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Wijayasari, Winda
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Earth & Planetary Sciences Energy Engineering Environmental Science Industrial & Manufacturing Engineering

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Analisis dan Penentuan Model Empiris untuk Estimasi Sebaran Klorofil-a menggunakan Citra Satelit Sentinel-2(Studi Kasus: Waduk Saguling, Sungai Citarum) Tirtana Putri, Aulia; Soewondo, Prayatni; Wijayasari, Winda; Immaddudin Wira Rohmat, Faizal
Jurnal Serambi Engineering Vol. 10 No. 2 (2025): April 2025
Publisher : Faculty of Engineering, Universitas Serambi Mekkah

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Abstract

The upstream of River Citarum is mildly polluted, which indicates the importance of water river monitoring. This study aims to analyze and determine an empirical model, which is a regression equation using Sentinel-2 satellite imagery to estimate chlorophyll-a concentration in the Saguling Reservoir, upstream of Citarum River. The Multiple Linear Regression (MLR) equation has been obtained, integrating bands 2, 3, 4, 5 and 11 with an R2 value of 0.75 and RMSE of 1.39. However, the results of the model correlation test with validation data indicate a decline in model performance, reflected by an R2 value of 0.261 and RMSE of 4.2. The visualization results using the model with Google Earth Engine (GEE) show an increase in chlorophyll-a concentration in 2024 compared to 2022. However, the actual presence of vegetation in the waters and segmentation errors need to be considered, because they can affect the accuracy of the estimate. This study has limitations in that it only uses reflectance values ​​and chlorophyll-a concentration in situ, without considering other factors. However, the results of the study indicate that the estimated results of the model and the actual values remain within the same range according to their trophic status, suggesting that this model can serve as an overview for predicting chlorophyll-a distribution in the Saguling Reservoir.
Pemetaan Transparansi Air di Waduk Saguling dengan Menggunakan ANN dan Landsat 8 Magfhira, Azzahra; Soewondo, Prayatni; Wijayasari, Winda; Rohmat, Faizal
Jurnal Serambi Engineering Vol. 10 No. 3 (2025): Juli 2025
Publisher : Faculty of Engineering, Universitas Serambi Mekkah

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The decline in water transparency in the Saguling Reservoir indicates deteriorating water quality due to increasing pollutant loads from domestic, industrial, agricultural, and aquaculture activities. This study aims to predict water transparency using an ANN model, integrating remote sensing data from Landsat 8 (2013-2024) and in-situ measurements from 12 sampling points. The analysis began with correlation tests, which revealed weak to moderate relationships between transparency and other variables. Subsequent simple and multiple linear and logistic regression analyses produced weak correlations, with the highest R² of 0.1853 observed in multiple logistic regression. The Random Forest algorithm was applied to identify the most influential variables. The selected predictors included Bands 3, 4, 5, and 7, as well as temperature, EC, and TSS. These variables were used as inputs for the ANN model, which demonstrated high performance with an R² of 0.8514, explaining 85.14% of the variability in water transparency. The prediction results were visualized in a distribution map, indicating a predominance of transparency class IV (0-2.5 m) across the reservoir. This suggests limited light penetration due to high pollutant loads. The study shows that integrating remote sensing and ML enables effective large-scale water quality monitoring and supports sustainable water resource management.
Co-Authors Immaddudin Wira Rohmat, Faizal Magfhira, Azzahra Prayatni Soewondo Rohmat, Faizal Tirtana Putri, Aulia