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All Journal PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS
Faradinah Nasir, Fadiah
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Computer Science & IT

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Detecting Marine Debris Using Sentinel-2 Satellite Images: (Case Study: Kuta Beach, Bali) Faradinah Nasir, Fadiah; Kurniawan, Robert
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.v2025i1.552

Abstract

Plastic waste pollution in the oceans remains a global problem. Kuta Beach is one of Bali's tourist destinations that has been affected by plastic waste pollution. This is not in line with the 14th SDGs, which is to prevent and reduce marine debris pollution. However, the marine debris monitoring process carried out by the Ministry of Environment and Forestry requires officers to conduct direct monitoring in the field, which incurs higher costs. Therefore, satellite imagery can be an alternative option for more effective and efficient marine debris detection. This study aims to detect marine debris on Kuta Beach using machine learning algorithms, namely Random Forest (RF), XGBoost, and LightGBM. This study uses the Marine Debris Archive (MARIDA) dataset, which has marine debris labels, and Sentinel-2 images of Kuta Beach from 2019–2023. The LightGBM algorithm provided the best performance in detecting marine debris with an F1-score of 95.16%. The area detected as marine debris on Kuta Beach in 2019–2023 was 500 m2, 0 m2, 100 m2, 300 m2, and 400 m2, respectively. Based on these results, marine debris is generally detected around the coastline, particularly in the southern area of Kuta Beach, which is located near a shopping center.
Co-Authors Robert Kurniawan, Robert