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All Journal Indonesian Journal of Electrical Engineering and Computer Science JITEL (Jurnal Ilmiah Telekomunikasi, Elektronika, dan Listrik Tenaga) Gunung Djati Conference Series
Surya, Irgi
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Sistem monitoring beban listrik dan perbaikan faktor daya menggunakan PZEM004T dan dashboard Adafruit berbasis IoT Surya, Irgi; Kustija, Jaja; Eka Pawinanto, Roer; Pramudita, Resa; Adli Rizqulloh, Muhammad; Wahyudin, Didin; Haritman, Erik
JITEL (Jurnal Ilmiah Telekomunikasi, Elektronika, dan Listrik Tenaga) Vol. 3 No. 3: September 2023
Publisher : Jurusan Teknik Elektro, Politeknik Negeri Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35313/jitel.v3.i3.2023.235-246

Abstract

Graphic User Interface (GUI) pada suatu sistem Internet of Things (IoT) salah satunya dipengaruhi oleh monitor yang mudah diakses, fleksibel, serta efisien dalam penggunaannya. Hal ini sudah banyak didiskusikan namun masalah tersebut masih belum dapat ditingkatkan. Salah satu solusi dari masalah tersebut adalah dengan dihadirkannya MQTT Adafruit, yang mana dengan menggunakan MQTT Adafruit GUI untuk memonitor suatu sistem IoT dapat mempermudah kontrol dan kendali jarak jauh. Penelitian ini bertujuan untuk menghadirkan sistem monitoring beban listrik dan perbaikan faktor daya menggunakan PZEM004T berbasis IoT yang sudah menggunakan MQTT Adafruit sebagai user interface-nya. Metode yang digunakan melalui pendekatan analysis, design, development, implementation, evaluation (ADDIE). Hasil penelitian menunjukan bahwa sistem ini layak digunakan karena berdasarkan hasil percobaan faktor daya yang sebelumnya 0,35 menjadi 0,89 setelah dilakukan perbaikan faktor daya. Sistem ini juga memberikan kemudahan bagi pengguna dan dapat melakukan monitoring secara real time arus, tegangan, faktor daya, daya nyata, daya semu, dan daya reaktif baik hanya dengan menggunakan smartphone, laptop, tablet, maupun komputer. Berdasarkan hasil uji reliabilitas alat ini memiliki selisih yang kecil antara setiap hasil percobaan.
Design and development of coastal marine water quality monitoring based on IoT in achieving implementation of SDGs Kustija, Jaja; Fahrizal, Diki; Nasir, Muhamad; Setiawan, Deny; Surya, Irgi
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 3: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i3.pp1470-1484

Abstract

Indonesia, an archipelagic nation with about 70% ocean territory, relies on oceanographic data for efficient marine environment monitoring and natural resource sustainability. Current data collection is limited by tools measuring only single parameters and lengthy data collection times. This study proposes a marine coastal water quality monitoring tool based on the internet of things (IoT), capable of simultaneously measuring temperature, electrical conductivity, pH, and dissolved oxygen. Utilizing an Atmega328 and a battery lasting up to 119 hours, this system offers a cost-effective solution for real-time oceanographic data collection. Employing the ADDIE methodology, the results demonstrate high measurement accuracy compared to traditional methods, with accuracy of 90.5% for temperature, 93.50% for electrical conductivity, 93.67% for pH, and 96.82% for dissolved oxygen. The development of this tool aims to reduce costs and labor in capturing oceanographic data integrated with IoT, facilitate access and monitoring of water data, and make a significant contribution to achieving SDGs targets. The main focus on the goals of addressing climate change and life underwater, especially in the aspects of water resources management and protection of marine ecosystems in Indonesian.
Optimization of IoT-based monitoring system for automatic power factor correction using PZEM-004T sensor Somantri, Maman; Fauzan, Mochamad Rizal; Surya, Irgi
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 2: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i2.pp860-873

Abstract

Power factor correction (PFC) is crucial for improving energy efficiency and reducing excessive power consumption, especially in inductive loads commonly found in household and industrial environments. Conventional PFC methods often rely on manual capacitor switching, which is inefficient and impractical for real-time applications. This study proposes an IoT-based automatic power factor monitoring and correction system that dynamically adjusts the power factor using real-time data analysis. The system integrates NodeMCU ESP32 and the PZEM-004T sensor to monitor electrical parameters and automatically switch capacitors based on power factor conditions. The research follows the ADDIE approach (analysis, design, development, implementation, evaluation) to ensure a structured development process. Experimental results demonstrate an average power factor improvement of 48.77% and a reduction in current consumption by 39.90%, significantly enhancing energy efficiency. The system's web-based interface allows real-time monitoring with an average data transmission response time of 207.67 ms, ensuring efficient remote management. Compared to existing systems, the proposed approach eliminates manual intervention and optimizes PFC adaptively. Future research should focus on expanding system reliability, testing on larger-scale applications, and integrating artificial intelligence (AI) for predictive power factor adjustments.
Data Quality in an IoT Sensor System for Water Quality: Demonstrated on Time-Dependent Water Temperature Fluctuations Jaja, Jaja; Surya, Irgi; Fahrizal, Diki
Gunung Djati Conference Series Vol. 61 No. 1 (2025): International Conference of the 17th OISAA’s International Symposium Türkiye
Publisher : UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/gdcs.v61i1.3272

Abstract

The increasing demand for reliable and efficient Internet of Things (IoT) applications underscores the importance of ensuring high-quality sensor data for accurate monitoring and decision-making. This study focuses on data quality in an IoT sensor system for water quality monitoring, specifically demonstrated on time-dependent water temperature fluctuations. The system integrates fuzzy logic–based analysis and IoT connectivity using the Adafruit MQTT platform to enable real-time data acquisition, monitoring, and anomaly detection through smartphones, tablets, or computers. To ensure systematic development, the research employs the ADDIE methodology (Analysis, Design, Development, Implementation, Evaluation), enabling iterative refinement of both hardware and software components. Experimental results show that the system effectively captures temperature variations over time while identifying anomalies that may indicate sensor drift, environmental irregularities, or potential system faults. By addressing both measurement reliability and anomaly detection, this research contributes to improving data quality in IoT-based water monitoring systems, providing a scalable solution for sustainable water resource management and industrial applications/
Modelling An Occupancy-Based Hvac System Controller for Building Energy Efficiency Kustija, Jaja; Muhammad, Raihan Zhifhanur; Fahrizal, Diki; Surya, Irgi
Gunung Djati Conference Series Vol. 61 No. 1 (2025): International Conference of the 17th OISAA’s International Symposium Türkiye
Publisher : UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/gdcs.v61i1.3273

Abstract

Heating, Ventilation, and Air Conditioning (HVAC) systems are major energy consumers in commercial buildings, often accounting for nearly half of total energy usage. A primary source of inefficiency is conventional operation that ignores occupancy patterns, leading to unnecessary conditioning of unoccupied spaces. This paper presents a simulation study of an occupancy-based HVAC control system using a simplified first-order thermal model of a building space. Three control strategies are compared: a baseline system without active control, a reactive On-Off controller, and a Proportional-Integral-Derivative (PID) controller tuned using the Ziegler-Nichols method. Both the On-Off and PID controllers are integrated with an occupancy model to enable adaptive operation. Simulation results show that the occupancy-based PID controller achieves the best performance in balancing energy efficiency and thermal comfort compared to the other strategies. In addition, this work highlights a planned extension toward intelligent control methods, such as Deep Reinforcement Learning (DQN), to provide more adaptive and robust HVAC operation in dynamic environments.
Co-Authors Adli Rizqulloh, Muhammad Deny Setiawan Didin Wahyudin, Didin Eka Pawinanto, Roer Erik Haritman, Erik Fahrizal, Diki Fauzan, Mochamad Rizal Jaja Kustija, Jaja JAJA, JAJA Maman Somantri Muhamad Nasir, Muhamad Muhammad, Raihan Zhifhanur Pramudita, Resa