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Rancang Bangun Sistem Pemadaman Ruangan Berbasis IoT dengan Metode Algoritma C4.5 Varian Rhaesa; Fara Triadi; Ahmad Rofiq Hakim
Jurnal Teknik Industri Terintegrasi (JUTIN) Vol. 9 No. 3 (2026): July
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jutin.v9i3.59771

Abstract

The IoT-based indoor fire extinguishing system with the C4.5 algorithm was developed to improve early detection, real-time monitoring, and automatic extinguishing at room scale. The system uses an ESP32, MQ-135, flame infrared, DHT22, and ultrasonic sensors to read environmental conditions, then sends the data to Firebase Realtime Database and an Android application. The C4.5 model uses a five-point time window to predict Safe, Alert, and Danger states. Training results show an average accuracy of 84.9% and best performance above 90%. Functional testing on 20 scenarios produced 13 successful and 7 failed cases, with a 65% success rate. Failures were mainly caused by mechanical belt-conveyor constraints, indicating that stronger mechanical components should be prioritized in future development.
Kendali Alat Sterilisasi Sepatu Berbasis Mobile Rakhmad Dhani; Arsan Kumala Jaya; Ahmad Rofiq Hakim
Jurnal Teknik Industri Terintegrasi (JUTIN) Vol. 9 No. 3 (2026): July
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jutin.v9i3.60344

Abstract

Shoes frequently come into contact with floors and the outdoor environment, making them a potential medium for spreading bacteria and viruses. This study aims to design and build an IoT-based shoe sterilization system that can be monitored and controlled via an Android application. The system uses an ESP32 microcontroller, DHT22 temperature and humidity sensor, MC-38 door sensor, and LJ12A3-4-Z/BX proximity sensor. The sterilization process uses a 254 nm UV-C lamp integrated with Firebase Realtime Database. The system can automatically detect shoe types, set a maximum temperature of 34°C for sneakers and 50°C for safety shoes, and automatically turn off the UV-C lamp when the door is opened. Test results show all components worked as designed. The integration of ESP32, Firebase, and the Android app proved to be an effective IoT-based sterilization solution.