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Ujianti, et al.

composition or increasing salinity. Contributing factors Conflict of interest
include soil erosion, agricultural runoff, domestic waste
pollution, and other human activities, which collectively The authors declare that they have no competing
raise TDS concentrations in river water. 57 interests.

4. Conclusion and recommendations Author contributions

The IoT-based water quality monitoring system allows Conceptualization: Rizky Muliani Dwi Ujianti, Mega
for continuous, real-time DAQ with low error margins, Novita, Roies Nur Ingsan, Alfan Najihil Wafa
providing accurate and reliable assessments suitable Formal analysis: All authors
for tropical coastal environments. The system’s Funding acquisition: Rizky Muliani Dwi Ujianti
integration of multiple sensors (pH, temperature, and Investigation: All authors
TDS) with on-site data display and cloud connectivity Methodology: Rizky Muliani Dwi Ujianti, Mega Novita,
enables prompt detection of water quality changes, Roies Nur Ingsan, Alfan Najihil Wafa
facilitating faster environmental response. Its low- Software: Aan Burhanudin, Muchamad Malik
cost design, ease of deployment, and ability to replace Validation: Rizky Muliani Dwi Ujianti, Roies Nur
labor-intensive manual sampling make this system Ingsan, Alfan Najihil Wafa
highly practical and scalable, supporting sustainable Visualization: Mega Novita, Agus Mukhtar, Althesa
coastal water management and data-driven decisions Androva, Jeki Mediantari Wahyu Wibawanti
in Semarang city and Kendal Regency, Central Java, Writing – original draft: Rizky Muliani Dwi Ujianti,
Indonesia. Roies Nur Ingsan
Our results highlight the promise of the IoT- Writing – review & editing: Rizky Muliani Dwi Ujianti,
based water quality monitoring system, which is Mega Novita, Agus Mukhtar, Althesa Androva, Jeki
recommended to be further developed and expanded Mediantari Wahyu Wibawanti
by integrating additional sensors to cover more
water quality parameters. Future work should focus Availability of data
on enhancing the system’s robustness for long-term
deployment in diverse coastal environments and Data used for this study were included in the manuscript.
optimizing data analytics for predictive environmental
management. Collaboration with local authorities and References
community stakeholders is essential to ensure effective 1. Khomich M, Kauserud H, Logares R, Rasconi S,
implementation and to promote sustainable ecosystem Andersen T. Planktonic protistan communities in lakes
management practices. along a large-scale environmental gradient. FEMS
Microbiol Ecol. 2017;93(4):fiw231.
Acknowledgments doi: 10.1093/femsec/fiw231
2. Djumanto N, Pranoto BE, Diani VS, Setyobudi E. Food
The authors would like to acknowledge Ministry of and the growth of introduced milkfish, Chanos chanos
Education, Culture, Research, and Technology of (Forsskal, 1775) in sermo reservoir, Kulon Progo.
Indonesia for the support. J Iktiologi Indones. 2017;17(1):83-100.
doi: 10.32491/jii.v17i1.306
Funding 3. Setyanto A, Rachman NA, Yulianto ES. Distribution and
composition of lobster species caught in java sea of east
The funding for this study was provided by the java, Indonesia. J Perikanan Universitas Gadjah Mada.
Ministry of Education, Culture, Research, and 2018;20(1):49-55.
doi: 10.22146/jfs/.36151
Technology of Indonesia in collaboration with 4. Baryshev IA, Veselov АE, Aleksandrovich D,
Universitas PGRI Semarang. The fund is under the Andreevich М, Pavlov DS. Benthic disturbance-recovery
research scheme of Penelitian Fundamental 2024. SK dynamics after construction impact in mountain river
No. 0667/E5/AL.04/2024 (contract numbers: 108/E5/ Mzymta (Sochi, Black Sea Basin). Turk J Fish Aquat Sci.
PG.02.00.PL/2024; 033/LL6/PB/AL.04/2024; 007/ 2017;17:1245-1251.
LPPM-UPGRIS/SP2H/PENELITIAN/VI/2024). doi: 10.4194/1303-2712-v17

Volume 22 Issue 4 (2025) 14 doi: 10.36922/AJWEP025110069