We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
Aksi Pulau Bersih sebagai Upaya Peningkatan Kesadaran Lingkungan Pesisir di Pulau Samalona Kota Makassar
Summary
This review assessed AI approaches for detecting lead (Pb²⁺) contamination in agricultural soils, finding that different machine learning models — SVMs, neural networks, CNNs, and LASSO — each suit specific detection scenarios depending on matrix complexity and concentration levels. While focused on heavy metals, the AI detection frameworks developed here are applicable to microplastic contamination monitoring, as both pollutants co-occur in agricultural soils and share detection challenges.
Samalona Island is one of the leading marine tourism destinations in Makassar City that faces coastal environmental pollution problems due to the accumulation of waste, particularly plastic debris. Intensive tourism activities, limited waste management facilities, and low environmental awareness among local communities and visitors are the main factors contributing to the decline in coastal environmental quality. This community service program aims to improve the cleanliness of the island’s environment and to enhance the environmental awareness of both the local community and tourists regarding the importance of protecting coastal ecosystems through the Clean Island Action program. The methods employed include beach and shallow-water clean-up activities, environmental education, and evaluation of participant involvement and program outcomes. The activity was conducted on December 6, 2025, on Samalona Island, involving lecturers, students, local residents, and environmental volunteers. The results indicate a reduction in waste volume in coastal and beach areas, as well as increased participation and awareness among participants regarding waste management. This program has generated positive ecological and social impacts and has the potential to serve as a community-based model for sustainable coastal environmental management.