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All Journal Reformasi : Jurnal Ilmiah Ilmu Sosial dan Ilmu Politik AL-ULUM : Jurnal Ilmu Sosial dan Humaniora Formosa Journal of Multidisciplinary Research (FJMR) Mudabbir: Journal Research and Education Studies Journal of Innovation Research and Knowledge Journal of Empowerment and Community Service Journal of Embedded Systems, Security and Intelligent Systems JGuruku: Jurnal Penelitian Guru Journal of Renewable Energy and Smart Device
Ade Hermawan
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Design and Calibration of Water Quality Monitoring System Based on Internet of Things Basino; Rafif Zainun; ⁠Berbudi Wibowo; Rahmad Surya Hadi Saputra; I Ketut Daging; Yusuf Syam; Akhmad Syarifudin; Ade Hermawan
Journal of Renewable Energy and Smart Device Vol. 3 No. 2 April 2026
Publisher : PT. Global Research Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66314/joresd.v3i2.429

Abstract

Real-time water quality monitoring is crucial for modern aquaculture. However, low-cost Internet of Things (IoT) systems frequently struggle with analog sensor precision due to the limitations of internal microcontrollers. This study presents the design, calibration, and performance evaluation of a highly precise IoT-based water quality monitoring system. The hardware architecture utilizes NodeMCU ESP-32 microcontroller integrated with an external ADS1115 16-bit Analog-to-Digital Converter (ADC) module. This integration effectively mitigates signal noise and accurately processes analog inputs. The system continuously measures temperature using a DS18B20 sensor, alongside pH, Dissolved Oxygen (DO), and Total Dissolved Solids (TDS). To ensure industrial-grade reliability, rigorous sensor calibration was executed using linear regression and standard buffer solutions prior to deployment. A 14-day comparative field test was then conducted against calibrated commercial handheld instruments to validate the system's accuracy. The statistical evaluation demonstrated exceptional precision, yielding minimal average measurement errors of 0.08°C for temperature, 0.35 for pH, 0.24 mg/L for DO, and 6.80 ppm for TDS. Furthermore, linear regression analysis confirmed highly robust data correlations between the IoT sensors and the standard devices. The system achieved coefficient of determination ($R^2$) values of 0.9928 for the temperature sensor, 0.8906 for pH, 0.9962 for DO, and 0.7656 for TDS. These results mathematically confirm that integrating an external high-resolution ADC alongside comprehensive statistical calibration significantly enhances measurement stability. Ultimately, this approach successfully elevates the precision of low-cost IoT monitoring systems for aquaculture applications.
Co-Authors Achmad Syarifudin Akhmad Syarifudin Aprizha Muhammad Fadhil Bakhtiar Basino Basino, Basino Daging, I Ketut Doly Andrian Harahap Eddy Mustono Faizal Fachruddin M. Alfan Anshori M. Naqsyabandi. S Marsono Marsono Muhammad Haider Ali Muhammad Jamili Mustofa Kamal Mustopa Kamal Nabila Triastuty Nur Aulia Indriyanti Priyantini Dewi Raedy Anwar Subiantoro Rafif Zainun Rafif Zainun Ridhwan Rahmad Surya Hadi Saputra Sakti P. Nababan Shamila Bashayeva Syarifah Fitri Teguh Binardi Yani Lubis Yeni Rahmawati Yusuf Syam ⁠Berbudi Wibowo ⁠I Ketut Daging