Article Per Year (5 Year)
p-Index From 2021 - 2026
0.61
P-Index
This Author published in this journals
All Journal Journal of Mechatronics and Artificial Intelligence
Panji Narputro
Nusa Putra University

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

Found 3 Documents
Search

 1 
Mamdani Fuzzy Logic-Based Room Temperature Monitoring and Control System Trisiani Dewi Hendrawati; Fikri Arif Wicaksana; Panji Narputro; Samirah Rahayu
Journal of Mechatronics and Artificial Intelligence Vol. 2 No. 1 (2025): JMAI: June 2025
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/jmai.v2i2.88461

Abstract

Automatic room temperature control is a crucial need for maintaining comfort and energy efficiency, especially in enclosed environments such as offices, laboratories, and homes. This research aims to design and develop a room temperature monitoring and control system based on Mamdani fuzzy logic. The system utilizes a temperature sensor to monitor real-time environmental conditions and actuators (fans or heaters) as outputs to adjust the temperature. The Mamdani fuzzy logic method is chosen for its ability to handle uncertainty and provide decisions that resemble human reasoning. Test results show that the system can maintain the room temperature within the desired range responsively and efficiently. By implementing this system, thermal comfort can be achieved automatically without manual intervention, while also supporting energy savings in the operation of cooling and heating devices.
Study of the Effect of the Use of Series Reactive Power Compensators on the Increase in Inductive Load Power Factor with Magnetic Energy Recovery Switches in Household Environments Adi Nugraha; Tartila Dinar Haqiqi; Lazuardi Akmal Islami; Panji Narputro
Journal of Mechatronics and Artificial Intelligence Vol. 2 No. 2 (2025): JMAI: December 2025
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/jmai.v2i2.83220

Abstract

The use of inductive loads in modern household electrical installations is increasing, particularly in multi-story homes equipped with elevators, water pump drive motors, and generators. Such inductive loads lead to a decrease in power factor due to the dominance of reactive power, which negatively affects the efficiency and cost of electricity consumption. This study aims to improve the power factor in a three-story residential electrical system by implementing a reactive compensation method using a Magnetic Energy Recovery Switch (MERS) circuit. The system design and analysis are based on active power data obtained through the Autodesk Revit 2024 application, with load parameters sourced from the F-H05 elevator, Grundfos pump motor, and Weichai Power generator. Simulation was carried out using PSIM software to determine the optimal capacitor value and triggering angle for the IRF820 MOSFET. The simulation results show that the application of MERS significantly improves the power factor, making the system more efficient and cost-effective.
Mamdani Fuzzy-Based Soil Fertility Detection Using Moisture and Color Sensors Fikri Arif Wicaksana; Trisiani Dewi Hendrawati; Panji Narputro; M Farhan
Journal of Mechatronics and Artificial Intelligence Vol. 3 No. 1 (2026): JMAI: June 2026
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/jmai.v3i1.135

Abstract

Soil fertility plays an important role in supporting agricultural productivity and sustainable farming practices. Conventional methods for determining soil fertility, such as visual observation of soil color and manual inspection of soil moisture, are often subjective, inefficient, and less accurate. This study proposes an Internet of Things (IoT)-based soil fertility detection system using a soil moisture sensor and a TCS3200 color sensor to provide real-time and objective soil condition monitoring. The system employs a NodeMCU ESP8266 microcontroller for data acquisition and wireless communication. Sensor data are processed using the Mamdani Fuzzy Inference System (FIS) to classify soil fertility into three categories: fertile, moderately fertile, and infertile. The developed system displays monitoring results locally through an OLED display and remotely through Google Spreadsheet integration for real-time observation. Sensor calibration and field testing were conducted using several soil samples with different moisture and color characteristics. Experimental results showed that the soil moisture sensor achieved an average error rate of 1.57%, indicating good measurement accuracy. Furthermore, the fuzzy-based classification successfully identified soil fertility levels according to the measured parameters. The integration of IoT technology and fuzzy logic provides an effective low-cost solution for precision agriculture applications, particularly for small-scale farming environments. The proposed system is expected to assist farmers in monitoring soil conditions more efficiently, accurately, and continuously.
Co-Authors Adi Nugraha Arif Fikri Wicaksana Lazuardi Akmal Islami M Farhan Samirah Rahayu Tartila Dinar Haqiqi Trisiani Dewi Hendrawati