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                  <text>VOL. 20, NO. 5 2022</text>
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                <text>TELKOMNIKA Telecommunication, Computing, Electronics and Control &#13;
Optimization of light source wavelength for ammonia detection in water</text>
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                <text>Ammonia detection, Optical sensor, Plastic optical fiber</text>
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                <text>Optimization of light source wavelength for ammonia detection in surface water is presented in this work. For the ammonia detection, the surface water sample is mixed with sodium chloride and nessler reagent, whereas the sensor head consists of unclad plastic optical fiber. The unclad region has a length of 1 cm and the cladding is removed by immersing it in acetone solution. Experimental results indicate that the output light intensity of the sensor has linear relationship with the ammonia concentration. At the wavelength of 510 nm, the output light increases linearly as the ammonia concentration varies from 0.07 mg/L to 8.97 mg/L. At the same wavelength, the proposed sensor achieves the sensitivity of 0.0139 (mg/L)-1 , accuracy of 99.59% and resolution of 0.72 μg/L. The analysis of light source wavelength reveals that a wavelength range from 450 nm to 580 nm produces the optimized performances. Within this wavelength range, the proposed sensor&#13;
achieves sensitivity of higher than 0.01 (mg/L)-1 , accuracy of higher than 99% and resolution of less than 1 μg/L. </text>
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                <text>Nurfatihah Che Abd Rashid, Noran Azizan Cholan, Kim Gaik Tay, Afiqah Yaacob, Nazrah Ilyana Sulaiman, Khairulanwar Mokhiri, Nor Hafizah Ngajikin</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v20i5.24079</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 &#13;
Model design to develop online web based questionnaire</text>
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                <text>Design, Features, Online, Questionnaire, Web Based</text>
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                <text>This research aims to create a web-based application for sharing questionnaires. The developed features are creating questionnaires, sharing questionnaire in the dashboard, filter the questionnaire as the requested criterias, exchange the rewarded coins for gifts, export questionnaire data to a document, set a limit for the questionnaire for each device. The development will be using data collecting using questionnaire and literature study. Then, software development life cycle (SDLC) waterfall research methodology will be used for the website system development. Result of this research will be a website application that will be used for questionnaire maker so that they can reach the respondent count target, have a suitable respondent (minimize respondent who does not meet the criteria), and also can collect more validated data. </text>
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                <text>Julian Wesley, Fifilia, Cynthia Catrine, Dennis Antony, Ferdian Rizky Estefan</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v20i5.23768</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. 5 2022</text>
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                <text>TELKOMNIKA Telecommunication, Computing, Electronics and Control &#13;
A stochastic algorithm for solving the posterior inference problem in topic models</text>
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                <text>Latent Dirichlet allocation, Posterior inference, Stochastic optimization, Topic models</text>
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                <text>Latent Dirichlet allocation (LDA) is an important probabilistic generative&#13;
model and has usually used in many domains such as text mining, retrieving information, or natural language processing domains. The posterior inference is the important problem in deciding the quality of the LDA model, but it is usually non-deterministic polynomial (NP)-hard and often intractable, especially in the worst case. For individual texts, some proposed methods such as variational Bayesian (VB), collapsed variational Bayesian (CVB), collapsed Gibb’s sampling (CGS), and online maximum a posteriori estimation (OPE) to avoid solving this problem directly, but they usually do not have any guarantee of convergence rate or quality of learned models excepting variants of OPE. Based on OPE and using the Bernoulli distribution combined, we design an algorithm namely general online maximum a posteriori estimation using two stochastic bounds (GOPE2) for solving the posterior inference problem in LDA model. It also is the NP-hard non-convex optimization problem. Via proof of theory and experimental results on the large datasets, we realize that GOPE2 is performed to develop the efficient method for learning topic models from big text collections especially massive/streaming texts, and more efficient than previous methods.</text>
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                <text>Hoang Quang Trung, Xuan Bui</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v20i5.23764</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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                <text>TELKOMNIKA Telecommunication, Computing, Electronics and Control&#13;
Wind turbine doubly-fed induction generator defects diagnosis under voltage dips</text>
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                <text>Diagnosis methods, Discrete wavelet transform, Fast Fourier transform, Lissajous curves, Monitoring, Voltage dips, Wind turbine conversion chain</text>
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                <text>Voltage dips are brief but frequent disturbances that can be defined as the most important problem affecting all electrical grids, it cannot be completely avoided and represent the main priority for the industry. This study remains part of monitoring the quality of electrical energy’s field. Its aim is to apply two approaches signals for improving the failure recognition in wind turbine conversion chain. One is based on the combination of spectral analysis of stator current by fast Fourier transform and Lissajous curves technique of grid currents. The second approach is based on the stator current analysis by discrete wavelet transform which is considered an ideal tool for this purpose due to its time-frequency localization. These defects diagnosis methods have&#13;
shown their efficiency in detection, visualization and analysis of voltage dips in order to develop a control strategy for a wind turbine requiring continuity of its service despite the presence of voltage dips. </text>
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Hybrid features selection method using random forest and meerkat clan algorithm</text>
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                <text>In the majority of gene expression investigations, selecting relevant genes for sample classification is considered a frequent challenge, with researchers attempting to discover the minimum feasible number of genes while yet achieving excellent predictive performance. Various gene selection methods employ univariate (gene-by-gene) gene relevance rankings as well as arbitrary thresholds for selecting the number of genes, are only applicable to 2-class problems and use gene selection ranking criteria unrelated to the algorithm of classification. A modified random forest (MRF) algorithm depending on the meerkat clan algorithm (MCA) is provided in this work. It is one of the swarm intelligence algorithms and one of the most significant machine learning approaches in the decision tree. MCA is used to choose characteristics for the RF algorithm. In information systems, databases, and other applications, feature selection imputation is critical. The proposed algorithm was applied to three different databases, where the experimental results for accuracy and time proved the superiority of the proposed algorithm over the original algorithm. </text>
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                <text>Hayder Adnan Saleh, Rana Amer Sattar, Enas Mohammed Hussein Saeed, Dalael Saad Abdul-Zahra</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v20i5.23515</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. 5 2022</text>
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Bandwidth enhanced deltoid leaf fractal antenna for 5.8 GHz WLAN applications</text>
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                <text>A wideband deltoid leaf fractal antenna is proposed for 5.8 GHz commonly used in industrial scientific and medical (ISM) and wireless local area networks (WLAN) applications. A microstrip patch antennas is designed with leaf shape radiating element. Using a leaf shape, it is possible to increase the perimeter of a design and thus reduce the overall dimensions of the antenna. A circular ring slot is made on the leaf shaped radiator, in a way that a circular disc is loaded at centre. Triangular fractal slots are made inside the circular disc to make it miniaturized. A partial ground is maintained with slot at centre. The antenna is fed by micro-strip feed. The locality and measurements of the fractal slots are varied to make the antenna radiate at 5.8 GHz with wider bandwidth (BW) of (2.26 GHz). The complete size of the antenna is 40 mm3 × 40 mm3 × 1.6 mm3 . The step-by-step implementation of the antenna and the effects of its dimensions are compared and presented using the reflection coefficient curve. The measured reflections coefficient |S11|&lt;-10 dB maintained the operational band from (5.36 GHz − 7.62 GHz), with gain 4.2 dBi. The proposed antenna is planned&#13;
and simulated using high frequency structure simulator (HFSS). The&#13;
simulated and measured comparison showed good agreement, the designed antenna is suitable for 5.8 GHz WLAN applications with wider bandwidth requirements. </text>
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                <text>Rani Rudrama Kodali, Polepalli Siddaiah, Mahendra Nanjappa Giri Prasad</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v20i5.23489</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. 5 2022</text>
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Official logo recognition based on multilayer convolutional neural network model</text>
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                <text>CNN, Deep learning, Features extraction, Learning, Logo recognition</text>
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                <text>Deep learning has gained high popularity in the field of image processing&#13;
and computer vision applications due to its unique feature extraction&#13;
property. For this characteristic, deep learning networks used to solve&#13;
different issues in computer vision applications. In this paper the issue has been raised is classification of logo of formal directors in Iraqi government. The paper proposes a multi-layer convolutional neural network (CNN) to classify and recognize these official logos by train the CNN model on several logos. The experimental show the effectiveness of the proposed method to recognize the logo with high accuracy rate about 99.16%. The proposed multi-layers CNN model proves the effectiveness to classify different logos with various conditions. </text>
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                <text>Zahraa Najm Abdullah, Zinah Abdulridha Abutiheen, Ashwan A. Abdulmunem, Zahraa A. Harjan</text>
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              <elementText elementTextId="47058">
                <text>DOI: 10.12928/TELKOMNIKA.v20i5.23464</text>
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              <elementText elementTextId="47059">
                <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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High-speed multi-channel long-haul coherent optical transmission system</text>
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                <text>In this work, high-speed transmission over the long-haul optical channel&#13;
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                <text>Muthanna Ali Kadhim, Ali Yousif Fattah, Atheer Alaa Sabri</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v20i5.23454</text>
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                <text>Sri Wahyuni</text>
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                <text>ISSN: 1693-6930</text>
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Study the effect of nickel and aluminium doped ZnO photoanode in DSSC</text>
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                <text>Dye sensitized solar cells (DSSC) is one of the promising candidates which are efficient, low-cost, and clean hybrid molecular solar cell devices. Zinc oxide (ZnO) has been widely used as the phoanode in DSSC due to its excellent charge conduction mechanism, yet still suffers from poor cell efficiency. In this study, aluminium doped ZnO (ZnO:Al) and Ni doped ZnO (ZnO:Ni) were studied as photoanode material in DSSC using solar cell capacitance simulator (SCAPS) simulation, and the electrolyte liquid considered a single solid p-type layer as hole transporting materials. Both studied photoanodes have demonstrated better cell performance than pure ZnO photoanode due to the small amount of aluminium (Al) and nikel (Ni) impurities added have enhanced the physiochemical properties of ZnO films. A power conversion efficiency (PCE) of 3.96% was obtained at 3 mol% ZnO:Al photoanode with optimized key parameters. These simulation results proved an opportunity to improve the performance of the DSSCs via doping&#13;
engineering into the ZnO photonaode. </text>
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                <text>Nur Syafiqah Nadiah Mohd Alias, Faiz Arith, Nur Syamimi Noorasid, Hafez Sarkawi, Ahmad Nizamuddin Muhammad Mustafa, Mohd Muzafar Ismail, Mohd Khanapiah Nor</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v20i5.23013</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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                  <text>VOL. 20, NO. 5 2022</text>
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A secure telemedicine electronic platform based on lightweight cryptographic approachcommunication, Computing, Electronics and Control </text>
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                <text>Diffie Hellman encryption, IoT chaotic cryptographic, IoT system, Lightweight crypto, Telemedicine platform</text>
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                <text>Telemedicine platforms have emerged as one of the most harnessed studies in recent years, especially after the spread of pandemics. Due to the epidemic, telemedicine distribution to rural or isolated areas has become an urgent need. However, there are several obstacles to providing remote medical care, the most significant of which is protecting patient data while sustaining the speed of communication between the patient and the medical staff. The significant of this study is to provides a lightweight encryption/decryption technique that uses on the internet of medical things in stance of bio-sensors and bio-actuators. This study is one of the cybersecurity approaches, such type of encryption has little effect on the speed of data transmission. The Diffie Hellman technique is used as a lightweight encryption method because it includes four encryption-keys. The efficiency of the proposed encryption method has been compared with several equivalent methods. According to experimental results, the proposed encryption method represents a lightweight and secure method which can accomplish the level of protection that required to secure medical&#13;
information despite the data’s disarray. </text>
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                <text>Israa Ezzat Salem, Haider Rasheed Abdulshaheed, Hassan Muwafaq Gheni</text>
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              <elementText elementTextId="47016">
                <text>DOI: 10.12928/TELKOMNIKA.v20i5.22662</text>
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                <text>Sri Wahyuni</text>
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                <text>ISSN: 1693-6930</text>
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