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All Journal Brilliance: Research of Artificial Intelligence
Dianradika Prasti
Universitas Cokroaminoto Palopo, Indonesia
Decision Sciences, Operations Research & Management Mathematics Other

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Internet of Things (IoT)-Based Water Quality Monitoring System Design for Tilapia Fish Farming Ponds Putu Erawati; Dianradika Prasti; Tri Bondan Kriswinarso
Brilliance: Research of Artificial Intelligence Vol. 5 No. 2 (2025): Brilliance: Research of Artificial Intelligence, Article Research November 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i2.6927

Abstract

This study aimed to develop an Internet of Things (IoT)-based water quality monitoring system for tilapia cultivation ponds at Varel Collection. Farmers previously monitored pond water manually, which was often neglected due to their agricultural activities, leading to poor water conditions and negative impacts on fish growth. To overcome this issue, a prototype system was designed to enable real-time monitoring of water parameters using IoT technology integrated with the Blynk platform. The research applied a Research and Development (R&D) approach with a Prototype method. The system was built using NodeMCU ESP32 as the main microcontroller, integrated with several sensors including a pH sensor, DS18B20 temperature sensor, and a turbidity sensor to measure water quality parameters. Data from these sensors are processed and transmitted to the Blynk application, allowing farmers to remotely monitor pond conditions via the internet. Supporting tools included Fritzing for design, Arduino IDE for programming, and hardware components such as adapters, jumper cables, and enclosures. Evaluation by three experts indicated that the system achieved an average feasibility index of 95.93%, categorized as “very good.” These findings show that the IoT-based monitoring system is functional, feasible for aquaculture use, and has strong potential for further development in real-time water quality management.
Design and Implementation of Electronic Queue System at Walenrang Health Center for Service Optimization Rizky Amalia Sugiman; Dianradika Prasti; Suparman Suparman
Brilliance: Research of Artificial Intelligence Vol. 5 No. 2 (2025): Brilliance: Research of Artificial Intelligence, Article Research November 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i2.6929

Abstract

This study aims to design, develop, and implement an Android-based electronic queuing system to enhance the effectiveness, efficiency, and overall quality of healthcare services at Walenrang Community Health Center. The manual queuing system previously applied often caused patient congestion, long waiting times, service delays, and discomfort for both patients and staff. To overcome these problems, an electronic queuing system was created, allowing patients to take queue numbers online, monitor the real-time status of the queue, access detailed service information, and view their visit history conveniently. This system was developed using a Research and Development (R&D) approach, following the waterfall model as the software development method. Evaluation of the system involved three expert validators, resulting in a validation score of 95.17%, which classifies the system as highly feasible for implementation. Furthermore, usability testing with 12 user respondents revealed an average satisfaction score of 94 out of 100, indicating a very high level of user satisfaction regarding ease of use, speed of access, and accuracy of queue information. Based on these results, the implemented system has proven effective in improving the efficiency of healthcare service delivery while providing greater convenience, comfort, and accessibility for the community, thereby supporting a more organized and patient-friendly healthcare environment.
Co-Authors Putu Erawati Rizky Amalia Sugiman Suparman Suparman Tri Bondan Kriswinarso