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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
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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 2 (2025): International Journal Of Electrical Engineering And Intelligent Computing" : 5 Documents clear
Proposed method for digital image normalisation Omar Muayad Abdullah
International Journal Of Electrical Engineering and Inteligent Computing Vol 2, No 2 (2025): 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.v2i2.10096

Abstract

Image normalisation is considered as an important factor in the scope of image enhancement. In this research paper we introduced a proposed model used for image normalisation (contrast stretching) through two phases, design phase and implementation phase. First, the design phase consists of the proposed formulas used for processing the degraded images, where the first formula represents the processing of the darked image illuminations and the second one represents the processing of the highlighted image illuminations, the second part of the design phase we determined which formula has to be used for processing the image degradation. So here for processing this part, we used a K-means clustering machine learning algorithm. The second part is the implementation phase which is used for applying the proposed model and the final step comparing the obtained results with other determined normalisation algorithms.
Recommendation systems: A Review Zaid Mundher
International Journal Of Electrical Engineering and Inteligent Computing Vol 2, No 2 (2025): 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.v2i2.9956

Abstract

Recommendation systems have become one of the most widespread types of systems today, as they have become a necessity and a need. Recommendation systems can be defined as methods for presenting or marketing electronic products (in various forms) to users, with the selection of products based on the user's actual needs. This is achieved through the use of specific algorithms and methods to gauge the user's interest in the suggested products. Recently, the applications of recommendation systems have expanded beyond a single field or aspect, extending into many areas of life and science. Many methods have been developed and improved for building recommendation systems from naive to advanced ones.This study aims to provide a comprehensive overview of recommendation systems: definitions, objectives, and types, including the advantages and disadvantages of each type.
Comparative Performance Analysis of VANET Routing Protocols under Dynamic Node Mobility Fahrizal Djohar; Hafid Syaifuddin; Dharmawan Dharmawan
International Journal Of Electrical Engineering and Inteligent Computing Vol 2, No 2 (2025): 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.v2i2.10058

Abstract

Vehicular Ad Hoc Networks (VANETs) face significant challenges in maintaining reliable communication due to high node mobility and frequent topology changes. This study evaluates the throughput performance of two routing protocols—one proactive and one reactive—under varying speed scenarios using the NS-3 simulator. Simulations were conducted in an area with node speeds set at 10 m/s (36 km/h) and 20 m/s (72 km/h). NetAnim was used to visualize node movement and routing behavior. The results show that the reactive protocol outperforms the proactive protocol in high-mobility scenarios by maintaining higher throughput and reducing routing overhead. These findings highlight the importance of selecting routing protocols that adapt effectively to different mobility conditions in VANETs, contributing to the design of more efficient vehicular communication systems.
A Multimodal Deep Learning Framework for Early Detection of Congenital Heart Disease in Neonates Iis Hamsir Ayub wahab; Sri Yati
International Journal Of Electrical Engineering and Inteligent Computing Vol 2, No 2 (2025): 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.v2i2.10059

Abstract

Congenital heart disease (CHD) is the most common congenital defect and still adds significantly to the neonatal morbidity and mortality rates. Classic echocardiography and ECG unimodal data traditional methods are often unable to analyze complex, multifunctional, and multifactorial cardiac pathologies in neonates. This paper presents an explainable multimodal deep learning framework that acquires four diverse sources of clinical data. Multimodal data includes echocardiogram videos, ECG, and other physiological and structured electronics health record (HER) data. We propose a self-attention-based late fusion transformer architecture that also uses self-attention mechanisms. The model trains and validates on benchmark datasets, which are transparently and reproducibly available (EchoNet-Dynamic, MIMIC-IV, PhysioNet Capnobase, and MIT-BIH). The results achieved using the proposed model mark an improvement over existing benchmarks with 93% accuracy, 95% sensitivity, and 0.96 area under the ROC curve. Using interpretability modules, features that were value added towards determining the diagnostic indicators that were incorporated in the neonatal infant care were shown to be critically relevant. Moreover, the model shows high performance consistency across several data sources and shifts. The research illustrates the use of explainable deep learning architectures for automation of early-stage heart defect detection in newborns. Some of the future work includes validation through clinical studies and multilingual electronic health record integration.
Analysis of Rooftop Solar Power Plant Planning for Lecturers' Houses and Solar Street Lighting at Campus 4 Unkhair Sofifi Idham A Djufri; Faris Syamsudin
International Journal Of Electrical Engineering and Inteligent Computing Vol 2, No 2 (2025): 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.v2i2.10364

Abstract

The utilization of solar energy as a substitute for fossil energy has become a necessity in facing the global energy crisis due to the increasingly critical dependence on fossil energy. Additionally, the use of fossil energy causes environmental damage/climate crisis. The utilization of solar energy not only alleviates the global energy crisis but also produces environmentally friendly energy that can reduce carbon emissions resulting from the combustion of fossil fuels. Currently, the use of solar energy is not only implemented in areas that are not yet served by PLN electricity, but it is also used in almost all public facilities with the aim of transitioning energy from conventional electricity to renewable electricity. One of the uses of solar energy is through a centralized system to meet the electricity needs in the surrounding area, reducing the use of electricity sourced from fossil fuels, and decreasing carbon emissions that cause climate damage. This research aims to utilize solar energy to reduce the use of fossil fuel-based energy, which can harm the climate and environment, as well as to calculate the investment costs of using centralized solar power plants (PLTS). The method used in this research is data collection and the calculation of technical and economic needs. The research results indicate that the rooftop solar power system for the lecturer's house has a total power of 7,920 Watts, using 4 solar modules with a capacity of 450 wp per module. The battery capacity used is 120 Ah 48 volts, with 4 units. For solar street lighting, a total of 17 solar streetlight poles were obtained, each 7 meters high, with a lamp power of 40 watts per pole. The solar module capacity is 100 Wp and the battery capacity is 100 Ah.

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