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INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
ISSN : 25024752     EISSN : 25024760     DOI : -
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Articles 65 Documents
Search results for , issue "Vol 39, No 1: July 2025" : 65 Documents clear
Smart enterprise architecture framework for developing patent office Prihastomo, Yoga; Prabowo, Harjanto; Trisetyarso, Agung; Soeparno, Haryono
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 1: July 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i1.pp681-690

Abstract

Technology and communication’s impact on daily life makes innovation vital for economic growth, highlighting prizing intellectual property (IP) asset protection and management. Patent office, pivotal custodians of legal frameworks and repositories of IP assets, grapples with significant challenges, and backlogs stemming from escalating patent applications and outdated processes. Patent office encounters the challenge of balancing innovation and IP protection because of the convergence of rapid advancements in technologies, for instance, AI, and blockchain. This research employs a design science research methodology to generate a tailored framework addressing these multifaceted challenges. The proposed smart enterprise architecture (SEA) framework offers a strategic, multidimensional approach to modernizing the patent office. It integrates principles from enterprise architecture, information systems management, and IP law, emphasizing efficiency, scalability, and security. The framework leverages the quadruple helix model, fostering collaboration between government, industry, academia, and civil society to enhance stakeholder engagement and innovation ecosystems. Optimizing patent office functions and adapting to IP management’s evolution, the SEA framework integrates technology and organizational goals for a comprehensive approach.
New technic of transfer learning for detecting epilepsy by EfficientNet and DarkNet models Edderbali, Fatima; El Malali, Hamid; Essoukaki, Elmaati; Harmouchi, Mohammed
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 1: July 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i1.pp345-352

Abstract

Epileptic seizures are one of the most prevalent brain disorders in the world. Electroencephalography (EEG) signal analysis is used to distinguish between normal and epileptic brain activity. To date, automatic diagnosis remains a highly relevant and significant research topic which can help in this task, especially considering that such diagnosis requires a significant amount of time to be carried out by an expert. As a result, the need for an effective seizure approach capable to classify the normal and epileptic brain signal automatically is crucial. In this perspective, this work proposes a deep neural network approach using transfer learning to classify spectrogram images that have been extracted from EEG signals. Initially, spectrogram images have been extracted and used as input to pre-trained models, and a second refinement is performed on certain feature extraction layers that were previously frozen. The EfficientNet and DarkNet networks are used. To overcome the lack of data, data augmentation was also carried out. The proposed work performed excellently, as assessed by multiple metrics, such as the 0.99 accuracy achieved with EfficientNet combined with a support vector machine (SVM) classifier.
Advanced generalized integrator based phase lock loop under complex grid condition: a comparative analysis Tripathy, Poonam; Misra, Banishree; Nayak, Byamakesh
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 1: July 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i1.pp23-32

Abstract

Integration of renewable energy systems (RESs) to the grid leads to various power quality issues. A proper control approach for the interfaced inverter is required to mitigate the uncertainties caused in the grid due to the RESs association to maintain the grid stability. The presence of harmonics and DC offset in the input grid voltage of a phase lock loop (PLL) leads to inaccurate phase estimation due to fundamental frequency oscillations. Though many advanced generalized integrator (GI) based PLLs have been developed still there is a need for a robust PLL for synchronization with faster dynamic response, both the harmonics and DC offset rejection ability with precise estimation. This paper proposes some simple yet effective advanced PLLs employing low pass filters (LPFs) in the existing GI based PLLs for faster and accurate phase angle estimation for seamless synchronization under complex grid circumstances. These advanced generalized integrators with LPFs (GI-LPF) based PLLs will provide enhanced and robust synchronization for the grid integrated RESs thereby addressing multiple power quality issues like voltage unbalance, harmonics and DC offsets. The simulation based comparative analysis of the proposed controllers confirm their effective disturbance rejection capability under complex grid conditions by providing advanced and precise response.
An approach for loss minimization and capacity savings in residential microgrid networks in Oman Sreedharan, Sasidharan; Solanki, Parmal Singh; Abdelfatah, Magdy S.; Wartana, I Made
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 1: July 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i1.pp1-10

Abstract

In this paper, an approach for end-user-based energy saving and loss reduction technique in residential networks has been proposed. The proposed approach is applied to an Oman case study of community microgrid networks by connecting automatically switched capacitors to improve power factor and analyzed for capacity saving and loss minimization. The proposed approach can reduce the cost of electrical bills in the total community microgrid by minimizing losses and the capacity investment cost saving of all equipments in the transmission and distribution line from the generation to the end user. In addition, this study focuses on the healthy conclusion that average kVA capacity could be saved to an extent of 12.22% and in economic terms, approximately USD 3.68 per hour in the microgrid. This proposed technique can be implemented as a model community project for other similar residential community systems.
Web GIS-based postcode alternative system for resolving “last mile” problem in Jordan’s home delivery Omar, Firas; Nabot, Ahmad; Sowan, Bilal
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 1: July 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i1.pp531-544

Abstract

As more and more people shop online, the postal code system must be more dependable. Due to the absence of a comprehensive postcode system, online purchases and shipping in the developing country of Jordan are complicated. This research paper proposes an alternative delivery system for delivering online purchases to customers without postal codes. Smartphone and computer-based geographic information system (GIS) applications evaluated in Jordan. The scientists found that the users were eager to adopt the system based on its ease of use and adoption rate. A questionnaire survey was distributed to 167 retail stores, delivery logistics employees, university students, and academics. The data collected were then analyzed using SPSS techniques such as POST HOC and ANOVA. To find a home delivery solution, we tested the suggested system app on both desktop and Smartphone platforms. The findings show that it is easier to locate a residential neighborhood. Customer trust and satisfaction with online purchases should increase due to the additional benefits of the system installation. Improve the effectiveness of home delivery services in Jordan with the use of artificial intelligence (AI). Both customers and stores prefer this system for online shopping rather than using postcodes. According to these data, experts can enhance their items by implementing digital sales strategies.
Design and development of an automated spirulina (Arthrospira platensis) algae cultivator Mariñas II, Miguel Q.; B. Enojas, Mark Joseph; Balolong, Daryll C.; B. Correa, Charissa Zandra; C. Roldan, Lemmuel Keith; Teves, Mark Lester; Dela Cruz, Christian Mari
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 1: July 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i1.pp139-147

Abstract

The cultivation of algae has gotten more attention from algae enthusiasts who have seen the benefits of algae in many uses. To maximize productivity, the parameters for growth of this algae must be controlled, such as pH, turbidity, light intensity, and the mixture solution for optimal growth. In this paper, an automated spirulina algae cultivator is designed and developed in a small-scale pond to replace the existing manual process. The system developed is composed of compact and modular cultivation unit, ph sensor, water level sensor, turbidity sensor, light intensity sensor, and motor actuators for mixing solutions. Each parameter was controlled individually in an on-off control system. A simple nutrient addition program (SNAP) solution is also used for better growth productivity by maximizing its nutrient contents. The pH is maintained at 9 to 12 for a healthy biomass output. Daily weight measurement was conducted using an analytical balance to monitor its growth. Using the developed prototype recorded a 33% higher rate of productivity over the manual process. This setup can potentially be used as a model for mass production of spirulina algae.
Robust k-NN approach for classifying Aquilaria oil species by compounds Ahmad Sabri, Noor Aida Syakira; Syafiqah Noramli, Nur Athirah; Nik Kamaruzaman, Nik Fasha Edora; Ismail, Nurlaila; Yusoff, Zakiah Mohd; Almisreb, Ali Abd; Tajuddin, Saiful Nizam; Taib, Mohd Nasir
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 1: July 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i1.pp178-189

Abstract

Accurate classification of Aquilaria oil species is essential for ensuring the quality and authenticity of agarwood oils, which are widely used in perfumes and traditional medicine. This study investigated the effectiveness of the k-nearest neighbours (k-NN) machine learning model for classifying Aquilaria oil species based on four significant chemical compounds: dihyro-βagarofuran, δ-guaiene, 10-epi-γ-eudesmol, and γ-eudesmol. The dataset comprised 480 samples of Aquilaria oil, which were analyzed using gas chromatography-mass spectrometry (GC-MS) and gas chromatography-flame ionization detector (GC-FID). The k-NN model, with an optimal k-value of 10 and using euclidean distance as the distance metric, achieved 100% accuracy, sensitivity, specificity, and precision in both training and testing datasets. These results demonstrate the robustness of k-NN in species identification, highlighting the discriminative power of the selected compounds. This study verifies that the integration of chemical profiling with machine learning offers a scalable solution for accurate species identification in the essential oil industry. Future work could explore hybrid models and data expansion techniques to further enhance the classification performance in more complex environmental conditions.
Hybrid energy storage solutions through battery-supercapacitor integration in photovoltaic installations Yousfi, Abdelkader; Mehedi, Fayçal; Bot, Youcef
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 1: July 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i1.pp11-22

Abstract

Batteries integrated into renewable energy storage systems may experience multiple irregular charge and discharge cycles due to the variability of photovoltaic energy production characteristics or load fluctuations. This could negatively impact the battery’s longevity and lead to an increase in project costs. This article presents an approach for the sharing of embedded energy between the battery, which serves as the main energy storage system, and the supercapacitors (SC), which act as an auxiliary energy storage system. By delivering or absorbing peak currents according to the load requirements, supercapacitors increase the lifespan of batteries and reduce their stresses. An maximum power point tracking (MPPT) algorithm regulates the connection of the photovoltaic (PV) cells to the DC bus through a boost converter. A buck-boost converter connects supercapacitors and batteries to the DC bus. A DC-AC converter connects the inductive load to the DC bus. The system regulates static converters connected to batteries and supercapacitors based on current. An energy management block supervises the system components. We implement the entire system in the MATLAB/Simulink environment. We present the simulation results to demonstrate the effectiveness of the proposed control strategy for the entire system.
A comparative analysis of hybrid of traditional load flow methods for IEEE distributed power generation networks Mohamed Hariri, Muhammad Hafeez; Daud, Noor Dzulaikha; Mohd Yusoff, Nor Azizah; Syed Zaman, Syed Muhammad Zakwan; Mat Desa, Mohd Khairunaz
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 1: July 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i1.pp33-44

Abstract

Analyzing power flow or load flow is crucial for planning, operating, maintaining, and controlling electrical power systems. Two traditional power flow methods namely the Newton-Raphson (NR) method are known for their accuracy and robustness nevertheless high computational intensity, and the fast decoupled load flow (FD) method, is valued for its computational efficiency and speed, however, generating less accurate data. This research aims to develop a hybrid load flow technique that integrates both strengths, achieving higher accuracy and faster convergence. The validation processes are based on several IEEE standard bus systems, including the 3-bus, 9-bus, 14-bus, and 30-bus systems. These systems, with different bus types and interconnections, represent real-world operations and help generate comprehensive data on iteration count, execution time, and the accuracy of the output data results. A new hybrid method generated from this research work compared to traditional load flow methods, provides a substantially well-balanced number of iteration counts, the fastest execution times, improved by 41.55%, and produces a similar accuracy of the data set. These improvements make the hybrid method highly advantageous in practical real-time applications and large-scale systems where both accuracy and speed are critical.
Short-term recall comparison of iconic auditory and visual feedback stimuli in a memory game Wersényi, György; Csapó, Ádám; Tóllár, József
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 1: July 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i1.pp310-321

Abstract

Multimedia user interfaces incorporate various feedback methods using different modalities. Cognitive processing of audiovisual information requires the ability to recall visual and auditory information, either separately, or in combination. Short-term memory capabilities vary individually and depend on factors such as signal presentation and the number and type of visual and auditory items. In an experiment involving 40 subjects, we aimed to compare short-term auditory and visual capabilities in a serious game application. Subjects played the ‘Pairs’ game at different resolutions, using either visual icons or audio samples, while the total time cost and number of flips were recorded. The results indicate that visual memory is not superior, and female subjects performed better than males at higher levels in the visual task. Additionally, human sound samples, speech and familiar auditory icons were found to be easier to recall than artificial measurement signals.

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