1 10 35 https://repository.horizon.ac.id/files/original/003b3e58f4a86a2a0b1cad785d5a206e.pdf 59e98abbe77b27a4392cd4f5f417384c Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 19, NO. 5 2021 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource TELKOMNIKA Telecommunication, Computing, Electronics and Control A maximum entropy classification scheme for phishing detection using parsimonious features Subject The topic of the resource Classification Parsimonous features Phishing Social engineering Description An account of the resource Over the years, electronic mail (e-mail) has been the target of several malicious attacks. Phishing is one of the most recognizable forms of manipulation aimed at e-mail users and usually, employs social engineering to trick innocent users into supplying sensitive information into an imposter website. Attacks from phishing emails can result in the exposure of confidential information, financial loss, data misuse, and others. This paper presents the implementation of a maximum entropy (ME) classification method for an efficient approach to the identification of phishing emails. Our result showed that maximum entropy with parsimonious feature space gives a better classification precision than both the Naïve Bayes and support vector machine (SVM). Creator An entity primarily responsible for making the resource Emmanuel O. Asani, Adebayo Omotosho, Paul A. Danquah, Joyce A. Ayoola, Peace O. Ayegba, Olumide B. Longe Source A related resource from which the described resource is derived http://journal.uad.ac.id/index.php/TELKOMNIKA Date A point or period of time associated with an event in the lifecycle of the resource Jul 13, 2021 Contributor An entity responsible for making contributions to the resource peri irawan Format The file format, physical medium, or dimensions of the resource pdf Language A language of the resource english Type The nature or genre of the resource text classification Jurnal Nasional Informatika Parsimonous features Phishing Social engineering https://repository.horizon.ac.id/files/original/e6346481e9372289a1c60a30d4edea1c.pdf e4a1383163c78eb21a7e725ab80f130f Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 19, NO. 5 2021 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource TELKOMNIKA Telecommunication, Computing, Electronics and Control A novel design of circularly polarized pentagonal planar antenna for ISM band applications Subject The topic of the resource Circular polarization Defected ground structure ISM band Micro-strip antenna Pentagonal shape Wireless power transmission Description An account of the resource This paper presents a new circular polarized micro-strip antenna with a pentagonal shape radiator. The proposed antenna is designed to operate in the industrial scientific medical (ISM) band at the frequency of 2.45GHz for Wireless applications. The antenna consists of a radiating pentagon patch with appropriate dimensions on the upper side of a dielectric substrate and a defective ground structure (DGS) on the other side. The pentagon patch is fed through a 50Ω microstrip line. The structure is implemented on an FR-4 substrate with a relative permittivity of 4.4, loss tangent equal to 0.025 and thickness 1.58 mm. The antenna is designed and simulated by using advanced design system (ADS) electromagnetic solver and the achieved results are validated by using another electromagnetic solver. The simulation results indicate that the designed circularly polarized (CP) pentagonal microstrip patch antenna gives good results in terms of the reflection coefficient, voltage standing wave ratio (VSWR) and, axial ratio of 1.025 at 2.45 GHz. Creator An entity primarily responsible for making the resource F. Ouberri, A. Tajmouati , J. Zbitou, I. Zahraoui, M. Latrach Source A related resource from which the described resource is derived http://journal.uad.ac.id/index.php/TELKOMNIKA Date A point or period of time associated with an event in the lifecycle of the resource Jul 25, 2021 Contributor An entity responsible for making contributions to the resource peri irawan Format The file format, physical medium, or dimensions of the resource pdf Language A language of the resource english Type The nature or genre of the resource text Circular polarization Defected ground structure ISM band Jurnal Nasional Informatika Micro-strip antenna Pentagonal shape Wireless power transmission https://repository.horizon.ac.id/files/original/119b182582ea899b7c9e276a6cd2f028.pdf 7e95916f0c376306518ee8194c902eb0 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 19, NO. 5 2021 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource TELKOMNIKA Telecommunication, Computing, Electronics and Control Analysis of FAM in satisfaction of inpatient services Subject The topic of the resource DSS FAM Patient satisfaction Description An account of the resource Patients are the main object who must get the best service at a hospital, because the quality of hospital services determines the recovery of a patient and the quality of the hospital. The quality of hospital services has two components, namely the fulfillment of predetermined quality standards and the fulfillment of patient satisfaction. Hospitals must provide services that focus on patient satisfaction. Improving the quality of health services can be started by evaluating each element that plays a role in shaping patient satisfaction. The application of evaluation measures to patient care in each hospital is needed as an increase in the quality of service to patients. The analysis of the fuzzy associate memory method has the closeness of human reasoning to get solutions to various problems so that they are easy to apply and understand. Utilization of decision support system (DSS) analysis with fuzzy associate memory method can be used as an evaluation of the perception of each consumer complaint to measure the level of patient satisfaction. Creator An entity primarily responsible for making the resource Muhammad Sabir Ramadhan, Nizwardi Jalinus, Refdinal, Marsono, Yohanni Syahra, Asyahri Hadi Nasyuha, Buyung Solihin Hasugian, Erika Fahmi Ginting, Masyuni Hutasuhut Source A related resource from which the described resource is derived http://journal.uad.ac.id/index.php/TELKOMNIKA Date A point or period of time associated with an event in the lifecycle of the resource Jun 28, 2021 Contributor An entity responsible for making contributions to the resource peri irawan Format The file format, physical medium, or dimensions of the resource pdf Language A language of the resource english Type The nature or genre of the resource text DSS FAM Jurnal Nasional Informatika Patient satisfaction https://repository.horizon.ac.id/files/original/2d48f26f6796eb736e5a69d1f5114fe8.pdf 3454275d68bda3d1918f6a37ae7f5057 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 19, NO. 5 2021 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource TELKOMNIKA Telecommunication, Computing, Electronics and Control Analysis of frequent itemset generation based on trie data structure in Apriori algorithm Subject The topic of the resource Apriori Hash-node calculation Level pruning Multi-thread Triedata structure Description An account of the resource Apriori is one technique of data mining association rules that aims to extract correlations between sets of items in the transaction database. The main problem with the Apriori algorithm is the process of scanning databases repeatedly to generate itemset candidates. This research examines the combination of pruning by using the trieapproach and multi-thread implementation in three algorithms to obtain frequent itemset. Trie is a data structure in the form of an ordered tree to store a set of strings where every node in the tree contains the same prefix. The use of a full combination trie (different from frequent pattern (FP) tree using links) allows the implementation of arrays and the hash calculation to achieve the addressing of itemset combination. In this research, the measure to get the address is called Hash-node calculation used to update support value. For these three alternatives, run time processing is analyzed based on the number of itemset combinations and transaction data at a certain minimum support value. The experimental results show that an algorithm thatexploits resource capabilities by applying multi-threadperforms almost seven times betterthanan algorithm implemented in single-thread in calculating hash-node. The fastest run time of the multi-thread approach is 43 minutes with 150-itemset combinations on 100,000 transaction data. Creator An entity primarily responsible for making the resource Ade Hodijah, Urip Teguh Setijohatmo Source A related resource from which the described resource is derived http://journal.uad.ac.id/index.php/TELKOMNIKA Date A point or period of time associated with an event in the lifecycle of the resource Apr 22, 2021 Contributor An entity responsible for making contributions to the resource peri irawan Format The file format, physical medium, or dimensions of the resource pdf Language A language of the resource english Type The nature or genre of the resource text Apriori Hash-node calculation Jurnal Nasional Informatika Level pruning Multi-thread Triedata structure https://repository.horizon.ac.id/files/original/630915bb9de81ee212981ab5835bc141.pdf dd344e0035dca77c0523b42fb8d9551f Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 19, NO. 5 2021 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource TELKOMNIKA Telecommunication, Computing, Electronics and Control Analysis of the reliability of the components of a multiservice communication network based on the theory of fuzzy sets Subject The topic of the resource Fuzzy logic toolbox Fuzzy set theory mathematical apparatus FuzzyTECH MATLAB environment Multiservice communication network Description An account of the resource The article presents the results of modeling the solution to the problem of determining the reliability of the components of a multiservice communication network (MCN) based on the theory of fuzzy sets. The main characteristics of the equipment that affect the reliability parameters of the MCN are given. To solve the problem of determining the reliability of MCN components based on the theory of fuzzy sets, a multiservice network is presented in the form of a hierarchical diagram, which shows the main components of each network level. A multiservice network is presented as a parameter of the U function. The reliable state of the MCN depends on the state of the equipment at the corresponding levels. The results of modeling the solution to the problem of determining the reliability of MCN components based on the theory of fuzzy sets are presented using the mathematical apparatus of the theory of fuzzy sets and fuzzy logic in MATLAB fuzzy logic toolbox, fuzzyTECH. Creator An entity primarily responsible for making the resource Alevtina Aleksandrovna Muradova, Aybek Fayzullaevich Khaytbaev Source A related resource from which the described resource is derived http://journal.uad.ac.id/index.php/TELKOMNIKA Date A point or period of time associated with an event in the lifecycle of the resource Apr 22, 2021 Contributor An entity responsible for making contributions to the resource peri irawan Format The file format, physical medium, or dimensions of the resource pdf Language A language of the resource english Type The nature or genre of the resource text Fuzzy logic toolbox Fuzzy set theory mathematical apparatus FuzzyTECH Jurnal Nasional Informatika MATLAB environment Multiservice communication network https://repository.horizon.ac.id/files/original/0c888b274c3501a42e1043c4758a6acb.pdf a6d3913459f3a0192abc42af9f91254c Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 19, NO. 5 2021 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource TELKOMNIKA Telecommunication, Computing, Electronics and Control Cervical cancer classification using convolutional neural network-support vector machine Subject The topic of the resource Cervical cancer Classification Convolutional neural network Machine learning Support vector machine Description An account of the resource Cervical cancer is the second most common cancer in women worldwide, and occurs when there are presences of abnormal cells in the cervix, which continue to grow uncontrollably. In the early stages, cervical cancer indications are not perceptible; however, it is easily detected with different forms of machine learning methods, such as the convolutional neural network (CNN). This is a popular method with a wide range of applications and known for its high accuracy value. Moreover, there is a support vector machine (SVM) with several kernel functions that is commonly used in the classification of diseases, and also known for its high accuracy value. Therefore, the combination of CNN–SVM with several linear kernels functions as classifier for the categorization of cervical cancer. Creator An entity primarily responsible for making the resource Jane Eva Aurelia, Zuherman Rustam, Ilsya Wirasati Source A related resource from which the described resource is derived http://journal.uad.ac.id/index.php/TELKOMNIKA Date A point or period of time associated with an event in the lifecycle of the resource Aug 1, 2021 Contributor An entity responsible for making contributions to the resource peri irawan Format The file format, physical medium, or dimensions of the resource pdf Language A language of the resource english Type The nature or genre of the resource text cervical cancer classification Convolutional neural network Jurnal Nasional Informatika machine learning Support Vector Machine https://repository.horizon.ac.id/files/original/84377e202cc4976a2abef6290c698b13.pdf 949afd1faab473c5ec2baf3a9232eaa2 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 19, NO. 5 2021 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource TELKOMNIKA Telecommunication, Computing, Electronics and Control Classification of EEG signals for facial expression and motor execution with deep learning Subject The topic of the resource BCI Deep learning EEG Nueral network PCA Description An account of the resource Recently, algorithms of machine learning are widely used with the field of electroencephalography (EEG) brain-computer interfaces (BCI). The preprocessing stage for the EEG signals is performed by applying the principle component analysis (PCA) algorithm to extract the important features and reducing the data redundancy. A model for classifying EEG, time series, signals for facial expression and some motor execution processes had been designed. A neural network of three hidden layers with deep learning classifier had been used in this work. Data of four different subjects were collected by using a 14 channels Emotiv EPOC+ device. EEG dataset samples including ten action classes for the facial expression and some motor execution movements are recorded. A classification results with accuracy range (91.25-95.75%) for the collected samples were obtained with respect to: number of samples for each class, total number of EEG dataset samples and type of activation function within the hidden and the output layer neurons. A time series EEG signal was taken as signal values not as image or histogram, analysed and classified with deep learning to obtain the satisfied results of accuracy. Creator An entity primarily responsible for making the resource Areej Hameed Al-Anbary, Salih Al-Qaraawi Source A related resource from which the described resource is derived http://journal.uad.ac.id/index.php/TELKOMNIKA Date A point or period of time associated with an event in the lifecycle of the resource Jun 28, 2021 Contributor An entity responsible for making contributions to the resource peri irawan Format The file format, physical medium, or dimensions of the resource pdf Language A language of the resource english Type The nature or genre of the resource text BCI deep learning EEG Jurnal Nasional Informatika Nueral network PCA https://repository.horizon.ac.id/files/original/7c1feb62139b0b5f83ee2ff307b743a4.pdf ae0046880707277f52e8f0d09b688712 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 19, NO. 5 2021 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource TELKOMNIKA Telecommunication, Computing, Electronics and Control Classification of heart disease based on PCG signal using CNN Subject The topic of the resource Continuous wavelet transform Convolutional neural network Heart disease Phonocardiogram Description An account of the resource Cardiovascular disease is the leading cause of death in the world, so early detection of heart conditions is very important. Detection related to cardiovascular disease can be conducted through the detection of heart signals interference, one of which is called phonocardiography. This study aims to classify heart disease based on phonocardiogram (PCG) signals using the convolutional neural networks (CNN). The study was initiated with signal preprocessing by cutting and normalizing the signal, followed by a continuous wavelet transformation process using a mother wavelet analytic morlet. The decomposition results are visualized using a scalogram, then the results are used as CNN input. In this study, the PCG signals used were classified into normal, angina pectoris (AP), congestive heart failure (CHF), and hypertensive heart disease (HHD). The total data used, classified into 80 training data and 20 testing data. The obtained model shows the level of accuracy, sensitivity, and diagnostic specificity of 100%, 100%, and 100% for training data, respectively, while the prediction results for testing data indicate the level of accuracy, sensitivity, and specificity of 85%, 80%, and 100%, respectively. This result proved to be better than the mother wavelet or other classifier methods, then the model was deployed into the graphical user interface (GUI). Creator An entity primarily responsible for making the resource Aditya Wisnugraha Sugiyarto, Agus Maman Abadi, Sumarna Source A related resource from which the described resource is derived http://journal.uad.ac.id/index.php/TELKOMNIKA Date A point or period of time associated with an event in the lifecycle of the resource Jul 28, 2021 Contributor An entity responsible for making contributions to the resource peri irawan Format The file format, physical medium, or dimensions of the resource pdf Language A language of the resource english Type The nature or genre of the resource text Continuous wavelet transform Convolutional neural network Heart disease Jurnal Nasional Informatika Phonocardiogram https://repository.horizon.ac.id/files/original/d26f7a72a75ea87cf4e9726ad9839bb1.pdf 81fab5e3647456142394a4eb838adaa6 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 19, NO. 5 2021 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource TELKOMNIKA Telecommunication, Computing, Electronics and Control Classification of water stress in cultured Sunagoke moss using deep learning Subject The topic of the resource Convolutional neural network Cultured Sunagoke moss Machine vision Non-destructive sensing Water stress Description An account of the resource Water stress greatly determines plant yield as it affects plant metabolism, photosynthesis rate, chlorophyll content index, number of leaves, physiological, biochemical compound, and vegetative growth. The research aimed to detect and classify water stress of cultured Sunagoke moss into several categories i.e. dry, semi-dry, wet, and soak by using a low-cost commercial visible light camera combined with a deep learning model. Cultured Sunagoke moss is a commercial product which has the potential use as rooftop-greening and wall-greening material. This research compared the performance of four convolutional neural network models, such as SqueezeNet, GoogLeNet, ResNet50, and AlexNet. The best convolutional neural network model according to the training and validation result was ResNet50 with RMSProp optimizer, 30 epoch, and 128 mini-batch size; this also gained an accuracy rate at 87.50%. However, the best result of the convolutional neural network model on data testing using confusion matrices on different data sample was ResNet50 with Adam optimizer, 30 epoch, 128 mini-batch size, and average testing accuracy of 94.15%. It can be concluded that based on the overall results, convolutional neural network model seems promising as a smart irrigation system that real-time, non-destructive, rapid, and precise method when controlling water stress of plants. Creator An entity primarily responsible for making the resource Yusuf Hendrawan, Retno Damayanti, Dimas Firmanda Al Riza, Mochamad Bagus Hermanto Source A related resource from which the described resource is derived http://journal.uad.ac.id/index.php/TELKOMNIKA Date A point or period of time associated with an event in the lifecycle of the resource Aug 3, 2021 Contributor An entity responsible for making contributions to the resource peri irawan Format The file format, physical medium, or dimensions of the resource pdf Language A language of the resource english Type The nature or genre of the resource text Convolutional neural network Cultured Sunagoke moss Jurnal Nasional Informatika Machine vision Non-destructive sensing Water stress https://repository.horizon.ac.id/files/original/8d27e4af90e49c26b8c30a2190845ab9.pdf 97ff83efc6a109013ac286c214364dbf Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 19, NO. 5 2021 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource TELKOMNIKA Telecommunication, Computing, Electronics and Control Comparative and analysis of evaluation of several direction of arrival estimation methods Subject The topic of the resource ESPRIT Intelligent arrays Multi-users MUSIC Signal process Description An account of the resource Modern-day, global, and clever array systems have several distinguished approaches with regard to a wireless device. In this paper, a comparative analysis has been carried out amongst nine direction of arrival (DOA) algorithms: Capon, multiple signal classification (MUSIC), Bartlett, Pisarenko, linear prediction, maximum entropies, and min-norm, root- MUSIC, and estimation of signal parameters via rotational invariance technique (ESPRIT). in this paper reduces the number of antennas and snaps necessary to observe six target swithout interference for several DOA estimation methods. After comparing and analyzing all the algorithms, it has been shown that the music algorithm is the best algorithm that reduces interference and detects the desired sources. MATLAB R2019b was used in the simulation process. Creator An entity primarily responsible for making the resource Aya Ahkam Kamil, Marwa M. Ismail, Bashar S. Bashar Source A related resource from which the described resource is derived http://journal.uad.ac.id/index.php/TELKOMNIKA Date A point or period of time associated with an event in the lifecycle of the resource Aug 2, 2021 Contributor An entity responsible for making contributions to the resource peri irawan Format The file format, physical medium, or dimensions of the resource pdf Language A language of the resource english Type The nature or genre of the resource text ESPRIT Intelligent arrays Jurnal Nasional Informatika Multi-users Music Signal process