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TELKOMNIKA (Telecommunication Computing Electronics and Control)
Published by Universitas Ahmad Dahlan
ISSN : 16936930     EISSN : 23029293     DOI : 10.12928
Core Subject : Science,
Computer Science & IT
Submitted papers are evaluated by anonymous referees by single blind peer review for contribution, originality, relevance, and presentation. The Editor shall inform you of the results of the review as soon as possible, hopefully in 10 weeks. Please notice that because of the great number of submissions that TELKOMNIKA has received during the last few months the duration of the review process can be up to 14 weeks. Communication Engineering, Computer Network and System Engineering, Computer Science and Information System, Machine Learning, AI and Soft Computing, Signal, Image and Video Processing, Electronics Engineering, Electrical Power Engineering, Power Electronics and Drives, Instrumentation and Control Engineering, Internet of Things (IoT)
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 59 Documents
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Search results for , issue "Vol 16, No 3: June 2018" : 59 Documents clear
Algorithm for the Representation of Parameter Values of Electrocardiogram Sabar Setiawidayat; Rudy Joegijantoro
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 3: June 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i3.6934

Abstract

Important parameters that need to be known from the results of cardiac examination using Electrocardiograph is the parameter value of PQRST amplitude peak on each lead. Peak P is associated with Atrium depolarization, QRS waves associated with ventricle depolarization and peak T associated with ventricle repolarization. The PQRST peak values on each lead to date are still manually calculated using small boxes on the ECG paper. Manual calculations lead to less accurate results and calculated waiting times. Less accuracy can lead to misdiagnosis while waiting times can result in increased disease stage. In this article we have been able to represent the values of PQRST amplitude peak and cardiogram in each cycle on each lead of the electrocardiogram. Continuous signal Electrocardiogram (ECG) examination results, in sampling at certain frequencies to obtain discrete data which is the amplitude as a function of integer numbers (N). The maximum amplitude value of each cycle is peak R. The peak time duration R to peak R (dR) is used as the time period of each cycle. A 1.5dR reversal of RN + 1 reverses the starting point of the cycle (sc) while the 0.5dR duration reversal of RN + 1 will be obtained by the end point of the cycle (ec). The maximum and minimum amplitude values between sc and peak R are peak P and peak Q respectively, while the minimum and maximum values between peak R to ec are peak Q and peak T respectively. Discrete data from Physionet MIT-BIH and bmeuwg are used as data to obtain PQRST peak electrocardiogram parameter values in each cycle.
Smart Garage Implementation and Design Using Whatsapp Communication Media Rendy Munadi; Arief Rakhman; Doan Perdana
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 3: June 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i3.8063

Abstract

WhatsApp is a social networking app that serves as a communication medium. According to the Online Audience Measurement Standards named comScore, in 2017, WhatsApp application users in Indonesia amounted to 35.8 million people. As the most popular mobile application with the most users in the country, in this research the authors chose Whatsapp as a communication medium that will be integrated into one application of Internet of Things (IoT), that is Smart Garage. Smart Garage is a combination of information technology and computing technology that is applied to a house by relying on efficiency and device automation. The results of this research shows that it is better to use mobile data networks than using the wireless networks. The maximum delay when using mobile data is 7.5 s and 7.7 s when using wireless networks. The research using WhatsApp application still rare especially in the field of IoT.
Energy Consumption Saving in Embedded Microprocessors Using Hardware Accelerators Gian Carlo Cardarilli; Luca Di Nunzio; Rocco Fazzolari; Marco Re; Francesca Silvestri; Sergio Spanò
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 3: June 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i3.9387

Abstract

This paper deals with the reduction of power consumption in embedded microprocessors. Computing power and energy efficiency are becoming the main challenges for embedded system applications. This is, in particular, the caseof wearable systems. When the power supply is provided by batteries, an important requirement for these systems is the long service life. This work investigates a method for the reduction of microprocessor energy consumption, based on the use of hardware accelerators. Their use allows to reduce the execution time and to decrease the clock frequency, so reducing the power consumption. In order to provide experimental results, authors analyze a case of study in the field of wearable devices for the processing of ECG signals. The experimental results show that the use of hardware accelerator significantly reduces the power consumption.
Weighted Round Robin Load Balancer to Enhance Web Server Cluster in OpenFlow Networks Yuggo Afrianto; Heru Sukoco; Sri Wahjuni
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 3: June 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i3.5601

Abstract

Web server clusters require a reliable network management for increasing the quality of service (QoS). A load balancer system installed in a software-defined network (SDN) is one method that can improve the performance and availability of web server services. SDN is a dynamic and a programmable network management approach, and one protocol that supports it is OpenFlow. This research aims to design and analyse a model of a load balancer on OpenFlow networks, implementing a Weighted Round Robin (WRR) algorithm. The analysis process is conducted by measuring the value of a QoS web server performance parameters, such as response time, throughput, HTTP success, and loss connection. The results showed the WRR algorithm can be implemented for balancing a network system with dynamic resource allocation. The weight workload of each service can be obtained from the needs and existing network resources. The performance of a load balancer on an OpenFlow network is 57% better than in a traditional one for testing of response time conducted in a high connection. However, the throughput and HTTP success connection decreased by 2% and 10%, respectively, while HTTP loss connection increased by 49%.
A Simple Classifier for Detecting Online Child Grooming Conversation Fergyanto E. Gunawan; Livia Ashianti; Nobumasa Sekishita
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 3: June 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i3.6745

Abstract

The massive proliferation of social media has opened possibilities for the perpetrator conducting the crime of online child grooming. Because the pervasiveness of the problem scale, it may only be tamed effectively and efficiently by using an automatic grooming conversation detection system. The current study intends to address the issue by using Support Vector Machine and k-nearest neighbors’ classifiers. Besides, the study also proposes a low-computational cost classification method, which classifies a conversation using the number of the existing grooming conversation characteristics. All proposed methods are evaluated using 150 textual conversations of which 105 are grooming, and 45 are non-grooming. We identify that grooming conversations possess 17 features of grooming characteristics. The results suggest that the SVM and k-NN can identify grooming conversations at 98.6% and 97.8% of the level of accuracy. Meanwhile, the proposed simple method has 96.8% accuracy. The empirical study also suggests that two among the seventeen characteristics are insignificant for the classification.
Lowpass Filter with Hilbert Curve Ring and Sierpinski Carpet DGS Dian Widi Astuti; Intan Wahyuni; Muslim Muslim; Mudrik Alaydrus
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 3: June 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i3.7722

Abstract

Good performance and compact size are the paramaters which are vital when desiging a filter. One of the creteria of good performance is selectivity. This research, conducted by Hilbert Curve Ring and Siepinski Carpet, is used as defected ground structure to overcome filter selectivity. By using three cascadeds Hilbert Curve Ring defected ground structure cells and three steps Sierpinski carpet, a lowpass filter is designed and fabricated. The measurement result for lowpass filterwith Hilbert Curve Ring defected ground structure has sharper selectivity with the cut off frequency at 2.173 GHz and the insertion loss value is 2.135 dB. While the measurement result for three steps Sierpinski carpet has the cut off frequency at 1.728 GHz and the insertion loss value is 0.682 dB.
Application Development Risk Assessment Model Based on Bayesian Network Jaka Sembiring; Johan P. Sipayung; Arry A. Arman
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 3: June 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i3.7288

Abstract

This paper describes a new risk assessment model for application development and its implementation. The model is developed using a Bayesian network and Boehm’s software risk principles. The Bayesian network is created after mapping top twenty risks in software projects with interrelationship digraph of risk area category. The probability of risk on the network is analyzed and validated using both numerical simulation and subjective probability from several experts in the field and a team of application developers. After obtaining the Bayesian network model, risk exposure is calculated using Boehm's risk principles. Finally, the implementation of the proposed model in a government institution is shown as a real case illustration.
Weighted Ensemble Classifier for Plant Leaf Identification R. Putri Ayu Pramesti; Yeni Herdiyeni; Anto Satriyo Nugroho
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 3: June 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i3.7615

Abstract

Plant leaf identification using image can be constructed by ensemble classifier. Ensemble classifier executes classification of various features independently. This experiment utilized texture feature and geometry feature of plant leaf to find out which features are more powerful. Each classifier trained by specific feature produced different accuracy rate. To integrate ensemble classifier the results of the classification were weighted, so as the score obtained from better features contributed greater to the final results. Weighted classification results were combined to get the final result. The proposed method was evaluated using dataset comprises of 156 variety of plants with 4559 images. Weighting and combining classifier used in this study were Weighted Majority Vote (WMV) and Naïve Bayes Combination. Both of those method result showed better accuracy than using single classifier. The average accuracy of single classifier was 61.2% for geometry classifier and 70.3% for texture classifier, while WMV method was 77.8% and Naïve Bayes Combination was 94.6%. The calculation of classifier’s weight by using WMV method produces a weight value of 0.54 for texture feature classifier and 0.46 for geometry feature classifier.
Design of Dual Band Stacked RDRA for 5G Applications A. I. Bugaje; M. H. Jamaluddin; R. Selvaraju; M. N. Hafiz; AdulKadir Bello Shallah
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 3: June 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i3.9037

Abstract

This paper focuses on the investigation and discussion of three different designs of stacked Rectangular Dielectric Resonator Antenna (RDRA) at dual bands of 25 GHz and 32 GHz for 5G applications. First, basic stacked RDRA. Second, basic stacked RDRA with a single notch. Third, basic stacked RDRA with double notches. All the proposed structure consists of two stacked DRA of dielectric permittivity of 10 which mounted on a Duriod dielectric substrate of dielectric permittivity of 2.2 and feed by Microstrip aperture slot feeding technique (MSA) for 50 Ω characteristic impedance. Authentication of all the proposed designs comparison is completed using 3D simulation tool by observing the performance of reflection coefficient, bandwidth, and gain. All the proposed RDRA are demonstrated simulated reflection coefficient lower than 20 dB for both bands and simulated gain more than 6 dBi. Meanwhile, for simulated bandwidth, only the proposed basic stacked RDRA with single and double notches are demonstrated simulated bandwidth more than 1 GHz, which fulfill the requirement for 5G applications.
Improving Sentiment Analysis of Short Informal Indonesian Product Reviews using Synonym Based Feature Expansion M. Ali Fauzi; Ro'i Fahreza Nur Firmansyah; Tri Afirianto
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 3: June 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i3.7751

Abstract

Sentiment analysis in short informal texts like product reviews is more challenging. Short texts are sparse, noisy, and lack of context information. Traditional text classification methods may not be suitable for analyzing sentiment of short texts given all those difficulties. A common approach to overcome these problems is to enrich the original texts with additional semantics to make it appear like a large document of text. Then, traditional classification methods can be applied to it. In this study, we developed an automatic sentiment analysis system of short informal Indonesian texts using Naïve Bayes and Synonym Based Feature Expansion. The system consists of three main stages, preprocessing and normalization, features expansion and classification. After preprocessing and normalization, we utilize Kateglo to find some synonyms of every words in original texts and append them. Finally, the text is classified using Naïve Bayes. The experiment shows that the proposed method can improve the performance of sentiment analysis of short informal Indonesian product reviews. The best sentiment classification performance using proposed feature expansion is obtained by accuracy of 98%.The experiment also show that feature expansion will give higher improvement in small number of training data than in the large number of them.

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