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                <text>TELKOMNIKA Telecommunication, Computing, Electronics and Control&#13;
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                <text>Index modulation, MISO-OFDM-SM, OFDM, Spatial modulation (SM)</text>
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                <text>Index modulation is one of the promising techniques for future&#13;
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                <text>DOI: 10.12928/TELKOMNIKA.v18i4.13873</text>
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                <text>Universitas Ahmad Dahlan</text>
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                <text>Sri Wahyuni</text>
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 Enhancement of student performance prediction using modified K-nearest neighbor </text>
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                <text>The traditional K-nearest neighbor (KNN) algorithm uses an exhaustive search for a complete training set to predict a single test sample. This procedure can slow down the system to consume more time for huge datasets. The selection of classes for a new sample depends on a simple majority voting system that does not reflect the various significance of different samples (i.e. ignoring the similarities among samples). It also leads to a misclassification problem due to the occurrence of a double majority class. In reference to the above-mentioned issues, this work adopts a combination of moment descriptor and KNN to optimize the sample selection. This is done based on the fact that classifying the training samples before the searching actually takes place can speed up and improve the predictive performance of the nearest neighbor. The proposed method can be called as fast KNN (FKNN). The experimental results show that the proposed FKNN method decreases original KNN consuming time within a range of (75.4%) to (90.25%), and improve the classification accuracy percentage in the range from (20%) to (36.3%) utilizing three types of student datasets to predict whether the student&#13;
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                <text>Saja Taha Ahmed, Rafah Al-Hamdani, Muayad Sadik Croock</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v18i4.13849</text>
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                <text>ISSN: 1693-6930</text>
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 GWO-based estimation of input-output parameters of thermal power plants</text>
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                <text>The fuel cost curve of thermal generators was very important in the calculation of economic dispatch and optimal power flow. Temperature and aging could make changes to fuel cost curve so curve estimation need to be done periodically. The accuracy of the curve parameters estimation strongly affected the calculation of the dispatch. This paper aims to estimate the fuel cost curve parameters by using the grey wolf optimizer method. The problem of curve parameter estimation was made as an optimization problem. The objective function to be minimized was the total number of absolute error or the difference between the actual value and the estimated value of the fuel cost function. The estimated values of parameter that produce the smallest total absolute error were the values of final solution. The simulation results showed that parameter estimation using gray wolf optimizer method further minimized the value of objective function. By using three models of fuel cost curve and given test data, parameter estimation using grey wolf optimizer method produced the better estimation results than those estimation results obtained using least square error, particle swarm optimization, genetic algorithm , artificial bee colony and cuckoo search methods. </text>
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                <text>Osea Zebua, I Made Ginarsa, I Made Ari Nrartha</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v18i4.12957</text>
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                <text>The breast cancer has affected a wide region of women as a particular case. Therefore, different researchers have focused on the early detection of this disease to overcome it in efficient way. In this paper, an early breast cancer detection system has been proposed based on mammography images. The proposed system adopts deep-learning technique to increase the accuracy of detection. The convolutional neural network (CNN) model is considered for preparing the datasets of training and test. It is important to note that the software engineering process model has been adopted in constructing the proposed algorithm. This is to increase the reliably, flexibility and extendibility of the system. The user interfaces of the system are designed as a website used at country side general purpose (GP) health centers for early detection to the disease under lacking in specialist medical staff. The obtained results show the efficiency of the proposed system in terms of accuracy up to more than 90% and decrease the efforts of medical staff as well as helping the patients. As a conclusion, the proposed system can help patients by early detecting the breast cancer at far places from hospital and referring them to nearest specialist center. </text>
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                <text>Muayad Sadik Croock, Saja Dhyaa Khuder,  Ayad Esho Korial, Sahar Salman Mahmood</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v18i4.14718</text>
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A compact multi-band notched characteristics UWB microstrip patch antenna with a single sheet of graphene </text>
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                <text>A rectangular tuneable ultra-wideband (UWB) microstrip patch (MP) antenna based on a single sheet of graphene (SSG) is designed in this study. The antenna band can be tuned by applying a DC voltage bias perpendicular to the SSG at various values via adjusting the input impedance. The antenna has been analyzed by computer simulation technology (CST) microwave studio (MWS) software using an FR4 substrate of thickness 1.6 mm with a dielectric permittivity εr= 4.4 and loss tangent tan  = 0.02 fed by a 50 Ω microstrip line frequency. The design is compact since the antenna consists mostly of copper and the SSG. Graphene’s low weight, high flexibility, and strength make it more attractive than other semiconductor materials. Then, the study investigates the effects of applying the electrical characteristics of graphene to the antenna’s length, which varies with the ON and OFF states. This UWB MP antenna is also designed with notch characteristics so that it can reject undesired interference signals. Subsequently, this compact UWB MP antenna with tuneable resonance frequency is suitable for most wireless communication applications. The simulation results work in the 3.1 to 10 GHz range, as required for UWB technology. </text>
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                <text>Sri Wahyuni</text>
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                <text>ISSN: 1693-6930</text>
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        <name>Microstrip patch antenna</name>
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                  <text>VOL. 18, NO. 4 2020</text>
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                <text>TELKOMNIKA Telecommunication, Computing, Electronics and Control &#13;
A principal component analysis-based feature dimensionality reduction scheme for content-based image retrieval system </text>
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                <text>Content-based image retrieval system, Feature dimensionality reduction, Low-level visual feature, Principal component analysis</text>
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                <text>In content-based image retrieval (CBIR) system, one approach of image&#13;
representation is to employ combination of low-level visual features cascaded together into a flat vector. While this presents more descriptive information, it however poses serious challenges in terms of high dimensionality and high computational cost of feature extraction algorithms to deployment of CBIR on platforms (devices) with limited computational and storage resources. Hence, in this work a feature dimensionality reduction technique based on principal component analysis (PCA) is implemented. Each image in a database is indexed using 174-dimensional feature vector comprising of 54-dimensional colour moments (CM54), 32-bin HSV-histogram (HIST32), 48-dimensional gabor wavelet (GW48) and 40-dimensional wavelet moments (MW40).&#13;
The PCA scheme was incorporated into a CBIR system that utilized the entire feature vector space. The k-largest eigenvalues that yielded a not more than 5% degradation in mean precision were retained for dimensionality reduction. Three image databases (DB10, DB20 and DB100) were used for testing The result obtained showed that with 80% reduction in feature dimensions, tolerable loss of 3.45, 4.39 and 7.40% in mean precision value were achieved on DB10, DB20 and DB100. </text>
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                <text>Oluwole A. Adegbola, Ismail A. Adeyemo, Folasade A. Semire, Segun I. Popoola, Aderemi A. Atayero</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v18i4.11176</text>
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                <text>Universitas Ahmad Dahlan</text>
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                <text>Sri Wahyuni</text>
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                <text>ISSN: 1693-6930</text>
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                <text>TELKOMNIKA Telecommunication, Computing, Electronics and Control </text>
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        <name>, Feature dimensionality reduction</name>
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        <name>Low-level visual feature</name>
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                  <text>VOL. 18, NO. 4 2020</text>
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A progressive domain expansion method for solving optimal control problem </text>
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                <text>Constraints, Inflow, Optimal control, Operating head, Pontryagain</text>
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                <text>Electricity generation at the hydropower stations in Nigeria has been below the expected value. While the hydro stations have a capacity to generate up to 2,380 MW, the daily average energy generated in 2017 was estimated at around 846 MW. A factor responsible for this is the lack of a proper control system to manage the transfer of resources between the cascaded Kainji-Jebba Hydropower stations operating in tandem. This paper addressed the optimal regulation of the operating head of the Jebba hydropower reservoir in the presence of system constraints, flow requirement and environmental factors that are weather-related. The resulting two-point boundary value problem was solved using the progressive expansion of domain technique as against the shooting or multiple shooting techniques. The results provide the optimal inflow required to keep the operating head of the Jebba reservoir at a nominal level, hence ensuring that the maximum number of turbo-alternator units are operated. </text>
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                <text>Olalekan Ogunbiyi, Oludare Y. Ogundepo, Madugu I. Sani, &#13;
Cornelius Thomas, Benjamin J. Olufeagba</text>
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            <elementTextContainer>
              <elementText elementTextId="42127">
                <text>DOI: 10.12928/TELKOMNIKA.v18i4.15047</text>
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                <text>Universitas Ahmad Dahlan</text>
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                <text>Sri Wahyuni</text>
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                <text>ISSN: 1693-6930</text>
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