Pendampingan dan Workshop untuk Penggiat Lingkungan: Pemanfaatan Vizly (AI – Powered Data Analysis) dalam Analisis Statistik Lingkungan Hidup

Authors

  • Bunga Mardhotillah Program Studi Matematika, Universitas Jambi, Jambi, Indonesia
  • Shally Yanova Program Studi Ilmu Lingkungan, Universitas Jambi, Jambi, Indonesia
  • Bambang Irawan Program Studi Ilmu Lingkungan, Universitas Jambi, Jambi, Indonesia
  • Ade Adriadi Program Studi Biologi, Universitas Jambi, Jambi, Indonesia
  • Lailal Gusri Program Studi Ilmu Lingkungan, Universitas Jambi, Jambi, Indonesia
  • Edi Saputra Program Studi Informatika, Universitas Jambi, Jambi, Indonesia
  • Ade Nurdin Program Studi Teknik Sipil, Universitas Jambi, Jambi, Indonesia
  • Tri Syukria Putra Program Studi Ilmu Lingkungan, Universitas Jambi, Jambi, Indonesia

Keywords:

Mentorship And Workshop, Environmental Activists, Environmental Data, Technology Utilization, Vizly as AI

Abstract

This mentorship and workshop aimed to enhance the capacity of environmental activists to understand and apply statistical analysis to environmental issues. Through the use of Vizly (AI-Powered Data Analysis), participants were introduced to an artificial intelligence-based approach that simplifies data processing, visualization, and interpretation of results. The workshop method included intensive mentoring, theoretical presentations, and hands-on practice using relevant environmental data, such as air quality, waste management, and renewable energy utilization. The workshop was conducted in a systematic manner: identifying participant needs, introducing basic statistical analysis concepts, simulating the use of Vizly, and post-workshop mentoring to ensure continued understanding. The results demonstrated improved skills among participants in processing environmental data more quickly, accurately, and evidence-based. Vizly has been proven to assist environmental activists in producing analyses that can support decision-making, policy advocacy, and environmental program planning. The implications of this activity include facilitating the integration of AI technology into environmental work, while also opening up opportunities for collaboration between academics, government, and communities.

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Published

2026-01-31