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Contact Name
Nizirwan Anwar
Contact Email
nizirwan.anwar@esaunggul.ac.id
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Journal Mail Official
telkomnika@ee.uad.ac.id
Editorial Address
Ahmad Yani st. (Southern Ring Road), Tamanan, Banguntapan, Bantul, Yogyakarta 55191, Indonesia
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INDONESIA
TELKOMNIKA (Telecommunication Computing Electronics and Control)
ISSN : 16936930     EISSN : 23029293     DOI : 10.12928
Core Subject : Science,
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)
Articles 55 Documents
Search results for , issue "Vol 15, No 4: December 2017" : 55 Documents clear
The Use of Polymer Based Gas Sensor for Detecting Formalin in Food Using Artificial Neural Network Budi Gunawan; Arief Sudarmaji
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 4: December 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i4.6164

Abstract

The usage of formalin as preservative substance in food is dangerous and make much threat to public society. Yet, it is difficult to identify the presence of formalin in food sensory. It commonly requires laboratory-based testing to detect the formalin. This work describes a detector system of formalin presence in food which employs a series of polymer-based gas sensor and uses a neural network detection method. The sensors are the polymer-carbon composite which made of the polymer mixed with active carbon. There are four types of polymer used, i.e. Polyethylene Glycol (PEG) 6000, PEG200, PEG20M, and PEG1450. The polymer-carbon composite provided a unique characteristic when it is exposed to vapor of food with or without formalin. The resistance of each polymer is different for each detected vapor. The combination of those sensors gives a pattern of voltage output on the sensors when they are exposed certain gas so that every gas has its unique output pattern. The method of detection uses an algorithm of back-propagation of the neural network. That voltage pattern of sensors serves as input to an artificial intelligence program. The result shows that the system has the accuracy of 75% in detecting formalin in food.
Shunt Active Power Filter based on P-Q Theory with Multilevel Inverters for Harmonic Current Compensation Suhendar Suhendar; Teguh Firmansyah; Alief Maulana; Zuldiag Zuldiag; Vektor Dewanto
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 4: December 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i4.6363

Abstract

A shunt active power filter based on P-Q theory combined with high pass filters (HPFs) for harmonic-current compensation was proposed in this paper. A dual level H-bridge inverter (DLHI) and clamp diode multilevel inverter (CDMI) as inverters was used. The proposed active power filter was applied to 3-phase power system with 220V voltage and 50Hz frequency. the simulation model was constructed by using Simulink MATLAB. The results show that the proposed active power filter with CDMI produces lower total harmonic distortion (THD) than the active power filters with DLHI. Additionally, the proposed shunt active power filter has lower THD compared with other types of active power filters.
An Image Enhancement Approach to Achieve High Speed Using Adaptive Modified Bilateral Filter for Satellite Images Using FPGA Sendamarai Panchacharam; Giriprasad M.N
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 4: December 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i4.3457

Abstract

For real time application scenarios of image processing, satellite imaginary has grown more interest by researches due to the informative nature of image. Satellite images are captured using high quality cameras. These images are captured from space using on-board cameras. Wrong ISO setting, camera vibrations or wrong sensory setting causes noise. The degraded image can cause less efficient results during visual perception which is a challenging issue for researchers. Another reason is that noise corrupts the image during acquisition, transmission, interference or dust particles on the scanner screen of image from satellite to the earth stations. If quality degraded images are used for further processing then it may result in wrong information extraction. In order to cater this issue, image filtering or denoising approach is required. Since remote sensing images are captured from space using on-board camera which requires high speed operating device which can provide better reconstruction quality by utilizing lesser power consumption. Recently various approaches have been proposed for image filtering. Key challenges with these approaches are reconstruction quality, operating speed, image quality by preserving information at edges on image. Proposed approach is named as modified bilateral filter. In this approach bilateral filter and kernel schemes are combined. In order to overcome the drawbacks, modified bilateral filtering by using FPGA to perform the parallelism process for denoising is implemented.
Selective Green Device Discovery for Device-to-Device Communication Bhaskara Narottama; Arfianto Fahmi; Rina Pudji Astuti; Desti Madya Saputri; Nur Andini; Hurianti Vidyaningtyas; Patricius Evander Christy; Obed Rhesa Ludwiniananda; Furry Rachmawati
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 4: December 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i4.6686

Abstract

The D2D communication is expected to improve devices’ energy-efficiency, which has become a major requirement of the future wireless network. Before the D2D communication can be performed, the device discovery between devices must be done. The previous works usually only assumed one mode of device discovery, i.e. either use network-assisted (with network supervision) or independent (without network supervision) device. Therefore, we propose a selective device discovery for device-to-device (D2D) communication that can utilize both device discovery modes and maintain devices’ energy-efficiency. Different from previous works, our proposed method selects the best device discovery mode to get the best energy-efficiency. Moreover, to further improve the energy-efficiency, our proposed method also deployed in D2D cluster with multiple cluster heads. The proposed method selects the most suitable mode using thresholds (cluster energy consumption and new device acceptance) and cluster energy expectation. Our experiment result indicates that the proposed method provides lowest energy consumption per new accepted device while compared with schemes with full network-assisted and independent device discovery in low numbers of new device arrival (for the number of new devices arrival = 1 ~ 3).
Compact Dual-band Parallel Coupled T-shaped SIR Filter for WLAN Applications Emad S. Ahmaed
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 4: December 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i4.5584

Abstract

In this article, a new compact dual-band bandpass filter was introduced. The filter utilized two operating bands centered at 2.45 GHz and 5 GHz widely used for wireless local area network applications. The filter consists of T-shaped sections of step impedance resonator. The structure is an even symmetrical around electrical or magnetic wall, so the operation mechanism of the filter can be analyzed by an even- and odd-mode transmission line theory. The resonator structure is parallel coupled to a pair of 50 Ω input/output ports. Proper feeding and coupling structures can realize at least two transmission zeros around each of the operating band. To enhance the spurs rejection in the out of the band response of the filter, additive transmission zero at 10 GHz was created by adding stub of quarter guided wavelength at a selected distant from the output port edge. The filter is designed and optimized using the full wave Electromagnetic simulator. The center frequency of the designed bands can be easily refined by the filter dimensions. The overall dimension of the filter is (where  is the guided wavelength at the frequency of 2.45 GHz) corresponding to 14.3 mm x 22 mm.
IMC Based Fractional Order Controller for Three Interacting Tank Process Abdul Wahid Nasir; Idamakanti Kasireddy; Arun Kumar Singh
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 4: December 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i4.5784

Abstract

In model based control, performance of the controlled plant considerably depends on the accuracy of real plant being modelled. In present work, an attempt has been made to design Internal Model Control (IMC), for three interacting tank process for liquid level control. To avoid complexities in controller design, the third order three interacting tank process is modelled to First Order Plus Dead Time (FOPDT) model. Exploiting the admirable features of Fractional Calculus, the higher order model is also modelled to Fractional Order First Order Plus Dead Time (FO-FOPDT) model, which further reduces the modelling error. Moving to control section, different IMC schemes have been proposed, where the fractional order filter is introduced along with the conventional integer order filter. Various simulations have been performed to show the greatness of Fractional order modelled system & fractional order filters over conventional integer order modelled system & integer order filters respectively. Both for parameters estimation of reduced order model and filter tuning, Genetic Algorithm (GA) is being applied.  
Hierarchy Process Mining from Multi-Source Logs Riyanarto Sarno; Yutika Amelia Effendi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 4: December 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i4.6326

Abstract

Nowadays, large-scale business processes is growing rapidly; in this regards process mining is required to discover and enhance business processes in different departments of an organization. A process mining algorithm can generally discover the process model of an organization without considering the detailed process models of the departments, and the relationship among departments. The exchange of messages among departments can produce asynchronous activities among department process models. The event logs from departments can be considered as multi-source logs, which cause difficulties in mining the process model. Discovering process models from multi-source logs is still in the state of the art, therefore this paper proposes a hierarchy high-to-low process mining approach to discover the process model from a complex multi-source and heterogeneous event logs collected from distributed departments. The proposed method involves three steps; i.e. firstly a high level process model is developed; secondly a separate low level process model is discovered from multi-source logs; finally the Petri net refinement operation is used to integrate the discovered process models. The refinement operation replaced the abctract transitions of a high level process model with the corresponding low level process models. Multi-source event logs from several departments of a yarn manufacturing were used in the computational study, and the results showed that the proposed method combined with the modified time-based heuristics miner could discover a correct parallel process business model containing XOR, AND, and OR relations.
Vision Based Human Decoy System for Spot Cooling Tan Chun Hou; Wan Nurshazwani Wan Zakaria; Tai Sue Jing; Razali Tomari; Tee Kian Sek; Anis Azwani Muhd Suberi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 4: December 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i4.7229

Abstract

This project aims to reduce the energy consumption of air conditioner usage while maintaining occupant comfort. Cooling down the unoccupied space can be considered as waste of energy. Therefore, a human decoy system is proposed to track any human in the detection area. Image contains depth data in each pixel which can be used to detect the presence of target subject as well as their position. The acquired position data is processed by using MATLAB and subsequently is transmitted to Arduino Mega using serial communication to control stepper motors. The experimental results show that the air conditioner airflow is successfully can be directed to the target human subject with average response of 0.860 seconds per movement within detection area.
Computer Aided Diagnosis using Margin and Posterior Acoustic Featuresfor Breast Ultrasound Images Hanung Adi Nugroho; Yuli Triyani; Made Rahmawaty; Igi Ardiyanto
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 4: December 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i4.5021

Abstract

Breast cancer is the most commonly diagnosed cancer among females worldwide. Computer aided diagnosis (CAD) was developed to assist radiologists in detecting and evaluating nodules so it can improve diagnostic accuracy, avoid unnecessary biopsies, reduce anxiety and control costs. This research proposes a method of CAD for breast ultrasound images based on margin and posterior acoustic features. It consists of preprocessing, segmentation using active contour without edge (ACWE) and morphological, feature extraction and classification. Texture and geometry analysis was used to determine the characteristics of the posterior acoustic and margin nodules. Support vector machines (SVM) provided better performance than multilayer perceptron (MLP). The performance of proposed method achieved the accuracy of 91.35%, sensitivity of 92.00%, specificity of 89.66%, PPV of 95.83%, NPV of 81.26% and Kappa of 0.7915. These results indicate that the developed CAD has potential to be implemented for diagnosis of breast cancer using ultrasound images.
Sentiment Mining of Community Development Program Evaluation Based on Social Media Siti Yuliyanti; Taufik Djatna; Heru Sukoco
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 4: December 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i4.4633

Abstract

It is crucial to support community-oriented services for youth awareness in the social media with knowledge extraction, which would be useful for both government agencies and community group of interest for program evaluation. This work provided to formulate effective evaluation on community development program and addressing them to a correct action. By using classification based SVM, evaluation of the achievement level conducted in both quantitative and qualitative analysis, particularly to conclude which activities has high success rate. By using social media based activities, this study searched the sentiment analysis from every activities comments based on their tweet. First, we kicked off preprocessing stage, reducing feature space by using principle of component analysis and estimate parameters for classification purposes. Second, we modeled activity classification by using support vector machine. At last, set term score by calculating term frequency, which combined with term sentiment scores based on lexicon.The result shows that models provided sentiment summarization that point out the success level of positive sentiment.

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