Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) is a peer reviewed International Journal in English published four issues per year (March, June, September and December). The aim of Indonesian Journal of Electrical Engineering and Informatics (IJEEI) is to publish high-quality articles dedicated to all aspects of the latest outstanding developments in the field of electrical engineering. Its scope encompasses the engineering of Telecommunication and Information Technology, Applied Computing & Computer, Instrumentation & Control, Electrical (Power), Electronics, and Informatics.
Articles
783 Documents
<![CDATA[Multi-Objective Reinforcement Learning Based Algorithm for Dynamic Workflow Scheduling in Cloud Computing ]]>
<![CDATA[Sudhakar, Rayapati V.]]>;
<![CDATA[Dastagiraiah, C.]]>;
<![CDATA[Pattem, Sampurnima]]>;
<![CDATA[Bhukya, Sreedhar]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 12, No 3: September 2024 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v12i3.5728
<![CDATA[It is essential to consider the infrastructures of workflows as a critical research area where even slight optimizations can significantly impact infrastructure efficiency and the services provided to users. Traditional workflow scheduling approaches using heuristics may not be efficient due to the dynamic workloads and diverse resources of cloud infrastructure. Additionally, the resources at any given time have different states that must be considered during workflow scheduling. The emergence of artificial intelligence has made it possible to address the dynamics and diverse resources of cloud computing during workflow management. In particular, reinforcement learning enables understanding the environment at runtime with an actor and critic approach to make well-informed decisions. Our paper introduces an algorithm called Multi-Objective Reinforcement Learning based Workflow Scheduling (MORL-WS). Our empirical study with various workflows has demonstrated that the proposed multi-objective reinforcement learning-based approach outperforms many existing scheduling methods, especially regarding makespan and energy efficiency. The proposed method with the Montage workflow demonstrated superior performance compared to scheduling 1000 tasks, achieving a least makespan of 709.26 and least energy consumption of 72.11 watts. This indicates that the proposed method is suitable for real-time workflow scheduling applications.]]>
<![CDATA[A Development of Supporting System for Historical Heritage Based Tourism ]]>
<![CDATA[Boonmee, Salinun]]>;
<![CDATA[Somsuphaprungyos, Suwit]]>;
<![CDATA[Natho, Parinya]]>;
<![CDATA[Boonying, Sangtong]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 12, No 3: September 2024 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v12i3.5089
<![CDATA[Tourism is a major economic contributor in Thailand. With the richness of historical heritage recognized as world heritages, Phra Nakhon Si Ayutthaya province is a famous destination for tourists who enjoy historical and cultural tourism. This work presents a development of a supporting system for tourism in Phra Nakhon Si Ayutthaya province in regarding of historical and cultural aspects of heritages. This work designs an ontology to represent a relation network of properties from tourist attractions based on historical and cultural relationship among them. Instances which are the heritages hence are related and can be visualized in a form of a graph. The suggestion module is designed to provide related tourist destination following the relations from the generated knowledge graph based on the initial query of a user. The experiment results signify that the system revealed hidden historical relations of destinations to users and made them learn the values of history lied within heritages. Furthermore, 87.5% of participants decided to make a tour plan following the suggested destinations since they found the linking in historical values to be more meaningful and interesting.]]>
<![CDATA[A Compact Inset Coupled-Fed Triangular Patch Antenna For Wideband 5G Applications ]]>
<![CDATA[C, Mohan]]>;
<![CDATA[J, Silamboli]]>;
<![CDATA[S, Divya]]>;
<![CDATA[R, Shantha Sheela]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 12, No 3: September 2024 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v12i3.5677
<![CDATA[For 5G applications, a compact inset coupled-fed high bandwidth triangle antenna is demonstrated. A large bandwidth can be achieved by combining the inset and coupling feeding with a triangle-shaped patch. With a VSWR of less than 2, the suggested antenna's working frequency of 3.6 GHz spans the frequency range needed for 5G applications, which is between 2.8 and 5.6 GHz. The primary characteristics of the suggested antenna are its smaller dimensions (20.5 × 17.5 mm2) and about 35% increased bandwidth. Significant factors that match the simulated results exactly are S11, radiation pattern, radiation efficiency, and peak gain in the proceeding of the proposed antenna. With the addition of two parallel rectangular strips with a triangular-shaped patch, the antenna is capable to achieve 40% reductions in size, 81.74% radiation efficiency, and 2.61 dB peak gain for the suggested antenna. With a center frequency of 3.6 GHz and a reflection coefficient of 28.6 dB, the fractional bandwidth is 66.67% (2.8 GHz to 5.6 GHz). With a smaller surface wave and an excellent omnidirectional radiation pattern, the antenna's inset coupling feeding arrangement makes it appropriate for Sub-GHz 5G applications. ]]>
<![CDATA[Performance Evaluation of Advanced PLL Techniques For Accurate FFPS Component Extraction ]]>
<![CDATA[Saritha, M]]>;
<![CDATA[Sidram, M H]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 12, No 3: September 2024 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v12i3.5686
<![CDATA[It is very necessary to adopt fundamental frequency positive sequence (FFPS) element extraction methods in order to maximise the efficiency of integrating and handling the use of renewable energy sources (RES). The decision to act in this manner is made with the purpose of contributing to the accomplishment of the aforementioned aim. The capability of the synchronous references frame phase-locked loop to reject variations over a broad variety of grid conditions is enhanced as a result of this. This is particularly true for voltage sags and surges that are accompanied by harmonics, irrespective of whether the harmonics are the result of balanced or unbalanced electrical current fluctuations. The accuracy of the extraction of FFPS components is significantly influenced by the frequency deviation in SRF-PLL systems. The frequency deviation is another critical component. This is a result of the frequency deviation not remaining constant. An investigation is being conducted to ascertain the effectiveness of a various advanced PLL techniques, such as the cascaded delayed signal cancellation (CDSC), the dual second-order generalized integrator (DSOGI) and the multiple delayed signal cancellation (MDSC). The objective of conducting this assessment is to facilitate the evaluation of the efficacy of these strategies, which is the reason for its implementation. The CDSC and MDSC PLL have been demonstrated to be preferable to other PLLs due to their ability to distinguish between even and odd harmonics. This is due to the fact that each of these harmonics possesses its own distinctive characteristics. This may be attributable to its capacity to independently identify either harmonic. The MATLAB simulation results is provided to demonstrate the exceptional performance of these highly advanced PLLs.]]>
<![CDATA[Novel Polar Coded MIMO Power Domain NOMA Scheme for 5G New Radio (NR) ]]>
<![CDATA[Pavithra, B]]>;
<![CDATA[Chakraborty, Parnasree]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 12, No 3: September 2024 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v12i3.5670
<![CDATA[The use of Polar coded Multiple Input Multiple Output Power Domain Non-Orthogonal Multiple Access (MIMO PD-NOMA) technology has the potential to greatly improve the capacity and spectral efficiency of 5G NR systems. From the on-going research, there is a combination of polar coded NOMA and Polar coded MIMO techniques are approached separately with other channel coding techniques. This paper introduces a novel approach to combine polar coded with MIMO power domain NOMA to enhance the system performance. MIMO Power Domain NOMA that utilizes polar codes for channel coding and power allocation. By combining the benefits of NOMA and MIMO, which permits multiple users to share frequency-time resources simultaneously and the MIMO employs multiple antennas to increase diversity gain and spatial multiplexing gain. The proposed scheme provides effective utilization of radio resources where the polar codes are an optimal choice for 5G NR systems due to their strong error correction capability and low complexity decoding. Successive Cancellation List -Singular Value Decomposition adaptive scaling algorithm (SCL-SVD) is proposed in the polar decoding process. The suggested method attains 6.5 dB coding gain and improved throughput of 80.34% using MATLAB simulation. The proposed model compared with the other existing model such as Power Domain NOMA (PD-NOMA), multiple input single output NOMA (miso-NOMA) and multiple input multiple output NOMA (mimo-NOMA) in terms of Bit Error Rate (BER) and Signal to Noise Ratio (SNR). This scheme has the potential for practical implementation and can play a crucial role in meeting the increasing demands of future wireless communication systems.]]>
<![CDATA[BERT-BiLSTM model for hierarchical Arabic text classification ]]>
<![CDATA[Hamzaoui, Benamar]]>;
<![CDATA[Bouchiha, Djelloul]]>;
<![CDATA[Bouziane, Abdelghani]]>;
<![CDATA[Doumi, Noureddine]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 12, No 3: September 2024 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v12i3.5659
<![CDATA[Text classification is a fundamental task in natural language processing (NLP) aimed at categorizing text documents into predefined categories or labels. Leveraging artificial intelligence (AI) tools, particularly deep learning and machine learning, has significantly enhanced text classification capabilities. However, for the Arabic language, which lacks comprehensive resources in this domain, the challenge is even more pronounced. Hierarchical text classification, which organizes categories into a tree-like structure, presents added complexity due to inter-category similarities and connections across different levels. In addressing this challenge, we propose a deep learning model based on BERT (Bidirectional Encoder Representations from Transformers) and BiLSTM (Bidirectional Long Short-Term Memory). Experimental evaluations demonstrate the effectiveness of our approach compared to existing methods, yielding promising results. Our study contributes to advancing text classification methodologies, particularly in the context of Arabic language processing.]]>
<![CDATA[ML-ACID: a Modified Machine Learning Algorithm Coupled With a Novel Ant Colony Approach for Intrusion Detection in IOT ]]>
<![CDATA[Belkhiri, Hamza]]>;
<![CDATA[Messai, Abderraouf]]>;
<![CDATA[Belhadad, Yehya]]>;
<![CDATA[Andre-Luc, Beylot]]>;
<![CDATA[Salheddine, Sadouni]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 12, No 3: September 2024 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v12i3.5533
<![CDATA[Software Defined Networks is becoming increasingly important in IoT because it allows devices to communicate more easily it provides the flexibility and centralized management, however in recent years these networks have witnessed a widespread spread of cyber-attacks that has a significant and negative impact on the availability of services. In this paper, we propose a novel approach for intrusion detection in Software Defined Networks for IoT. our work inspired by the self-defense mechanism of ant colonies. The approach uses a self-adaptable colony fingerprint and based on multiple parameters, it makes the detection of intrusions easy and filters out every other legitimate communication within the network. A machine learning model is used to provide basic predictions about the communication that later drives the evolution of the colony in terms of self-defence. The whole approach is implemented in a simple switch using Ryu-controller and analyses OpenFlow datagrams. The meta-heuristic implication of using ant colony optimization improved approach provides the system with reliability and high performance of detecting and blocking threats. in the end interesting results based on several scenarios shows the usability of our approach.]]>
<![CDATA[Design of Robust Centralized PID Optimized LQR Controller for Temperature Control in Single-Stage Refrigeration System ]]>
<![CDATA[Ekengwu, Bonaventure Onyeka]]>;
<![CDATA[Eze, Paulinus Chinaenye]]>;
<![CDATA[Muoghalu, Chidiebere Nnaedozie]]>;
<![CDATA[Asiegbu, Christopher Nnaemeka]]>;
<![CDATA[Achebe, Patience Nkiruka]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 12, No 3: September 2024 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v12i3.5629
<![CDATA[Refrigeration systems are used for many purposes such as food preservation, cooling and others. They require controller to ensure that the refrigerating cycle can go ON and OFF to maintain a setpoint temperature. For instance, in preservation of food or other perishables, deterioration can occur without efficient system to ensure that temperature within refrigerating space is kept at a setpoint value. This paper presents robust centralized proportional integral and derivative (PID) optimized linear quadratic regulator (LQR) temperature control system for single-stage refrigeration system. A composite technique in which PID algorithm was used to adjust the gains of LQR is proposed. The model of single-stage vapour compressor refrigeration (VCR) system was established in terms of the evaporator, compressor, condenser and the expansion valve’s temperatures. An LQR was initially designed. Then a PID optimized LQR was design. The results indicated that the PID optimized LQR controller outperformed the LQR by providing 73.4% and 62.7% improvement for the evaporating temperature, 45.6% and 71.4% improvement for the compression temperature, 30% and 84.6% improvement for the condensing temperature, and lastly 72% and 70.2% improvement for the expansion temperature in terms of response time and settling time. Simulation with test data proved its robustness and effectiveness in tracking setpoint temperature. Generally, the proposed system has shown capacity to offer robust and centralized tracking in the presence of changing setpoint values. ]]>
<![CDATA[Comparative Analysis of Hardware Performance for Linear Detection in a Massive MIMO System on FPGA Using the Vivado HLS Tool ]]>
<![CDATA[Ismail, Nurulhuda]]>;
<![CDATA[Jabbar, Mohamad Hairol]]>;
<![CDATA[Joret, Ariffuddin]]>;
<![CDATA[Katiran, Norshidah]]>;
<![CDATA[Saadon, Eddy Irwan Shah]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 12, No 3: September 2024 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v12i3.5356
<![CDATA[This paper compares the performance of hardware implementation for linear detection in a massive MIMO system. The study focuses on Gram matrix inversion solved using two approaches: direct and indirect matrix inversion. Direct matrix inversion is represented by Cholesky Decomposition, while indirect matrix inversion is represented by the Neumann series and the Gauss-Seidel method. The algorithm for inversions, embedded in a C-based function, is virtually implemented on the FPGA using the Vivado HLS tool. The synthesis report categorizes the performance from the FPGA implementation into three parts: timing (ns), cycle latency, and resource utilization. With the same targeted time limit, indirect matrix inversion such as the Neumann series seems to be the fastest algorithm compared to the direct method due to the matrix-matrix multiplication approach. In terms of latency, NS requires more clock cycles to obtain the output compared to others. Based on the results, the direct inversion method exhibits higher complexity, particularly in timing for clock frequency and resource utilization needed to complete the inversion]]>
<![CDATA[Photometric Stereo-based Woven Fabric Pattern Recognition Using Wavelet Image Scattering ]]>
<![CDATA[Setiawan, Irwan]]>;
<![CDATA[Juliastuti, Endang]]>;
<![CDATA[Kurniadi, Deddy]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 12, No 4: December 2024 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v12i4.5589
<![CDATA[The weave pattern is a crucial factor that enhances the strength and stability of the fabric. Pattern recognition of woven fabric based on vision methods has been widely developed. In this research, woven fabric's basic weaving pattern recognition is based on photometric stereo images. First, six images of woven fabric were taken, each with a different direction of light. Next, an unbiased photometric stereo algorithm was used to reconstruct the six images. This paper used 23 grayscale photometric stereo images measuring 400 x 300 pixels. Augmentation techniques were carried out to produce 458 images consisting of 240 plain woven images, 159 twill woven images, and 60 satin woven images. The training data set consists of 367 images, and testing consists of 192 images. The feature extraction method uses wavelet image scattering and classification using Principal Component Analysis (PCA) and Support Vector Machine (SVM). The wavelet image scattering method effectively extracts texture features of photometric stereo images of diverse woven fabrics, while the PCA and SVM methods successfully classify the basic woven fabric patterns. The results of recognizing the basic woven fabric pattern using PCA and SVM classification obtained an accuracy of 98.57%.]]>
