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                <text>TELKOMNIKA Telecommunication, , Computing, Electronics and Control &#13;
Planar broadband antenna for 2G/3G systemsComputing, Electronics and Control </text>
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                <text>A planar antenna with broadband gestalt is presented for mobile networks. The structure of the antenna is made up of a folded dipole pair with an L-figure microstrip coupling line. The microstrip coupling along with the dipoles are attached on a similar substrate. The radiation parts are plotted at 1.7 GHz, 2.2 GHz, and 2.7 GHz. A flexible coaxial cable made of perfect electric conductor (PEC) material is attached to the L-figure microstrip whereas the outside conductor made up of RO4350B material is attached to the coplanar strip of line. The gain of the antenna is almost 9 dBi. The benefit of the planar structure is that it offers a simple feeding structure and compact size that is necessary for second generation (2G)/third-generation (3G)/long-term evolution (LTE) systems. Finally, the antenna proposed is designed by using computer simulation technology (CST) microwave studio. </text>
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                <text>DOI: 10.12928/TELKOMNIKA.v20i3.18977</text>
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A hybrid soft bit flipping decoder algorithm for effective signal transmission and reception</text>
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                <text>The Euclidean geometry (EG) based low-density parity check (LDPC) codes are enciphered and deciphered in various modes. These algorithms have the back-and-forth between decoding delay, and power usage, device unpredictability resources, and error rate efficacy are all available with these methods. As a result, the goal of this paper is to develop a comprehensive method to describe both soft and burst error bits for optimal data transfer. As a result, for EG-LDPC codes, a hybrid soft bit flipping (HSBF) decoder is suggested, which decreases decoding complications while improving message data transfer. A simulation model is formed using Xilinx synthesis report to study decoding latency, hardware usage, and power usage. A HSBF decoder is used in this paper, which accepts a 64-bit coding sequence and assigns 64 Adjustable nodes to it. It checks all customizable cluster connections and quantifies adjustable node values and actions. As a consequence of the data collected, our simulation model demonstrates that the HSBF technique outperforms soft bit flipping (SBF) algorithms. As a result, the techniques are ideal for usage in intermediate applications and as well as in cyber security processing technologies, medical applications. </text>
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                <text>Shaik Asif Hussain, Jyothi Chinna Babu, Raza Hasan, Salman Mahmood</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v20i3.23300</text>
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                <text>TELKOMNIKA Telecommunication, Computing, Electronics and Control &#13;
A novel fern-like lines detection using a hybrid of pre-trained convolutional neural network model and Frangi filter </text>
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                <text>Full ferning is the peak of the formation of a salt crystallization line pattern shaped like a fern tree in a woman’s saliva at the time of ovulation. The main problem in this study is how to detect the shape of the salivary ferning line patterns that are transparent, irregular and the surface lighting is uneven. This study aims to detect transparent and irregular lines on the salivary ferning surface using a comparison of 15 pre-trained convolutional neural network models. To detect fern-like lines on transparent and irregular layers, a pre-processing stage using the Frangi filter is required. The pre-trained convolutional neural network model is a promising framework with high precision and accuracy for detecting fern-like lines in salivary ferning. The results of this study using the fixed learning rate model ResNet50 showed the best performance with an error rate of 4.37% and an accuracy of 95.63%. Meanwhile, in implementing the automatic learning rate, ResNet18 achieved the best results with an error rate of 1.99% and an accuracy of 98.01%. The results of visual detection of fern-like lines in salivary ferning using a patch size of 34×34 pixels indicate that the ResNet34 model gave the best appearance. </text>
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                <text>Heri Pratikno, Mohd Zamri Ibrahim,  Jusak</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v20i3.23319</text>
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A novel wideband circularly-polarized microstrip antenna array based on DGS for wireless power transmission </text>
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                <text>The requirement for applications operating at a variety of frequencies in a unified wireless device has greatly enhanced in recent years. For this&#13;
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presents a new design of a wideband circularly-polarized microstrip antenna array with defected ground structure (DGS). A previous design was introduced which cover the C-band at 5.8 GHz and operates in the industrial scientific medical (ISM) band for wireless communication applications. The proposed antenna has excellent performances which include good input impedance matching with a fed of the circular polarization at 5.8 GHz. The proposed design is validated and optimized by adding a new design of defected ground structure. This aperture geometry enables the antenna to operate in a wideband. The obtained results show that the modified antenna has a good performance in terms of return loss, bandwidth, gain and radiation pattern and demonstrate that the proposed antenna offers a good solution for multi-standard wireless communication applications. </text>
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                <text>DOI: 10.12928/TELKOMNIKA.v20i3.21711</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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An open-source active power controller for grid required ancillary services</text>
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                <text>With increasing penetration of renewable energies into modern power&#13;
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support active power control. With this extension, in addition to active&#13;
power control support the resulted mechanical loads on various turbine parts can be evaluated. </text>
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                <text>Nadia Zendehdel, Danyal Bustan</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v20i3.23320</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>VOL. 20, NO. 3 2022</text>
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Attenuated-chattering adaptive second order variable structure controller for mismatched uncertain systems</text>
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                <text>In this paper, an attenuated-chattering adaptive second order variable&#13;
structure controller (ACASOVSC) is proposed for mismatched uncertain&#13;
systems using a Moore-Penrose inverse method. The key achievements of this study include three tasks: 1) influence of the chattering in control input is diminished, 2) finite-time convergence of system states is guaranteed, and 3) external disturbance is generally assumed to be unknown in advance. Firstly, a switching manifold which comprises only output information is defined. Secondly, a reduced-order variable structure estimator (ROVSE) with lower dimension is designed to reduce the computation burden and enhance the robustness. Thirdly, an adaptive approach is used to guess the upper bound of the unknown exogenous disturbance. Next, an ACASOVSC is investigated for attenuating the chattering phenomenon and stabilizing the system. Then, a novel linear matrix inequality (LMI) constraint by the Lyapunov technique is given such that the plant is entirely invariant to matched uncertainties and asymptotically stable. Finally, a mathematical illustration is simulated, which exhibits the usefulness and the feasible&#13;
application of the proposed method. </text>
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                <text>Phan-Thanh Nguyen, Trieu Ton Ngoc, Cong-Trang Nguyen</text>
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              <elementText elementTextId="46184">
                <text>DOI: 10.12928/TELKOMNIKA.v20i3.23317</text>
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                <text>Sri Wahyuni</text>
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                <text>ISSN: 1693-6930</text>
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                  <text>VOL. 20, NO. 3 2022</text>
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Benefits of using TiO2 quantum dots in producing low-cost and high-quality white light-emitting diodes</text>
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                <text>Color uniformity, Luminous flux, Mie-scattering theory, TiO2</text>
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                <text>Quantum dots (QDs) is considered as a potential material for the&#13;
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                <text>DOI: 10.12928/TELKOMNIKA.v20i3.15347</text>
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                <text>Sri Wahyuni</text>
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Comparative study of extraction features and regression algorithms for predicting drought rates</text>
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                <text>Rice is the primary staple food source for Indonesian people, with&#13;
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This research aims to determine the best extraction feature between the&#13;
normalized difference vegetation index (NDVI) and the normalized&#13;
difference water index (NDWI) in describing rice fields’ dryness. Moreover, using the random forest regression algorithm. This research compares NDVI with NDWI using data originating from Sentinel-2A and retrieved via the google earth engine. Regression algorithms are used in research to predict drought in paddy fields. This research shows that NDVI is better than NDWI in predicting drought using random forest regression algorithms and logistic regression algorithms. The random forest regression algorithm based on the results obtained shows that the average root mean square error (RMSE) on NDVI is 0.018, and NDWI is 0.012. Based on the logistic regression algorithm results, it was found that the average value of RMSE on NDVI was 0.346, and NDWI was 0.336. Based on the results of the RMSE, it shows that the forecasting ability of the random forest regression algorithm is better than the logistic regression. </text>
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                <text>Irza Hartiantio Rahmana, Amalia Rizki Febriyani, Indra Ranggadara, Suhendra, Inna Sabily Karima</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v20i3.23156</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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Crime index based on text mining on social media using multi classifier neural-net algorithm</text>
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              <elementText elementTextId="46296">
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                <text>Everyday criminal issues appear on social media, even some crime news is often disturbing to the public but it gives a warning to the public to remain careful and alert to the surrounding environment. However, following large amounts of crime information on social media is not effective, especially for busy people. Therefore, there is a need to efficiently and effectively summarize information in a way that is meaningful and easy to see, attracts people’s attention, and can be used by law enforcement officials. The purpose of this study is to present the index crime based on social media by looking for patterns of crime. This study proposes the projected index crime based on crime trends by using text mining to classify tweet texts and post contents into 10 crime classes. The classification method uses the neural-net multi classifier algorithm which has several classifiers namely logistic regression, naïve bayes, support vector machine (SVM), and decision tree in parallel. In this approach, the classifier that provides the best accuracy will be the winning classifier and will be used in the next learning process. In this experiment, in using the multi classifier neural-net, the logistics regression classifier often provides the best accuracy. </text>
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                <text>Teddy Mantoro, Muhammad Anton Permana, Media Anugerah Ayu</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v20i3.23321</text>
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                <text>ISSN: 1693-6930</text>
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