Sentiment Analysis of Community Perceptions on Coastal HRM Practices in Blue Economy Initiatives: An NLP-Based Study - Muhamad Toyib Daulay (Jurnal Ilmiah Manajemen Kesatuan, 2025)
Indonesia’s vast coastline and reliance on maritime sectors highlight the urgency of sustainable coastal management. Within this context, Human Resource Management (HRM) plays a crucial role in ensuring community participation and support for blue economy initiatives. This study examines community perceptions toward coastal HRM practices within blue economy initiatives in North Sumatra Province, Indonesia, using advanced natural language processing techniques. This study analyzes 4,399 text samples from community surveys, public forums, and stakeholder interviews using RoBERTa, BERT, and LSTM models to identify sentiment patterns surrounding coastal management strategies. Results show a balanced sentiment distribution: 34.7% positive, 28.9% neutral, and 36.4% negative responses. Temporal analysis reveals sentiment evolution from initial skepticism (-0.23) through consultation improvements (+0.15) to cautious optimism (+0.31) following early project benefits. Key findings indicate that while communities show potential for supporting blue economy initiatives, successful implementation requires addressing concerns about economic displacement, cultural disruption, and inadequate compensation. The study contributes a scalable NLP framework for continuous community sentiment monitoring in coastal management contexts.