Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal Journal of Embedded Systems, Security and Intelligent Systems Journal of Renewable Energy and Smart Device
Basino
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Semar AquaConnect: A Closed-Loop IoT System for Real-Time Monitoring and Autonomous Control in Catfish (Pangasianodon hypophthalmus) Larvae Rearing Rafif Zainun Ridhwan; Basino; ⁠Berbudi Wibowo; Rahmad Surya Hadi Saputra; ⁠I Ketut Daging; Yusuf Syam; Akhmad Syarifudin; Ade Hermawan
Journal of Embedded Systems, Security and Intelligent Systems Vol 7 No 1 (2026): March 2026
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v7i1.11782

Abstract

Purpose – This study aims to develop and validate Semar AquaConnect, a closed-loop Internet of Things (IoT) system for real-time monitoring and automated environmental control in catfish (Pangasianodon hypophthalmus) larval rearing tanks. Design/methods/approach – The system integrates an ESP32-based controller with sensors for temperature, pH, dissolved oxygen, total dissolved solids, and water level, as well as relay-based control of pumps, an aerator, and an immersion heater. A web-based dashboard and Telegram Bot were also developed for remote monitoring, data visualization, and emergency notifications. System performance was evaluated through sensor accuracy testing and repeated simulated extreme-condition scenarios (n=5). Findings – The results showed low mean differences of 0.12°C for temperature, 0.33 for pH, 0.08 mg/L for dissolved oxygen, and 5.10 ppm for total dissolved solids. In simulated scenarios, the system achieved a 100% relay activation success rate, including responses to critical pH fluctuations and temperature drops. Mean response latency ranged from 0.85 ± 0.10 s to 1.42 ± 0.18 s. Research implications/limitations – This study is limited to technical validation and has not yet included live biological trials to measure actual larval survival improvement. Originality/value – The study presents an integrated smart aquaculture platform combining multi-parameter sensing, autonomous actuator control, and dual-interface remote monitoring for catfish larval rearing.
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 Ade Hermawan Akhmad Syarifudin Daging, I Ketut Rafif Zainun Rafif Zainun Ridhwan Rahmad Surya Hadi Saputra Yusuf Syam ⁠Berbudi Wibowo ⁠I Ketut Daging