cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Mochammad Apriyadi Hadi Sirad
Contact Email
ijeeic.unkhair@gmail.com
Phone
+6282292852552
Journal Mail Official
ijeeic.unkhair@gmail.com
Editorial Address
Departement of Electrical Engineering, Faculty of Engineering, Universitas Khairun, Address: Yusuf Abdulrahman No. 53 (Gambesi) Ternate City - Indonesia
Location
Kota ternate,
Maluku utara
INDONESIA
International Journal of Electrical Engineering and Intelligent Computing
Published by Universitas Khairun
ISSN : -     EISSN : 30315255     DOI : 10.33387/ijeeic
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering Energy
International Journal of Electrical Engineering and Intelligent Computing, E-ISSN : 3031-5255 is an official publication of the Universitas Khairun. The IJEEIC is an international journal is a peer-reviewed open-access. The IJEEIC that has been published online since 2023.
Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro
Articles 5 Documents
 1 
Search results for , issue "Vol 2, No 1 (2024): International Journal Of Electrical Engineering And Intelligent Computing" : 5 Documents clear
Smart Parking based on Car Detection using Deep Learning YOLOv8 Waluyo Nugroho; Afianto Afianto; Mada Jimmy Fonda Arifianto
International Journal Of Electrical Engineering and Inteligent Computing Vol 2, No 1 (2024): International Journal Of Electrical Engineering And Intelligent Computing
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/ijeeic.v2i1.8692

Abstract

In the context of rapidly growing urbanization, the need for efficient parking management solutions is becoming increasingly urgent. This research develops and implements a car detection system based on YOLOv8 (You Only Look Once Version 8) for smart parking applications using Raspberry Pi and the Node-RED platform. This system is designed to optimize the use of parking spaces and increase parking management efficiency by utilizing YOLO's real-time object detection capabilities. Data processed by the Raspberry Pi is sent to the Node-RED platform for Internet of Things (IoT) via MQTT protocol. Node-RED functions as a management and visualization system, allowing users to monitor parking status in real-time through an intuitive graphical interface. With Node-RED, users can find out which parking lots are full and which areas are still available.
Personal Tool for Protection on the Net Yasir Ali Mahmood
International Journal Of Electrical Engineering and Inteligent Computing Vol 2, No 1 (2024): International Journal Of Electrical Engineering And Intelligent Computing
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/ijeeic.v2i1.9105

Abstract

Every time a computer device connects to the Internet it is at risk. Data theft is one of the threats facing computers when they connect to the Internet. For a computer to connect to the Internet, it needs an IP address and a port address to send and receive data. When the data reaches the computer via a port, it needs to reach the process that requested this information, which is linked to that port. A process does all the internet connections by the compute. These processes need an approach to send and receive information, which is the ports themselves. The attacker uses this port to make a connection to the victim's computer to steal information. In such situations, support is crucially needed to prevent these attacks from affecting our system. This work develops a personal tool for helping users to protect themselves from external attacks. The proposed tool monitors the open ports and shows all the information about the processes that are used. The proposed tool can close the open port, kill the process associated with it, and delete the process. When closing this port, the attacker cannot have access to the victim's computer. The findings show that the proposed tool is highly efficient when it comes to computer protection. The experimental results also demonstrate that the features of the tool can be tuned to fit users’ interest.
Hybrid Systems for Energy Distribution and Telecommunication Reliability in Smart Grids Saidah Sayuti; Hariani Ma'tang Pakka; Andi Syarifuddin; Muhammad Yusuf Mappeasse; Widya Wisanty
International Journal Of Electrical Engineering and Inteligent Computing Vol 2, No 1 (2024): International Journal Of Electrical Engineering And Intelligent Computing
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/ijeeic.v2i1.9520

Abstract

The integration of energy distribution systems and telecommunication networks is crucial for improving the reliability, efficiency, and scalability of smart grids. However, challenges such as electromagnetic interference (EMI), latency, and fault tolerance complicate seamless operation. This study proposes a hybrid framework using MATLAB/Simulink to model and simulate energy distribution, real-time monitoring, and fault detection in high-voltage environments. The simulation framework consists of a high-voltage energy distribution network modeled with multiple buses, transformers, and distributed renewable energy sources. IoT-based sensors are strategically placed at critical nodes to collect real-time voltage and current data, which are transmitted via 5G communication protocols using the MQTT messaging standard. Fault detection is performed using an AI-driven Support Vector Machine (SVM) algorithm, trained with historical fault data to detect anomalies and classify fault types with high accuracy. The simulation environment integrates power flow analysis, real-time fault detection mechanisms, and communication latency assessment to evaluate system performance. Key findings demonstrate up to 92.8% energy efficiency with 60% renewable energy penetration, fault recovery times reduced to 35 ms through AI-based detection, and communication latency maintained below 15 ms for IoT-based monitoring. These results validate the proposed framework’s ability to address critical challenges in smart grids, including EMI mitigation, fault tolerance, and system scalability. This research bridges the gap between energy distribution and telecommunication systems, offering a scalable and sustainable solution for smart grid optimization.
Improving Artificial Intelligence Techniques for Classifying the Vessels of the Grand Mosque of Al-Nuri Ruba Talal Ibrahim
International Journal Of Electrical Engineering and Inteligent Computing Vol 2, No 1 (2024): International Journal Of Electrical Engineering And Intelligent Computing
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/ijeeic.v2i1.9620

Abstract

The Grand Mosque of al-Nuri is a historic mosque that preserves the civilized history of Mosul. It is one of the oldest mosques in the city and contains the Al-Hadba Minaret, which includes the same name as the city of Mosul. This minaret is distinguished by its architectural design and its varied and wonderful decorations. The architectural design of the mosque is unique. The mosque was damaged during the ISIS campaign in Mosul, and the majority of the vessels and relics within it were broken. As a result, it became important to conserve and electronically document the remaining archeological landmarks. So, in this study a hybrid was made between pre-training model to extract features and machine learning methods to classify the dataset of the vessels of the Grand Mosque of al-Nuri. Several pre-processing was applied to the images and then passed to DenesNet201 to extract features and send them to the Extra Tree and Random Forest methods to classify them into pottery and ceramic categories. The results showed that the two hybrid methods outperformed traditional machine learning methods with an accuracy of 98% and 93%, respectively.
Overload Protection and Electricity Volume Monitoring on Internet of Things (IOT)-Based Three-Phase Induction Motors Ramly Rasyid; Miftah Muhammad; Mochammad Apriyadi Hadi Sirad
International Journal Of Electrical Engineering and Inteligent Computing Vol 2, No 1 (2024): International Journal Of Electrical Engineering And Intelligent Computing
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/ijeeic.v2i1.9711

Abstract

The protection and monitoring of the amount of electricity in three-phase induction motors that are widely used in the industry needs to be carried out continuously so that the performance of the motor continues to run well and if there is a disturbance, it can be known early. The purpose of the research to be carried out is to make a device to protect and monitor the amount of electricity of a three-phase induction motor based on the Internet of Things (IoT) and see the performance of the device. From the results of the overload protection test with the three-phase induction motor load current indicator, it can be seen that when the motor is loaded until the current rises at the R phase of 1.23 A, the S phase 1.31 A, and the T phase 1.24 A, which means that the maximum current of the induction motor is exceeded by 0.401 A as the relay works to protect the induction motor. As for the calculation of the measurement error presentation, it can be seen that for the error presentation, the voltage measurement ranges from 0.001% to 0.088%, current 0.001% to 3.509%, power factor 0.433% to 4.438%, apparent power 0.020% to 3.774%, active power 0.149% to 4.904%, and reactive power 0.008% to 4.455%.  The tool that is made works well because the protection runs well and the error presentation is below 5%. 

Page 1 of 1 | Total Record : 5

 1 

Filter by Year

2024 2024


Reset
Filter By Issues
All Issue Vol 3, No 1 (2025): International Journal Of Electrical Engineering And Intelligent Computing Vol 2, No 2 (2025): International Journal Of Electrical Engineering And Intelligent Computing Vol 2, No 1 (2024): International Journal Of Electrical Engineering And Intelligent Computing Vol 1, No 2 (2024): International Journal Of Electrical Engineering And Intelligent Computing Vol 1, No 1 (2023): International Journal of Electrical Engineering and Intelligent Computing