Komponen Utama Kesuburan Perairan Tambak Di Desa Pondong Baru Dengan Menggunakan Nilai Spektral Citra Drone
Abstract
The productivity of brackish water aquaculture is often fluctuative due to suboptimal water quality and the difficulty of monitoring pond water fertility over large areas. This study aims to identify the main components of pond water fertility and to examine the relationship between RGB spectral values from drone imagery with nitrate and phosphate parameters. Image acquisition was carried out using a DJI Mavic 2 Pro drone at an altitude of 50 m, with 15 samples collected from three semi-intensive ponds in Pondong Baru Village, Kuaro District, Paser Regency. The measured parameters included brightness, temperature, salinity, pH, dissolved oxygen, turbidity, nitrate, and phosphate. Data analysis was performed using Principal Component Analysis (PCA) and linear regression. The results showed that two principal components (PCs) explain 87.1% of the data variation. PC1 is dominated by temperature (0.967), pH (0.912), brightness (0.882), and dissolved oxygen (0.851), while PC2 is dominated by phosphate (0.798) and nitrate (-0,637). Linear regression for phosphate showed R² = 0.495 (marginal significance), while nitrate was not significant (R² = 0.033). Drone imagery has the potential to be effective for monitoring pond water fertility, particularly for phosphate parameters.
Keywords: pond water fertility, drone imagery, RGB, PCA, linear regression, nitrate, phosphate
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References
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Baena-Navarro, R., Carriazo-Regino, Y., Torres-Hoyos, F., & Pinedo-López, J. (2025). Intelligent Prediction and Continuous Monitoring of Water Quality in Aquaculture: Integration of Machine Learning and Internet of Things for Sustainable Management. Water, 17(1), 82. https://doi.org/10.3390/w17010082
Bai, X., Wang, J., Chen, R., Kang, Y., Ding, Y., Lv, Z., Ding, D., & Feng, H. (2024). Research progress of inland river water quality monitoring technology based on unmanned aerial vehicle hyperspectral imaging technology. Environmental Research, 257, 119254. https://doi.org/10.1016/j.envres.2024.119254
Basyuni, M., Bimantara, Y., & Amelia, R. (2021). Mengenal Drone dalam Sistem Informasi Geografis dan Aplikasinya dalam Penelitian Kehutanan. USU Press.
BPS. (2024). Produksi Perikanan Budidaya Menurut Komoditas Utama (Ton). Badan Pusat Staistik. https://www.bps.go.id/id/statistics-table/2/MTUxMyMy/produksi-perikanan-budidaya-menurut-komoditas-utama.html
Chen, Y., Yao, K., Zhu, B., Gao, Z., Xu, J., Li, Y., Hu, Y., Lin, F., & Zhang, X. (2024). Water Quality Inversion of a Typical Rural Small River in Southeastern China Based on UAV Multispectral Imagery: A Comparison of Multiple Machine Learning Algorithms. Water, 16(4), 553. https://doi.org/10.3390/w16040553
Christiana, D. W., Pairunan, R., & Ibrahim, L. K. J. (2024). Menuju Hilirisasi Sektor Perikanan Indonesia yang Kuat dan Berkelanjutan. World Resources Institute (WRI) Indonesia. World Resources Institute (WRI) Indonesia. https://wri-indonesia.org/id/wawasan/menuju-hilirisasi-sektor-perikanan-indonesia-yang-kuat-dan-berkelanjutan
CHUMAISAROH, D. A., Widiastuti, N. A., & Kusumodestoni, R. H. (2021). Monitoring Produktivitas Nauplius Vanammei Dengan Fuzzy C-Means Pada BBPBAP Jepara. UNIVERSITAS ISLAM NAHDLATUL ULAMA JEPARA.
Cui, M., Sun, Y., Huang, C., & Li, M. (2022). Water Turbidity Retrieval Based on UAV Hyperspectral Remote Sensing. Water, 14(1), 128. https://doi.org/10.3390/w14010128
Dewi, N. N. (2025). Analisis Kualitas Perairan Berdasarkan Tingkat Kesuburan dan Status Pencemaran Air Pesisir Bomo, Banyuwangi, Indonesia. JFMR-Journal of Fisheries and Marine Research, 9(3). https://doi.org/10.21776/ub.jfmr.2025.009.03.4
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Manurung Morgan, Ismail Fahmy Almadi, & Asfie Maidie. (2024). Hubungan Nilai Spektral Citra Drone dengan Kesuburan Plankton pada Tambak di Muara Badak Kabupaten Kutai Kartanegara. Jurnal Aquawarman, 10(1), 101–112.
Muhammad, M., Musafira, F., & Khairunnisa, K. (2023). Analisis Kesuburan Perairan Di Krueng Geukuh, Aceh Utara Berdasarkan Sebaran Nitrat Dan Fosfat Terhadap Kelimpahan Fitoplankton. Jurnal Kelautan dan Perikanan Indonesia, 3(2), 66–78. https://doi.org/10.24815/jkpi.v3i2.32738
Onibala, M., Thambas, A. H., & Riogilang, H. (2025). Analisis Kualitas Air Di Danau Tondano Menggunakan Evaluasi Temporal, WQI, CCME-WQI, DAN PCA. Jurnal Sosial Teknologi, 5(5). https://doi.org/10.59188/jurnalsostech.v5i5.32095
Sandu, M. A., Virsta, A., Vasilescaeteanu, G., Iliescu, A. I., Ivan, I., Nicolae, C. G., Stoian, M., & Madjar, R. M. (2023). Water Quality Monitoring Of Moara Domnească Pond, Ilfov County, Using UAV-Based RGB Imaging. AgroLife Scientific Journal, 12(1), 191–201. https://doi.org/10.17930/AGL2023122
Song, H., Mehdi, S. R., Li, Z., Wang, M., Wu, C., Venediktov, V. Y., & Huang, H. (2023). Investigating the rate of turbidity impact on underwater spectral reflectance detection. Frontiers in Marine Science, 10, 1031869. https://doi.org/10.3389/fmars.2023.1031869
Suhana. (2022). Tingkat Pemanfaatan Ikan di WPPNRI Dominan Fully dan Over Exploited. Literasi Ekonomi Kelautan. https://suhana.web.id/2022/04/08/tingkat-pemanfaatan-ikan-di-wppnri-dominan-fully-dan-over-exploited/
Wasehun, E. T., Hashemi Beni, L., & Di Vittorio, C. A. (2024). UAV and satellite remote sensing for inland water quality assessments: A literature review. Environmental Monitoring and Assessment, 196(3), 277. https://doi.org/10.1007/s10661-024-12342-6
Yusal, Muh. S., Hasyim, A., Hastuti, H., Arif, A., & Pratomo, R. H. S. (2025). Review Eutrofikasi: Risiko dalam Kesuburan Lingkungan Perairan dan Upaya Penanggulangannya. Jurnal Kesehatan Lingkungan Indonesia, 24(1), 123–134. https://doi.org/10.14710/jkli.67125
Zhang, Y., Jing, W., Deng, Y., Zhou, W., Yang, J., Li, Y., Cai, Y., Hu, Y., Peng, X., Lan, W., Peng, M., & Tang, Y. (2023). Water quality parameters retrieval of coastal mariculture ponds based on UAV multispectral remote sensing. Frontiers in Environmental Science, 11, 1079397. https://doi.org/10.3389/fenvs.2023.1079397
Published
28-06-2026
How to Cite
Almadi, I., Ramadhan, M., & Nikhlani, A. (2026). Komponen Utama Kesuburan Perairan Tambak Di Desa Pondong Baru Dengan Menggunakan Nilai Spektral Citra Drone. Jurnal Pertanian Terpadu, 14(1), 169-178. https://doi.org/10.36084/jpt.v14i1.782
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