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All Journal Journal of Computer Networks, Architecture and High Performance Computing
Arifani, Kahpi Baiquni
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Computer Science & IT Education

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FUZZY LOGIC-CONTROLLED IOT SYSTEM FOR SMART PUBLIC TOILETS: DESIGN, IMPLEMENTATION, AND EVALUATION Arifani, Kahpi Baiquni; Irsyadi, Muhamad Haidir; Prakoso, Akbar Tri; Amrullah, Ahmad Wildan; Alam, Fajar Indra Nur; Prasetya, Dwi Arman; Sari, Anggraini Puspita
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 3 (2025): Articles Research July 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i3.6045

Abstract

Efficient energy management in public facilities such as public toilets has become an important challenge in the modern era, especially with the increasing demand for environmental sustainability. In this research, we developed a smart toilet system based on the Internet of Things (IoT) using the ESP32 as the main microcontroller and fuzzy logic methods for intelligent decision-making. This system is equipped with temperature (DHT22), humidity, and distance (HC-SR04) sensors to detect environmental conditions and user presence. Based on this data, the toilet fan and light are automatically controlled to minimize energy consumption. To facilitate real-time monitoring and threshold control, this system is integrated with a Flutter-based application, which provides an intuitive user interface for viewing environmental data and setting temperature, humidity, and distance thresholds. Fuzzy logic is used to determine the fan speed based on temperature and humidity inputs, with the output being a gradual fan speed control. (PWM). The test results show that the system can reduce energy consumption by up to 30% compared to the manual method, especially by reducing the unnecessary device idle time. Additionally, the system has an average response time of 200 ms to send sensor data to the application and receive threshold updates from the user. With this approach, the research shows that the integration of IoT with fuzzy logic provides significant energy efficiency and enhances the user experience. This research also opens up opportunities for further development, such as the integration of machine learning technology for predicting facility usage patterns or the implementation of additional sensors for air quality detection. These findings support the implementation of IoT-based automated systems in public facilities to achieve energy efficiency and environmental sustainability.
Real-Time Data Integration and Weather Reporting Automation with Cloud Computing-based Interactive Spatial Dashboard for Extreme Weather Risk Analytics in Indonesia Arifani, Kahpi Baiquni; Pintarko, Dody; Sari, Anggraini Puspita; Agussalim, Agussalim
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 3 (2025): Articles Research July 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i3.6298

Abstract

Global climate change has increased the risk of extreme weather events in Indonesia, necessitating an accurate and real-time weather information system. This study develops a cloud computing-based system capable of integrating national weather data in real-time, automating the generation of actual and forecast weather reports, and presenting this information through an interactive spatial dashboard. The system is built on a client-server architecture deployed on Google Cloud Platform, utilizing the OpenWeatherMap API, a Flask backend, and a JavaScript-based frontend (Leaflet.js and Chart.js). Evaluation results indicate that the system can provide integrated national weather data with latency under one second, generate automated multi-province weather reports, and deliver interactive heatmap visualizations of extreme weather risks. This system is effective in improving the speed, accuracy, and efficiency of weather information distribution to support decision-making in the maritime, transportation, and disaster management sectors.
Co-Authors Agussalim, Agussalim Alam, Fajar Indra Nur Amrullah, Ahmad Wildan Anggraini Puspita Sari Dwi Arman Prasetya Irsyadi, Muhamad Haidir Pintarko, Dody Prakoso, Akbar Tri