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.
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<![CDATA[An Effective Model Of Autism Spectrum Disorder Using Machine Learning ]]>
<![CDATA[Razieh Asgarnezhad]]>;
<![CDATA[Karrar Ali Mohsin Alhameedawi]]>;
<![CDATA[Hani Akram Mahfoud]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 2: June 2023 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v11i2.4060
<![CDATA[Autism spectrum disorder (ASD) is one of the most common diseases that affect human nerves and cause a decrease in the intelligence and comprehension of the person. This disease is a group of various disorders that are characterized by poor social behavior and communication. It affects all age groups, including adults, adolescents, children, and the elderly, but the symptoms of this disease always appear in their early years. ASD suffer from problems, the most important of which are data loss, low quality, and extreme values. This makes the process of diagnosing the ASD early. Our goals in this research is to solve the ASD problems. The cussent authors proposed a technical model that solves all data problems. We used ensemble techniques that include Bayesian Boosting, Classification by Regression, Polynomial by Binominal Classification. We also used classification techniques that include CHAID, Decision Stump, Decision Tree (Weight-Based), Gradient Boosted Trees, ID3. It is proven that the proposed model solves data problems, and has obtained the highest search accuracy that has reached 100% as well as we have obtained the highest f1 measurement that has reached 100%. This proves that our work is superior to its peers.]]>
<![CDATA[Techniques for Improving the Performance of Unsupervised Approach to Sentiment Analysis ]]>
<![CDATA[Farha Naznin]]>;
<![CDATA[Anjana K. Mahanta]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 2: June 2023 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v11i2.4187
<![CDATA[In this work, few techniques were proposed to enhance the performance of unsupervised sentiment analysis method to categorize review reports into sentiment orientations (positive and negative). In review reports, generally negations can change the polarity of other terms in a sentence. Therefore, a new technique for handling negations was proposed. As it is seen that, the positions of terms in a report are also important i.e. the same term appearing at different positions in a report may convey different amount of sentiments. Thus, a new technique was proposed to assign weights to the terms depending on their positions of occurrences within a review. Again, another technique was proposed to use the presence of exclamatory marks in the reviews as the effects of exclamatory marks are equally important in categorizing review reports. After incorporating all these concepts in the first phase of the proposed method, in the second phase, analysis of sentiment orientations was done using cluster ensemble method. The proposed method was tested on a state-of-the-art Movie review dataset and 91.75% accuracy was achieved. A significant improvement over some of the unsupervised and supervised methods in terms of accuracy was achieved with incorporation of the new techniques.]]>
<![CDATA[Testable Design for Positive Control Flipping Faults in Reversible Circuits ]]>
<![CDATA[Mousum Handique]]>;
<![CDATA[Hiren K D Sarma]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 2: June 2023 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v11i2.4184
<![CDATA[Fast computational power is a major concern in every computing system. The advancement of the fabrication process in the present semiconductor technologies provides to accommodate millions of gates per chip and is also capable of reducing the size of the chips. Concurrently, the complex circuit design always leads to high power dissipation and increases the fault rates. Due to these difficulties, researchers explore the reversible logic circuit as an alternative way to implement the low-power circuit design. It is also widely applied in recent technology trends like quantum computing. Analyzing the correct functional behavior of these circuits is an essential requirement in the testing of the circuit. This paper presents a testable design for the k-CNOT based circuit capable of diagnosing the Positive Control Flipping Faults (PCFFs) in reversible circuits. The proposed work shows that generating a single test vector that applies to the constructed design circuit is sufficient for covering the PCFFs in the reversible circuit. Further, the parity-bit operations are augmented to the constructed testable circuit that produces the parity-test pattern to extract the faulty gate location of PCFFs. Various reversible benchmark circuits are used for evaluating the experimental results to establish the correctness of the proposed fault diagnosis technique. Also a comparative analysis is performed with the existing work.]]>
<![CDATA[A Cost Sensitive SVM and Neural Network Ensemble Model for Breast Cancer Classification ]]>
<![CDATA[Tina Elizabeth Mathew]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 2: June 2023 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v11i2.3934
<![CDATA[Breast Cancer has surpassed all categories of cancer in incidence and is the most prevalent form of cancer in women worldwide. The global incidence rate is seen to be highest in the country of Belgium as per statistics of WHO. In the case of developing countries specifically, India, it has overtaken other cancers and stands first in incidence and mortality. Major factors identified as impacting the prognosis and survival in the country is chiefly the late diagnosis of the disease and diverse situations prevailing in different parts of the country including lack of diagnostic facilities, lack of awareness, fear of undergoing existing procedures and so on. This is also true for many other countries in the world. Early diagnosis is a vital factor for survival. The implementation of machine learning techniques in cancer prediction, diagnosis and classification can assist medical practitioners as a supplementary diagnostic tool. In this work, an ensemble model of a polynomial kernel-based Support Vector machines and Gradient Descent with Momentum Back Propagation Artificial Neural Networks for Breast Cancer Classification is proposed. Feature selection is applied using Genetic Search for identifying the best feature set and data sampling techniques such as combination of oversampling and undersampling and cost senstivke learning are applied on the individual Neural Network and Support Vector Machine classifiers to deal with issues related with class imbalance. The ensemble model is seen to show superior performance in comparison with other models producing an accuracy of 99.12%.]]>
<![CDATA[A Novel Approach for improving Post Classification Accuracy of Satellite Images by Using Majority Analysis ]]>
<![CDATA[Swasti Patel]]>;
<![CDATA[Dr. Priya Swaminarayan]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 2: June 2023 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v11i2.4270
<![CDATA[In past one year, due to climatic changes and some anthropogenic activities, the forests of Uttarakhand are burning. To identify the damage caused by the forest fires, an area of Nainital district has been taken for the study. Multi temporal Landsat 7 images were taken from April - 2020 and April – 2021. This paper shows a novel approach to increase the accuracy of the classified image. The Support Vector Machine classification is first done and then to improve the accuracy of the classified image, a post-classification technique called Majority Analysis is applied. This method helps to classify the unclassified pixel and it also smoothens out the boundary of the classified pixels, leading to higher accuracy rate. The classification accuracy has improved significantly for April 2020 and April 2021 images from 89.35% to 98.71% and from 88.52% to 99.76% respectively. The change detection study showed a drastic increase in the barren land due to the forest fires and on the contrary, the forest, scarce forest and the shrub land areas have decreased.]]>
<![CDATA[Neuro-Fuzzy Combination for Reactive Mobile Robot Navigation: A Survey ]]>
<![CDATA[Brahim Hilali]]>;
<![CDATA[Mohammed Ramdani]]>;
<![CDATA[Abdelwahab Naji]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 2: June 2023 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v11i2.4009
<![CDATA[Autonomous navigation of mobile robots is a fruitful research area because of the diversity of methods adopted by artificial intelligence. Recently, several works have generally surveyed the methods adopted to solve the path-planning problem of mobile robots. But in this paper, we focus on methods that combine neuro-fuzzy techniques to solve the reactive navigation problem of mobile robots in a previously unknown environment. Based on information sensed locally by an onboard system, these methods aim to design controllers capable of leading a robot to a target and avoiding obstacles encountered in a workspace. Thus, this study explores the neuro-fuzzy methods that have shown their effectiveness in reactive mobile robot navigation to analyze their architectures and discuss the algorithms and metaheuristics adopted in the learning phase.]]>
<![CDATA[Pectoral Muscle Removal in Digital Mammograms Using Region Based Standard Otsu Technique ]]>
<![CDATA[Jacinta C. Anusionwu]]>;
<![CDATA[Vincent C. Chijindu]]>;
<![CDATA[Joy N. Eneh]]>;
<![CDATA[ThankGod I. Ozue]]>;
<![CDATA[Nnabuike Ezukwoke]]>;
<![CDATA[Mamilus A. Ahaneku]]>;
<![CDATA[Edward C. Anoliefo]]>;
<![CDATA[Walter A. Ohagwu]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 2: June 2023 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v11i2.4043
<![CDATA[Mammography is usually the first preference of imaging diagnostic modalities used for detection of breast cancer in the early stage. Two projections Cranio Caudal (CC) and Medio-Lateral Oblique (MLO) which depict different degrees for visualizing the breast are used during digital mammogram acquisition and the MLO view shows more breast tissue and Pectoral Muscle (PM) area when compared to CC view. Although, the PM is a criterion used to show proper positioning, it can result in biased results of mammographic analysis like: cancer detection and breast tissue density estimation, because the PM area has similar or even higher intensity than breast tissue and breast lesions if present. This paper proposed a Region Based Standard Otsu thresholding method for the elimination of PM area present in MLO mammograms. The proposed algorithm was implemented using 322 digital mammograms from the Mammographic Image Analysis Society (MIAS) database, and the difference between the PM detected and the manually drawn PM region by an expert was evaluated. The results showed an average: Jaccard Similarity Index, False Positive Rate (FPR) and False Negative Rate (FNR) of 93.2%, 3.54% and 5.68% respectively and also an acceptable rate of 95.65%]]>
<![CDATA[Development and Evaluation of a High-Performance Electrochemical Potentiostat-Based Desktop Application for Rapid SARS-CoV-2 Testing ]]>
<![CDATA[Faisal Ahmed Assaig]]>;
<![CDATA[Teddy Surya Gunawan]]>;
<![CDATA[Anis Nurashikin Nordin]]>;
<![CDATA[Rosminazuin Ab. Rahim]]>;
<![CDATA[Zainihariyati Mohd Zain]]>;
<![CDATA[Rozainanee Mohd Zain]]>;
<![CDATA[Fatchul Arifin]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 2: June 2023 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v11i2.4645
<![CDATA[The COVID-19 pandemic has necessitated the development of rapid and trustworthy diagnostic tools. Reverse transcription-polymerase chain reaction (RT-PCR) is the gold standard for detecting SARS-CoV-2 but has cost and time constraints. The sensitivity, specificity, and low cost of electrochemical biosensors make them an attractive alternative for virus detection. This study aims to develop and evaluate a high-performance desktop application for an electrochemical potentiostat-based SARS-CoV-2 test device, with a user-friendly interface that automatically interprets results, to expedite the testing process and improve accessibility, particularly in resource-limited settings. The application was built with the Electron framework and the HTML, CSS, and JavaScript programming languages. Our findings indicate that the developed electrochemical potentiostat-based desktop application demonstrates high accuracy compared to commercial software, achieving rapid detection within 30 seconds. The graphical user interface was found to be straightforward and user-friendly, requiring minimal training for efficient system operation. Our electrochemical potentiostat-based desktop application represents a valuable tool for rapid SARS-CoV-2 testing, particularly in settings with limited resources. This research contributes to developing rapid and reliable diagnostic tools for SARS-CoV-2 and potentially other pandemic-causing viruses, addressing the pressing need for improved public health surveillance and response strategies.]]>
<![CDATA[Classification of Cassava (Manihot sp.) Leaf Variants Using Transfer Learning ]]>
<![CDATA[Agus Pratondo]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 2: June 2023 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v11i2.4685
<![CDATA[There are several types of cassava leaves with different characteristics, tastes, and nutritional content. Some people use cassava leaves as a vegetable ingredient for daily consumption as a source of fiber and minerals. However, people often have difficulty identifying the different types of cassava leaves, including cassava leaf variants that are locally referred to as gajah, karet, and mentega. This study aims to use transfer learning to identify the variant of cassava leaves. The Inception v3 architecture was selected to build the classification model. To demonstrate the superiority of transfer learning, the Inception v3 architecture was run with two different weights. The first weight was randomly initialized, while the second weight was taken from pre-trained weights from ImageNet. The experimental results show that the classification accuracy rate using the pre-trained weights reached 95.76%. This indicates that the classification model used in this study is promising and can be used for practical purposes in everyday life.]]>
<![CDATA[Design and Analysis of a Fish-Friendly Micro Gravitational Water Vortex Power Plant (GWVPP) on Zarqa River, Jordan ]]>
<![CDATA[Aouda Arfoa]]>;
<![CDATA[Sadam Al-Mashakbeh]]>;
<![CDATA[Atef Saleh Al-Mashakbeh]]>;
<![CDATA[Abdullah Eial Awwad]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 2: June 2023 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/.v11i2.4382
<![CDATA[The main water source of Zarqa River is the treated wastewater from As-Samra Wastewater Treatment Plant (As-Samra WWTP) which is located in Zarqa Governorate in Al-Hashimiyya on the eastern part of the river; this means year-round flowing water in the eastern part of the river. This hydro energy is wasted continuously without exploiting it to generate electricity, but when trying to implement traditional hydropower projects on the river the main problem faced is low water head and low water flow. Since a Gravitational Water Vortex Power Plant (GWVPP) is an in-stream hydropower technology that can be operated with a low hydraulic head of (0.7-5.0) m and a low flow rate of 0.5 m3/s at least; this study proposed to install an on-grid GWVPP on Zarqa River by one of the manufacturing companies to exploit hydro energy and to serve the local community by providing farmers needs of electricity. The study also determines the appropriate site for establishing the GWVPP by collecting site data in terms of head, flow, and proximity to the grid and roads by Google Earth, site visits, and making site measurements. Then one of the GWVPP manufacturers contacted which is Turbulent Company, and then GWVPP has been designed. Environmental and economic feasibility analyses were performed by using RETScreen Expert software. As a result, the research indicates that installing a GWVPP on the Zarqa River is technically, economically, and ecologically viable.]]>
