IoT-Enabled Real-Time Monitoring and Tsukamoto Fuzzy Classification of Mandar River Water Quality via Web Integration for Sustainable Resource Management
DOI:
https://doi.org/10.52436/1.jutif.2025.6.5.5249Keywords:
ESP32, IoT, pH sensor, real-time monitoring, TDS, Tsukamoto fuzzy logic, turbidityAbstract
This study presents the design and implementation of a real-time water quality monitoring system that utilizes pH, Total Dissolved Solids (TDS), and turbidity sensors, integrated with an ESP32 microcontroller. Sensor data are processed using the Tsukamoto fuzzy logic method to classify river water suitability into two categories: Suitable and Not Suitable. This approach effectively addresses imprecise and uncertain data, thereby producing more reliable classifications compared to conventional threshold-based methods. System validation was conducted through field testing over seven consecutive days at four different times of the day (morning, midday, afternoon, and evening), with results demonstrating stable performance. Recorded pH values ranged from 7.02 to 9.96, TDS values from 140 to 176 ppm, and turbidity levels between 4.00 and 5.15 NTU, indicating that the Mandar River remains within safe limits for daily use. The novelty of this study lies in the direct implementation of the Tsukamoto fuzzy logic method on a resource-constrained IoT device (ESP32), enabling edge-level classification with low latency and without full reliance on cloud computing. The system is designed to maintain decision reliability even under fluctuating sensor data, thus offering a practical and integrated solution for real-time monitoring. The main contribution of this work to computer science is the demonstration of lightweight embedded intelligent algorithms capable of running on constrained devices, the reinforcement of Explainable AI through transparent linguistic rules, and the integration of IoT with edge computing to support sustainable resource management in real-time.
Downloads
References
S. Sukmawati, Maarifah Dahlan, and R. Dela, “Analisa Pencemaran Sungai Mandar Dengan Bioindikator Makroinvertebrata Melalui Metode Biotilik,” Bina Gener. J. Kesehat., vol. 12, no. 2, pp. 48–52, 2021, doi: 10.35907/bgjk.v12i2.165.
M. H. Ramadhan, G. Dewantoro, and F. D. Setiaji, “Rancang Bangun Sistem Pakar Pemantau Kualitas Air Berbasis IoT Menggunakan Fuzzy Classifier,” J. Tek. Elektro, vol. 12, no. 2, pp. 47–56, 2020, doi: 10.15294/jte.v12i2.25351.
A. Lestari and A. Zafia, “Penerapan Sistem Monitoring Kualitas Air Berbasis Internet Of Things,” LEDGER J. Inform. Inf. Technol., vol. 1, no. 1, pp. 17–24, 2022, doi: 10.20895/ledger.v1i1.776.
H. F. bin Hawari, M. N. S. bin Mokhtar, and S. Sarang, “Development of Real-Time Internet of Things (IoT) Based Water Quality Monitoring System,” Lect. Notes Electr. Eng., vol. 758, no. September, pp. 443–454, 2022, doi: 10.1007/978-981-16-2183-3_43.
H. M. Forhad et al., “IoT based real-time water quality monitoring system in water treatment plants (WTPs),” Heliyon, vol. 10, no. 23, p. e40746, 2024, doi: 10.1016/j.heliyon.2024.e40746.
H. Fakhrurroja, E. T. Nuryatno, A. Munandar, M. Fahmi, and N. A. Mahardiono, “Water quality assessment monitoring system using fuzzy logic and the internet of things,” J. Mechatronics, Electr. Power, Veh. Technol., vol. 14, no. 2, pp. 198–207, 2023, doi: 10.14203/j.mev.2023.v14.198-207.
M. Andara, E. Purwanto, A. H. Pratomo, R. Kurniawan, and H. H. Triharminto, “Water Quality Monitoring System Based on Fuzzy Algorithm,” Int. J. Adv. Sci. Eng. Inf. Technol., vol. 12, no. 5, pp. 2105–2111, 2022, doi: 10.18517/ijaseit.12.5.15996.
F. Rozie, I. Syarif, and M. U. H. Al Rasyid, “Design and implementation of Intelligent Aquaponics Monitoring System based on IoT,” IES 2020 - Int. Electron. Symp. Role Auton. Intell. Syst. Hum. Life Comf., no. November 2020, pp. 534–540, 2020, doi: 10.1109/IES50839.2020.9231928.
A. J. Kuswinta, I. G. P. W. Wedashwara W, and I. W. A. Arimbawa, “Implementasi IoT Cerdas Berbasis Inference Fuzzy Tsukamoto pada Pemantauan Kadar pH dan Ketinggian Air dalam Akuaponik,” J. Comput. Sci. Informatics Eng., vol. 3, no. 1, pp. 65–74, 2019, doi: 10.29303/jcosine.v3i1.245.
A. F. Daru, A. M. Hirzan, F. B. Saputra, and P. A. Christianto, “Implementation of ESP8266 and Turbidity Sensor in Water Turbidity Monitoring Model Using Fuzzy Tsukamoto,” J. Adv. Comput. Technol. Appl., vol. 6, no. 2, pp. 1–13, 2024, doi: 10.54554/jacta.2024.06.02.001.
D. Rahmawati et al., “Rancang Bangun Pengaturan Microbubble dan Kualitas Air Tambak Udang Berbasis Internet of Things (IoT),” SinarFe7, vol. 6, no. 1, pp. 59–65, 2024, [Online]. Available: https://journal.fortei7.org/index.php/sinarFe7/article/view/641
B. D. Prasetyo, E. Widodo, and D. Ardiatma, “Sistem Monitoring Kualitas Air Sumur Berbasis Iot Dengan Fuzzy Logic dan Interface Berbasis Web,” vol. 11, no. 1, pp. 5–8, 2025.
H. Qulub, S. Adi Wibowo, and A. Faisol, “Rancang Bangun Sistem Monitoring Kelayakan Air Minum Berbasis Iot Menggunakan Metode Fuzzy Tsukamoto,” JATI (Jurnal Mhs. Tek. Inform., vol. 7, no. 5, pp. 3082–3089, 2024, doi: 10.36040/jati.v7i5.7602.
D. M. S. Chairi Nur Insani, “Monitoring Sistem Fluktuasi Harga Pangan Secara Realtime Berbasis Website 1,2,” vol. 5, no. 1, pp. 88–100, 2024, doi: 10.35957/algoritme.xxxx.
M. Saleem, N. Shingari, M. S. Farooq, B. Mago, and M. A. Khan, “Real-Time Air Quality Monitoring Model using Fuzzy Inference System,” Int. J. Adv. Comput. Sci. Appl., vol. 15, no. 6, pp. 838–846, 2024, doi: 10.14569/IJACSA.2024.0150684.
S. K. Nagothu, P. Bindu Sri, G. Anitha, S. Vincent, and O. P. Kumar, “Advancing aquaculture: fuzzy logic-based water quality monitoring and maintenance system for precision aquaculture,” Aquac. Int., vol. 33, no. 1, pp. 1–21, 2025, doi: 10.1007/s10499-024-01701-2.
S. Ismail, G. S. Member, R. Marsh, and A. L. I. S. Alshami, “IoT-Based Water Management Systems : Survey and Future Research Direction,” IEEE Access, vol. 10, pp. 35942–35952, 2022, doi: 10.1109/ACCESS.2022.3163742.
L. Rosnita, M. Ikhwani, H. A. K. Aidilof, Salamah, W. Hamsi, and H. Y. Rangkuti, “Water Quality Monitoring and Control System for Tilapia Cultivation Based on Internet of Things,” Int. J. Eng. Sci. Inf. Technol., vol. 4, no. 4, pp. 38–43, 2024, doi: 10.52088/ijesty.v4i4.566.
R. Trach, Y. Trach, A. Kiersnowska, A. Markiewicz, M. Lendo-Siwicka, and K. Rusakov, “A Study of Assessment and Prediction of Water Quality Index Using Fuzzy Logic and ANN Models,” Sustain., vol. 14, no. 9, 2022, doi: 10.3390/su14095656.
F. Jan, N. Min-Allah, and D. Düştegör, “Iot based smart water quality monitoring: Recent techniques, trends and challenges for domestic applications,” Water (Switzerland), vol. 13, no. 13, pp. 1–37, 2021, doi: 10.3390/w13131729.
S. Safitri, D. M. Sari, C. N. Insani, and S. A. Rachmini, “Sistem Kontrol dan Monitoring Pemberi Pakan Ikan Otomatis Berbasis IOT,” J. Manaj. Inform. Sist. Inf. dan Teknol. Komput., vol. 1, no. 1, pp. 74–82, 2022, doi: 10.70247/jumistik.v1i1.12.
C. N. I. Hasnawati, Muh. Fuad Mansyur, “Deteksi Kesegaran Ikan Selar Menggunakan Sensor Warna dan Sensor Gas Berbasis Web,” J. Comput. Inf. Syst., vol. 6, no. 1, pp. 37–44, 2023.
A. F. Choiri, “IoT-Based Water Quality Monitoring System for Fish Ponds Using Fuzzy Inference Method,” J. Teknol. Inf. Dan Terap. (J-TIT, vol. 11, no. 2, pp. 143–152, 2024, [Online]. Available: https://doi.org/10/25047/jtit.v11i2.5794
M. R. Al Mamun, M. Ashik-E-Rabbani, M. M. Haque, and S. M. Upoma, “IoT-based real-time biofloc monitoring and controlling system,” Smart Agric. Technol., vol. 9, no. November, p. 100598, 2024, doi: 10.1016/j.atech.2024.100598.
M. W. Hamdani, “Perancangan dan Implementasi Metode Kontrol Fuzzy Logic Mamdani pada Sistem Kontrol TDS dan pH Hidroponik,” JTT (Jurnal Teknol. Terpadu), vol. 10, no. 2, pp. 171–183, 2022, doi: 10.32487/jtt.v10i2.1555.
A. Adha, “Penerapan Logika Fuzzy Pada Mesin Cuci Dan Menentukan Lama Waktu Pencucian,” JIKO (Jurnal Inform. dan Komputer), vol. 6, no. 1, p. 125, 2022, doi: 10.26798/jiko.v6i1.289.
N. A. Mohd Jais, A. F. Abdullah, M. S. Mohd Kassim, M. M. Abd Karim, A. M, and N. ‘Atirah Muhadi, “Improved accuracy in IoT-Based water quality monitoring for aquaculture tanks using low-cost sensors: Asian seabass fish farming,” Heliyon, vol. 10, no. 8, 2024, doi: 10.1016/j.heliyon.2024.e29022.
W. T. Saputra et al., “IoT-MQTT Protocol-Based Water Sensor System to Monitor Citarum River Water Quality using Arduino Uno R4 Wifi,” J. ELTIKOM, vol. 9, no. 1, pp. 11–22, 2025, doi: 10.31961/eltikom.v9i1.1335.
Andrianto bala, Cindy P.C Munaiseche, Kristofel Santa, “Sistem Kontrol Alat Pengukur Berbasis IoT Menggunakan Fuzzy Tsukamoto Dipertenakan Ayam Broiler Desa Tonsea Lama,” JOINTER J. Informatics Eng., vol. 3, no. 02, pp. 24–35, 2022, doi: 10.53682/jointer.v3i02.71.
M. Yudi Abdul Syawari and Hartono, “Sistem Inferensi Fuzzy Tsukamoto Untuk Menentukan Tingkat Kualitas Air Pada Kolam Budidaya Ikan Lele,” Sienna, vol. 5, no. 1, pp. 95–109, 2024, doi: 10.47637/sienna.v5i1.1358.
A. Suherman and D. Widyaningrum, “Implementasi Fuzzy Tsukamoto pada Sistem Internet of Things Budidaya Tanaman Bayam,” Smatika J., vol. 14, no. 01, pp. 195–204, 2024, doi: 10.32664/smatika.v14i01.1332.
D. Setiyawan, A. Arbansyah, and A. J. Latipah, “Fuzzy Inference System Metode Tsukamoto Untuk Penentuan Program Studi Fakultas Sains Dan Teknologi Di Universitas Muhammadiyah Kalimantan Timur,” JIKO (Jurnal Inform. dan Komputer), vol. 7, no. 1, p. 23, 2023, doi: 10.26798/jiko.v7i1.657.
Y. G. Purba and D. Avianto, “Implementasi Logika Fuzzy Tsukamoto untuk Optimasi Jumlah Produksi Es Batu Kemasan,” MALCOM Indones. J. Mach. Learn. Comput. Sci., vol. 5, no. 1, pp. 119–129, 2024, doi: 10.57152/malcom.v5i1.1736.
D. O. Kurniawati and T. Feri Efendi, “Penerapan Metode Fuzzy Tsukamoto Dalam Diagnosa Penyakit Demam Berdarah,” J. Inform. Komput. dan Bisnis, vol. 1, no. 1, pp. 1–10, 2020, [Online]. Available: https://jurnal.itbaas.ac.id/index.php/jikobis
A. Febriansyah, I. Irwan, S. Surojo, A. Zahri, and D. Amanda, “Monitoring Kadar Air Berdasarkan Kadar pH, Tingkat Kondusifitas Air, dan Kadar Kekeruhan Air,” Manutech J. Teknol. Manufaktur, vol. 16, no. 01, pp. 18–25, 2024, doi: 10.33504/manutech.v16i01.313.
S. Sugeng, T. N. Nizar, D. A. Jatmiko, R. Hartono, and Y. Y. Kerlooza, “Kalibrasi Sensor Monitoring Cuaca pada Area Lokal untuk Meningkatkan Akurasi pada Sensor Biaya Rendah,” Komputika J. Sist. Komput., vol. 13, no. 2, pp. 277–287, 2024, doi: 10.34010/komputika.v13i2.13949.
Additional Files
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Chairi Nur Insani, Nurhikma Arifin
This work is licensed under a Creative Commons Attribution 4.0 International License.
