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All Journal Jurnal Tekno Kompak Jurnal Nasional Ilmu Komputer Jurnal Pengembangan Sistem Informasi dan Informatika Brilliance: Research of Artificial Intelligence Journal of Artificial Intelligence and Digital Business Journal Of Artificial Intelligence And Software Engineering SULUH ABDI : Jurnal Ilmiah Pengabdian Kepada Masyarakat Jurnal Ilmiah Sistem Informasi
Hidayat, kemas Muhammad Wahyu
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences Other

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IoT-Based Electrical Power Consumption Monitoring System in Households Using ESP32 and PZEM-004T Hidayat, Kemas Muhammad Wahyu; Al-Faris, Muhammad Ghozi
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.v5i2.6368

Abstract

Electricity consumption in the household sector is often poorly controlled, leading to energy waste and increased electricity bills. To address this issue, this study presents the design and implementation of an electricity consumption monitoring system based on the Internet of Things (IoT) using the ESP32 microcontroller and PZEM-004T sensor. The system allows real-time monitoring of electrical parameters such as voltage, current, power, and energy, with data displayed on digital devices like smartphones or computers.  Measurement data from the sensor is transmitted wirelessly to an IoT platform via Wi-Fi, enabling users to monitor electricity usage anytime and anywhere. A prototype method was used in this research, covering hardware and software design, sensor integration, and system testing.The testing results show that the system effectively provides accurate and responsive electricity usage data. With this system, users can identify usage patterns, detect high-power appliances, and make informed decisions to improve energy efficiency. The ability to access real-time data helps prevent energy waste and control monthly costs more effectively.Beyond individual benefits, this system also supports wider energy conservation initiatives by promoting conscious energy consumption behavior. The integration of IoT technology in household energy management demonstrates a practical solution for creating smarter and more sustainable living environments. This study confirms the potential of IoT-based systems to enhance energy awareness and support efforts in reducing overall electricity consumption.
Implementation of Testing of Automatic Light Control Tools Using Arduino Uno-Based Sound Sensors Mutia, Dian; Jimmie, Jimmie; Hidayat, Kemas Muhammad Wahyu
Jurnal Ilmiah Sistem Informasi Vol. 5 No. 1 (2026): January: Jurnal Ilmiah Sistem Informasi
Publisher : LPPM Universitas Sains dan Teknologi Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/w8gh5k23

Abstract

Penelitian ini bertujuan untuk merancang dan menguji sistem kendali lampu otomatis menggunakan sensor suara berbasis Arduino Uno sebagai solusi untuk mengatasi pemborosan energi listrik akibat lampu yang tetap menyala tanpa aktivitas. Penelitian ini bertujuan untuk merancang dan menguji sistem kendali lampu otomatis sensor suara berbasis Arduino uno sebagai solusi terhadap pemborosan energi listrik yang hidup tanpa ada aktivitas. Penelitian ini terletak pada penerapan dilingkungan rumah tangga, dikembang kan dengan cara sensor suara untuk memperbaiki tingkat keberhasilan deteksi perintah suara. Metode penelitian pengumpulan kebutuhan perancangan perangkat keras (menggunakan sensor suara, relay, Arduino uno, dan komponen yang mendukungnya) perancangan perangkat lunak dan Arduino IDE, pengujian menggunakan response time dan eror rate berdasarkan variasi jarak 50cm-450cm. hasil menunjukan bahwa sistem memiliki tingkat keberhasilan sebesar 87,5% dengan response time 1,2 detik. Sistem ini dinilai efektif dalam menilai dalam mendeteksi suara keras untuk menghidupkan dan mematikan lampu otomatis, sehingga mendukung konsep rumah pintar sekaligus meningkatkan efisiensi energi listrik.
Co-Authors afif, muhammad faris Agung Saputra Al-Faris, Muhammad Ghozi ANDI WIJAYA Jimmie, Jimmie Mutia, Dian Oktariani, Nandita Perdana, Meiylana Winda Prasetya, Rahmad Dhavin Puteri, delita M Roni, Kgs Ahmad Safutra, Edo sofiah, sofiah sofiah Syarifah Aini