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Characteristic's analysis of associative switching system&#13;
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                <text>This paper introduced new method and model of telecommunication&#13;
switching system design which can be applied to wavelength-division&#13;
multiplexing (WDM) optical networks, circuit-switching networks or virtual channel/path connections in an asynchronous transfer mode (ATM) networks. Modern data switching systems such as electronic private branch exchange (PBX), routers and switches include switching matrix which are constructed in the form of bipartite graphs. In such systems, the issues of requests’ processing are considered from the queuing theory point of view. Associative switching systems are fundamentally new structures, therefore it is necessary to develop adequate methods for their throughput determination. Article covered matters of throughput determination basics of an associative switching system and the obtained formulas used for state probability calculation of switching modules and system throughput. </text>
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                <text>DOI: 10.12928/TELKOMNIKA.v20i1.17640</text>
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                <text>Universitas Ahmad Dahlan</text>
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                <text>Sri Wahyuni</text>
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                <text>TELKOMNIKA Telecommunication, Computing, Electronics and Control &#13;
Enhancement detection distributed denial of service attacks using hybrid n-gram techniques</text>
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                <text>Distributed denial of service (DDoS) attacks have always been a concern of cyber experts. To detect DDoS attacks, several methods can be used. One of the methods used in this research is the n-gram technique. The n-gram approach analyzes the payload of data packets that enter the network to obtain attack patterns. Data is captured and analyzed, after which it is compared with clean data packets. The chi-square distance value close to 1 indicates that the two packages are very similar so that the data packet is not an attack. A deal less than one means the data packet is categorized as an attack. In this research, the threshold for determining the attack level can be lowered to obtain a very high detection accuracy. As a result, the 2-gram technique has a detection accuracy rate with the lowest false positive value of around 13%, with the highest actual positive ratio reaching 99.98%. </text>
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                <text>Andi Maslan, Kamaruddin Malik Mohamad, Cik Feresa Mohd Foozy</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v20i1.18103</text>
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                <text>Sri Wahyuni</text>
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                <text>TELKOMNIKA Telecommunication, Computing, Electronics and Control &#13;
Design and analysis of single layer quantum dot-cellular automata based 1- bit comparators</text>
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                <text>Quantum dot-cellular automata (QCA) technology has recently emerged as a potential candidate for the design of nanometer-scale computational circuits. In digital logic circuits, the comparator is the basic building block for comparing two binary values. This paper presents and implements two 1-bit QCA-based comparator designs. The proposed QCA implementations are compact, require only a single layer and are less complex compared to recently reported designs. The QCADesigner tool has been used to confirm the functional validity of the proposed QCA structures. The simulation results of the proposed comparators have shown considerable improvements compared to their existing counterparts in terms of the number of QCA cells and occupational area requirements in addition to cost and efficient complexity values. Furthermore, all of the proposed structures are dissipating extremely low energy values. Thus, the proposed QCA-based comparators can be viewed as viable options for low power digital applications. </text>
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                <text>Ziyad A. Altarawneh, Mutaz A.B. Al-Tarawneh</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v20i1.18434</text>
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                <text>TELKOMNIKA Telecommunication, Computing, Electronics and Control &#13;
Natural language processing and machine learning based cyberbullying detection for Bangla and Romanized Bangla texts </text>
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                <text>The popularity of social media has been increasing tremendously in recent times and thus cyberbullying towards people has also increased at an alarming rate. Many cyberbullying texts can be found in the comment sections of many well-known Bangladeshi social media personalities YouTube videos. It has the potential to cause severe emotional and psychological distress. Therefore, texts containing cyberbullying should be detected at the earliest stage and prevented from being displayed. In this study, we use natural language processing (NLP) techniques and various machine learning classifiers and presented model for cyberbullying detection in Bangla and Romanized Bangla texts obtained from YouTube video comments. We developed our own datasets using YouTube application programming interface (API) version 3.0. We collected 5000 Bangla comments, as well as 7000 Romanized Bangla comments from videos of different well-known social media personals. These two datasets, as well as a third dataset of 12000 texts which was the combination of the first two datasets were used to train the classifiers. These datasets were used to train machine learning classifiers after being preprocessed using NLP techniques. With an accuracy score of 76%, support vector machine (SVM) outperformed the other classifiers for the first dataset. The highest accuracy scores for the second and third datasets were 84% and 80%, respectively, which were both achieved by multinomial naive Bayes. </text>
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                <text>Md. Tofael Ahmed, Maqsudur Rahman, Shafayet Nur, Abu Zafor Muhammad Touhidul Islam, Dipankar Das</text>
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              <elementText elementTextId="45027">
                <text>DOI: 10.12928/TELKOMNIKA.v20i1.18630</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. 1 2022</text>
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                <text>TELKOMNIKA Telecommunication, Computing, Electronics and Control &#13;
Improving the usability of faceted exploratory search tools</text>
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                <text>Exploratory search, Faceted energy, Faceted search, Information organization, Information retrieval</text>
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                <text>For some years now, the faceted exploratory search has faced tremendous challenges to devise a simple, instantly understandable, and usable user interface to explore the vast amount of data and information available on the Internet. In our previous research, we have indicated certain burdens with some of the existing approaches. Therefore, in this research, we are trying to uncover the attributes that influence users to use the faceted feature of the exploratory search technique. In this paper, we presented several key elements of existing search engine systems, the best of their major features were explored, and guidelines that will help to improve the usability of faceted exploratory search have been suggested and offers a further understanding of the fundamental characteristics of the faceted search, which shows the motivations to use the search, also presented the main parts of a pluggable search system. </text>
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                <text>Mohammed Najah Mahdi, Abdul Rahim Ahmad, Qais Saif Qassim, Roslan Ismail</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v20i1.18722</text>
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              <elementText elementTextId="45042">
                <text>Universitas Ahmad Dahlan</text>
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              <elementText elementTextId="45044">
                <text>Sri Wahyuni</text>
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              <elementText elementTextId="45045">
                <text>ISSN: 1693-6930</text>
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                <text>http://journal.uad.ac.id/index.php/TELKOMNIKA</text>
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                <text>TELKOMNIKA Telecommunication, Computing, Electronics and Control </text>
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                  <text>VOL. 20, NO. 1 2022</text>
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                <text>TELKOMNIKA Telecommunication, Computing, Electronics and Control &#13;
Comparative analysis of various machine learning algorithms for ransomware detection</text>
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                <text>Computer security, Machine learning, Ransomware detection</text>
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                <text>Recently, the ransomware attack posed a serious threat that targets a wide range of organizations and individuals for financial gain. So, there is a real need to initiate more innovative methods that are capable of proactively detect and prevent this type of attack. Multiple approaches were innovated to detect attacks using different techniques. One of these techniques is machine learning techniques which provide reasonable results, in most attack detection systems. In the current article, different machine learning techniques are tested to analyze its ability in a detection ransomware attack. The top 1000 features extracted from raw byte with the use of gain ratio as a feature selection&#13;
method. Three different classifiers (decision tree (J48), random forest, radial basis function (RBF) network) available in Waikato Environment for Knowledge Analysis (WEKA) based machine learning tool are evaluated to achieve significant detection accuracy of ransomware. The result shows that random forest gave the best detection accuracy almost around 98%. </text>
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                <text>Ban Mohammed Khammas</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v20i1.18812</text>
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              <elementText elementTextId="45056">
                <text>Universitas Ahmad Dahlan</text>
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                <text>Sri Wahyuni</text>
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              <elementText elementTextId="45059">
                <text>ISSN: 1693-6930</text>
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                <text>http://journal.uad.ac.id/index.php/TELKOMNIKA</text>
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                <text>TELKOMNIKA Telecommunication, Computing, Electronics and Control </text>
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                  <text>VOL. 20, NO. 1 2022</text>
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Agriculture data visualization and analysis using data mining techniques: application of unsupervised machine learning </text>
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                <text>Big data, Distplot, Elbow method, Kernel density estimate, K-means, Principal component analysis</text>
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                <text>Unsupervised machine learning is one of the accepted platforms for applying a broad data analytics challenge that involves the way to identify secret trends, unexplained associations, and other significant data from a wide dispersed dataset. The precise yield estimate for the various crops involved in the planning is a critical problem for agricultural planning. To achieve realistic and effective solutions to this problem, data mining techniques are an essential approach. Applying distplot combined with kernel density estimate (KDE) in this paper to visualize the probability density of disseminated datasets of vast crop deals for crop planning. This paper focuses on analyzing and segmenting agricultural data and determining optimal parameters to maximize crop yield using data mining techniques such as K-means clustering and principal component analysis (PCA). </text>
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                <text>Kunal Badapanda, Debani Prasad Mishra, Surender Reddy Salkuti</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v20i1.18938</text>
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              <elementText elementTextId="45070">
                <text>Universitas Ahmad Dahlan</text>
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              <elementText elementTextId="45072">
                <text>Sri Wahyuni</text>
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Exploiting performance gap among two users in reconfigurable intelligent surfaces-aided wireless systems </text>
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                <text>In this work, we study the outage performance of a reconfigurable intelligent surfaces (RIS)-aided wireless systems in the presence of non-orthogonal multiple access (NOMA). In particular, different power factors are allocated to users which belong a dedicated group. We derive exact outage probability of two users in a group. Specifically, it is assumed that the RIS is placed between the source and the users and far user has better performance under assistance of RIS. We also provide comparison analysis to investigate the effect of the main parameters on the outage performance of our proposed system, such as the number of tunable elements of the RIS, power allocation factors, target rates and the average signal-to-noise ratio at the base station. If we set small tunable elements for RIS, we can obtain the best performance. By using Monte-Carlo simulation, we verify our analytical results via simulations. Our main results reported in this paper show the positive effect once we deploy RISs for guaranteeing fairness among NOMA users in wireless systems. </text>
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                <text>Dinh-Thuan Do, Chi-Bao Le</text>
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                <text>Sri Wahyuni</text>
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                <text>ISSN: 1693-6930</text>
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Design of multiple-input and multiple-output antenna for modern wireless applications </text>
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