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International Journal of Electrical and Intelligent Engineering
Published by Universitas Islam Negeri Maulana Malik Ibrahim Malang
ISSN : -     EISSN : 31107079     DOI : https://doi.org/10.18860/ijeie
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering
International Journal of Electrical and Intelligent Engineering is an open access journal. The International Journal of Electrical and Intelligent Engineering IJEIE is a scholarly journal with a strong presence in Asia and seeks to engage a global audience. The journal mission is to promote the convergence of electrical engineering intelligent systems and automation technologies across various engineering disciplines. It aims to publish pioneering research in electrical engineering electronics engineering sensor networks robotics automation and intelligent systems. The journal invites research papers and literature reviews that explore both theoretical innovations and practical engineering implementations. Special attention is given to innovative technologies system architectures and the application of smart technologies in real world engineering environments. The IJEIE is a resource for academics engineers system architects and industry professionals specializing in electrical engineering robotics automation sensor technologies and intelligent systems. The topics covered include electrical engineering technologies electronics systems automation and control systems robotics sensor systems power systems intelligent control smart grid IoT industrial IoT machine learning artificial intelligence cyber physical systems embedded systems intelligent transportation renewable energy smart manufacturing human machine interaction and advanced materials.The topics covered by the International Journal of Electrical and Intelligent Engineering include, but are not limited to, the following: Electrical engineering technologies Electronics engineering systems Automation and control systems Robotics and robot applications Sensor systems and applications Power systems control and distribution Intelligent control systems Smart grid technologies IoT and industrial IoT applications Machine learning and AI for engineering systems Cyber-physical systems Embedded systems and real-time computing Intelligent transportation systems Renewable energy technologies Smart manufacturing systems Automation in manufacturing Advanced fabrication technologies Human-machine interaction Intelligent systems in healthcare Robotic process automation in industries Advanced materials and electronic components
Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro
Articles 5 Documents
 1 
Search results for , issue "Vol 1, No 1 (2025)" : 5 Documents clear
Effect of Using PID Control in Switched Inductor Boost Converter Mochamad Shofwan Rizqulloh; Unggul Wibawa; Lunde Ardhenta; Alisa Zahrani Farady Daud
International Journal of Electrical and Intelligent Engineering Vol 1, No 1 (2025)
Publisher : Department of Electrical Engineering Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/ijeie.v1i1.34206

Abstract

Among the different kinds of boost converters is the switched inductor boost converter. But the Switched Inductor Boost Converter still has drawbacks, like output voltage results that still overshoot, a lengthy time to attain a steady state, and output voltage that fluctuates in response to input voltage changes. This shortcoming can be addressed in this investigation by using a PID controller. The PID parameter is obtained using the Direct Synthesis method, which includes Kp, Ki, and Kd. The state space averaging method is employed for the converter modeling. By applying the PID controller to the Switched Inductor Boost Converter while simulation is carried out using MATLAB-Simulink, the output voltage's transient response is improved where PID control can eliminate overshoot on output voltage response and speed up settling time by 1.35 times and also improves system's resistance to variations in input voltage and load value, allowing it to sustain the output voltage and lower momentary voltage change up to 68.3045% and speeds up recovery time up to 2.5287 times faster when input voltage changes occurs and lower overshoot value up to 39.2809% and speeds up recovery time up to 2.708 times faster when load changes occurs.
Blind Spot Detection to Prevent Serious Accidents for Children in Cyclists Utari Sanaba; Virhan Mujahid Syufie; Rasyeedah Binti Mohd Othman; Muhammad Richard Dzaki Dharma
International Journal of Electrical and Intelligent Engineering Vol 1, No 1 (2025)
Publisher : Department of Electrical Engineering Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/ijeie.v1i1.34781

Abstract

Bicycles are a mode of transportation used not only to move a person from one point to another but also commonly as a means of exercise. The lack of a safety system on bicycles increases the risk of accidents and theft, especially for children who have not yet developed stable emotional control while cycling. The use of ultrasonic sensors can be applied as detectors to provide early warnings when a cyclist is about to switch lanes, considering the wide blind spot area for cyclists. In this research, the system includes an application that can control a smart lock and the boundaries of the detector using the TCP/IP protocol via SIM900A, allowing the bicycle owner to manage the device's condition and monitor the bicycle's location. After going through several stages of testing and analyzing the results, it can be concluded that the transmission of GPS position data was successfully stored and accurately reflected in the database, with errors of 0.0012614% and 5.41295E-05% for latitude and longitude data, respectively. The blind spot detector successfully measured the distance of walls and motor vehicles located within the cyclist's blind spot area with an accuracy of 85.54%, and the safety system—comprising the lock and LED indicator—was also successfully activated when a vehicle approached the cyclist within the blind zone.
Improving Random Forest Performance for Botnet Attack Detection in IoT Big Data Using Remove Frequent Values Filter Imam Marzuki; Mas Ahmad Baihaqi; Hartawan Abdillah; Dwi Iryaning Handayani; Nurhidayati Nurhidayati
International Journal of Electrical and Intelligent Engineering Vol 1, No 1 (2025)
Publisher : Department of Electrical Engineering Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/ijeie.v1i1.34533

Abstract

This research aims to enhance the performance of the Random Forest algorithm in classifying big data within the Internet of Things (IoT) domain, specifically for detecting botnet attacks. The study utilizes the N-BaIoT dataset, comprising 150,000 instances of IoT network traffic categorized into normal and anomalous (botnet) data. To optimize classification outcomes, a preprocessing technique—the “remove frequent values” filter—is applied to reduce redundancy and improve computational efficiency. Model performance is evaluated using accuracy, precision, recall, and F1-score. Experimental results demonstrate that this filter improves classification accuracy from 99.976% to 99.998%, with precision, recall, and F1-score all reaching 1.000. Cross-validation was conducted to ensure the robustness of these results. These findings suggest that even lightweight preprocessing techniques can significantly enhance machine learning performance in IoT big data classification tasks. 
Artificial Intelligence Application of Back-propagation Neural Network in Cryptocurrency Price Prediction Muhammad Sahi; Galan Ramadan Harya Galib
International Journal of Electrical and Intelligent Engineering Vol 1, No 1 (2025)
Publisher : Department of Electrical Engineering Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/ijeie.v1i1.33800

Abstract

This study explores the use of Deep Learning and Artificial Intelligence (AI), particularly Artificial Neural Networks (ANN), for cryptocurrency price prediction. Given the high volatility of crypto markets, traditional models often underperform. A backpropagation-based ANN with a 7-5-1 architecture is proposed and tested using historical Bitcoin data. The model achieves high accuracy, with a Mean Squared Error (MSE) of 4.0431e-04, equivalent to 99.96% accuracy, demonstrating its ability to capture complex nonlinear patterns. However, overfitting remains a concern, emphasizing the need for robust generalization and feature selection. The results validate the potential of ANN in crypto forecasting and encourage further research using diverse features and assets.
Design of Single-Phase Induction Motor Soft Starter with Closed Loop Method Using Arduino Microcontroller Ardhito Primatama; Lutfir Rahman Aliffianto; Ciptian Weried Priananda
International Journal of Electrical and Intelligent Engineering Vol 1, No 1 (2025)
Publisher : Department of Electrical Engineering Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/ijeie.v1i1.33950

Abstract

A closed‑loop soft‑starter for a 220 V/0.5 hp single‑phase induction motor driven by an Arduino micro‑controller and dual feedback (current + speed) is presented. Relative to direct‑on‑line (DOL) starting, the prototype halves the in‑rush current under no‑load conditions (6.62 A versus 3.30 A) and reduces it by 36 % when the motor drives a synchronous generator (8.28 A versus 5.33 A). Starting torque is maintained at ≥ 90 % of the DOL value in both scenarios, whereas transient time rises modestly from 0.77 s to 2.32 s (no‑load) and to 7.92 s under generator load. These findings demonstrate that the proposed soft‑starter mitigates voltage sag and mechanical stress without compromising torque, making it suitable for small‑enterprise applications where three‑phase supplies are unavailable.

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