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Journal : PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS

Satellite-Based Detection of Floating Plastic Debris in Jakarta Bay (2021–2024) Santi Wilda, Marchadha; Pasaribu, Ernawati
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2025 No. 1 (2025): Proceedings of 2025 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2025i1.573

Abstract

Plastic waste is a critical environmental issue in Jakarta Bay, causing ecosystem degradation and challenging coastal management. This study analyzes seasonal dynamics and spatial impacts of floating plastic debris using Sentinel-2 imagery from July 2021 to November 2024. The Floating Debris Index (FDI) and Normalized Difference Vegetation Index (NDVI) were applied, with optimum thresholds determined through ROC curve analysis. Monthly median composites were processed to minimize atmospheric noise. The results show a recurring seasonal pattern, with debris consistently peaking in June, likely influenced by monsoon driven runoff and human activities. A clear increasing trend from 2021 to 2023 was followed by a decline in 2024, coinciding with the implementation of the National Ocean Love Month program. Buffer analysis indicated that most debris accumulates within 500 m of the shoreline, particularly near river mouths, ports, and settlements, while Thiessen Polygon analysis revealed hotspots concentrated along the eastern and western coasts. These findings highlight that floating plastic debris in Jakarta Bay is strongly shaped by seasonal cycles and land-based inputs, providing critical insights for designing targeted, evidence-based waste management policies.
Analysis and Prediction of Green GRDP in Indonesia with Ecosystem Service Value Approach Gata, Ibnu; Pasaribu, Ernawati
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2025 No. 1 (2025): Proceedings of 2025 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2025i1.627

Abstract

Gross Regional Domestic Product (GRDP) as a measure of economic output in each region has not reflected sustainability because it overlooks the environmental impacts caused. Green GRDP is an important innovation that integrates environmental aspects into sustainable development. Indonesia has committed through TAP MPR IX/2001, Indonesia Emas 2045, and the SDGs to implement sustainable development. This study analyzes and projects Indonesia’s Green GRDP using the Ecosystem Service Value (ESV) approach. Satellite imagery data from MODIS MCD12Q1 and the Cellular Automata–Artificial Neural Network (CA-ANN) method are employed to predict land cover changes, while time series models are applied to forecast GRDP. Variations in provincial ESV are strongly influenced by land cover composition. In 2001, Papua recorded the highest Green GRDP and ESV contribution, whereas by 2020 (projected to 2030), Jakarta leads in Green GRDP but exhibits the lowest ESV contribution percentage. Throughout the period 2001–2030, Papua consistently maintains the highest ESV proportion relative to its Green GRDP. The findings highlight the importance of incorporating ecosystem service values into regional and national economic planning to ensure that economic growth inherently reflects environmental sustainability. This effort should be supported by spatially differentiated development strategies aligned with each region’s ecological capacity.