Article Per Year (5 Year)
p-Index From 2021 - 2026
0.61
P-Index
This Author published in this journals
All Journal G-Tech : Jurnal Teknologi Terapan
Denny Irawan
Universitas Muhammadiyah Gresik, Indonesia
Computer Science & IT Decision Sciences, Operations Research & Management Energy Engineering

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Three Phase Motor Speed Monitoring and Control System Using Raspberry Pi and Node RED in Molding Production at PT XYZ Muhammad Nashruddin Alie; Denny Irawan
G-Tech: Jurnal Teknologi Terapan Vol 9 No 3 (2025): G-Tech, Vol. 9 No. 3 July 2025
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v9i3.7514

Abstract

PT XYZ is a company that produces the largest automotive tools in Gresik. In producing the tool, a molding process is needed as a mold maker. In the molding process at PT XYZ, furan resin is used as a bonding agent and mixed with a catalyst in the appropriate proportion to produce a sand mold. Three-phase motor speed control in the molding process is very much needed so that the production process reaches maximum targets. The use of VFD in motor speed control can facilitate operators in the process of mixing materials for molding. Raspberry Pi combined with Node RED is an alternative as a cheap and efficient 3-phase motor speed monitoring and control system. The speed control of 3 phase motors on VFD can be done using Raspberry Pi with the help of Node RED as a communication bridge with VFD with Modbus protocol. The speed of 3 phase motors on VFD has an error percentage of 1.362% when compared to the UNI-T 373 tool. So that the monitoring and control system of 3 phase motors using Raspberry Pi and Node RED in molding production at PT XYZ is in accordance with the researcher's expectations and the system that has been designed can be implemented at PT XYZ.
Fertilizer Factory Port Conveyor Optimization Design System With Outseal PLC and HMI Rovi Maulidani Syela; Denny Irawan
G-Tech: Jurnal Teknologi Terapan Vol 9 No 4 (2025): G-Tech, Vol. 9 No. 4 October 2025
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v9i4.8073

Abstract

The development of automation systems in industry is increasingly rapid, especially in the field of material control and distribution. Automation systems are designed to simplify human work and stabilize the performance of industrial machines to be more efficient and reliable. This article discusses the design and implementation of a prototype of an automatic conveyor system in the port area that functions to support the material distribution process to the fertilizer factory. This system uses the Outseal Nano Programmable Logic Controller (PLC) as the main controller and the Haiwell Human Machine Interface (HMI) as a remote monitoring and control system. The main objective of the design is to reduce buildup and prevent material spillage during the transportation process from the port to the production area. Test results show that the automatic conveyor system is able to operate stably at an operational temperature of 45°C and a Moisture Quantity (MQ) value of at least 30%, without significant disruption to the transportation process. The implementation of this system resulted in an increase in material distribution efficiency of 27.8% compared to the manual system, and reduced material handling time by up to 22%. In addition, the error rate in material distribution was reduced by up to 15%, which contributed to increased accuracy and work safety in the port area. Overall, this automation system has been proven to increase the efficiency and reliability of the material distribution process, as well as being an effective solution to overcome logistical and operational problems in the port industry environment.
IoT-Based Automatic Irrigation System with Reinforcement Learning for Water Optimization Naufal Arief Baihaqi; Denny Irawan
G-Tech: Jurnal Teknologi Terapan Vol 10 No 1 (2026): G-Tech, Vol. 10 No. 1 January 2026
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v10i1.8376

Abstract

Water efficiency in agriculture plays a crucial role in addressing climate change and freshwater scarcity challenges. Conventional irrigation systems often result in excessive water usage due to non-adaptive watering schedules. This study proposes an adaptive automatic irrigation system based on the Internet of Things (IoT) integrated with the Reinforcement Learning (RL) Q-Learning algorithm to optimize water usage. The system utilizes an ESP32 microcontroller connected to DHT22 and YL-69 sensors for real-time monitoring of temperature, humidity, and soil moisture, with data transmitted to the Firebase Realtime Database. The system was experimentally tested for 30 days under three soil moisture conditions with repeated measurements, resulting in an average sensor accuracy of 97.9% and a 70% reduction in daily water consumption compared to manual irrigation. The implementation of RL enables the system to autonomously adjust irrigation decisions based on environmental dynamics while providing remote monitoring via a web dashboard. The results demonstrate that the proposed IoT-RL solution offers an effective, intelligent, and sustainable approach for improving agricultural water resource management.
Co-Authors Muhammad Nashruddin Alie Naufal Arief Baihaqi Rovi Maulidani Syela