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All Journal Jurnal Masyarakat Informatika JSI: Jurnal Sistem Informasi (E-Journal) Jurnal Informatika Jurnal Informatika ICON-CSE Annual Research Seminar CESS (Journal of Computer Engineering, System and Science) Sistemasi: Jurnal Sistem Informasi Sinkron : Jurnal dan Penelitian Teknik Informatika JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Teknologi Sistem Informasi dan Aplikasi Jurnal Teknologi Informasi dan Pendidikan TEKNOKOM : Jurnal Teknologi dan Rekayasa Sistem Komputer Jurnal Tekinkom (Teknik Informasi dan Komputer) Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal Generic Jurnal Algoritma INOVTEK Polbeng - Seri Informatika JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Mgs Afriyan Firdaus
Universitas Sriwijaya
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Library & Information Science Public Health Other

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Journal : Jurnal Masyarakat Informatika

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Aspect-Based Sentiment Analysis on Nickel Mining Activities in Raja Ampat to Support Sustainable Development Goals Karima, Dzakiah Aulia; Indah, Dwi Rosa; Firdaus, Mgs Afriyan; Sanjaya, M Rudi; Hartono Cahyadi, Gabriel Ekoputra
Jurnal Masyarakat Informatika Vol 17, No 1 (2026): May 2026 (Ongoing)
Publisher : Department of Informatics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jmasif.17.1.77146

Abstract

Nickel mining in Raja Ampat has triggered significant public reaction, particularly on social media, due to its environmental and social impacts. However, public opinion on this issue has not been systematically analyzed. This study aims to examine public sentiment toward this issue using the Aspect-Based Sentiment Analysis (ABSA) approach with four classification algorithms: Support Vector Machine, K-Nearest Neighbor, Naïve Bayes, and Random Forest, all optimized through the Particle Swarm Optimization (PSO) method. Data was collected from X between June 1 and June 30, 2025, and analyzed based on three main aspects, namely environmental, social, and economic, with a total of 4,025 datasets. The analysis shows that negative sentiment dominates over positive sentiment, with the environmental aspect being the main focus, especially regarding coral reef damage and marine pollution. Among the four models used, the optimized Support Vector Machine algorithm achieved the highest performance with an accuracy of 87.5%. These findings are expected to serve as an evaluation for the government regarding mining permits to formulate policies that support the achievement of SDG 14 (Life Below Water) and SDG 15 (Life on Land).
Co-Authors Akrom, Akrom Ali Ibrahim Andhika Setiadi Apriansyah Putra Ari Wedhasmara Arwin Permata Putra Athalina, Ghita Choirunnisa Qonitah Damayanti, Indri Dwi Dhilarofii Russandwi, Saras Dwi Rosa Indah Endang Lestari Endang Lestari Ruskan Ermatita - Errissya Rasywir Fauza Adelma Syafrizal Firman Wijaya Gumay, Naretha Kawadha Pasema Gumay, Naretha Kawadha Pasemah Harlili Harlili Hartono Cahyadi, Gabriel Ekoputra Jaidan Jauhari Karima, Dzakiah Aulia Ken Dhita Tania Khoiriah, Annisa Lovinta Happy Atrinawati Lufiah, Fara Megah Mulya Monterico Adrian Mutia Farahdilla Pacu Putra Perdianza, Muhammad Egi Pratama, Muhammad Fandra Eka Purwita Sari, Purwita Putra, Julian Putri Eka Sevtiyuni Putri Ratna Sari, Putri Ratna Putri, Indah Arsita Rahmat Izwan Heroza Rahmayuni, Septa Rusdi Rivaldo Sabrina, Dea Fitri Samsuryadi Samsuryadi Sanjaya, M Rudi Sanjaya, M. Rudi Saputra, Danny Matthew Saras Dhilarofii Russandwi Syahnel, Ahmad Hidayat Tsabitah, Laila Wijaya, Firman Yadi Utama Yudha Pratomo Yunita Yunita Zahirah, Nabilah