Yayasan Sinergi Kawula Muda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61194/law.v3i2.746

Abstract

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Design and Feasibility Analysis of an integrated Zero-Waste Palm Oil biorefinery for Sustainable Aviation Fuel Production and Greenhouse Gas Mitigation Aidatul Fitriyah
International Journal of Oil Palm Vol. 8 No. 3 (2025)
Publisher : Indonesian Oil Palm Society /IOPS (Masyarakat Perkelapa-sawitan Indonesia /MAKSI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35876/ijop.v8i3.165

Abstract

This study aims to design and assess the technical, environmental, and economic feasibility of an integrated Zero-Waste Palm Oil biorefinery for the production of Sustainable Aviation Fuel (SAF) and other value-added co-products. A quantitative-descriptive approach was employed, integrating process simulation using Aspen Plus V14, Life Cycle Assessment (LCA), and financial modeling to evaluate the system’s performance and sustainability. Primary data were obtained from operational palm oil mills. In contrast, secondary data were sourced from the International Energy Agency (IEA), the International Renewable Energy Agency (IRENA), Statistics Indonesia (BPS), and the Ministry of Energy and Mineral Resources (ESDM) during 2023–2024. The results demonstrate that the integrated biorefinery configuration, which combines thermochemical conversion pathways (pyrolysis, gasification, and Fischer–Tropsch synthesis) with biochemical processes (anaerobic digestion), achieves a mass conversion efficiency of 58.4 percent, net energy efficiency of 72 percent, and an Energy Return on Investment (EROI) of 4.97, exceeding the global bioenergy feasibility threshold of three. The LCA results indicate total Life-cycle emissions of 17.3 g CO?-eq per MJ, representing an 80.6 percent reduction relative to fossil-based Jet A-1 fuel, thereby meeting both CORSIA and RED II sustainability standards. The system also achieves a 95 percent reduction in solid residues, effectively realizing a near-zero-waste operation. Financial modeling reveals a net present value (NPV) of USD 68.2 million, an internal rate of return (IRR) of 17.6 percent, and a payback period of 6.2 years, confirming the project’s economic viability. Overall, this model establishes a scalable pathway for decarbonizing the palm oil industry through circular bioeconomy principles and positions Indonesia as a potential global hub for SAF production aligned with international carbon reduction targets.
Co-Authors Rahman, Gohar