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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 65 Documents
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Search results for , issue "Vol 18, No 2: April 2020" : 65 Documents clear
Integration of IoT and chatbot for aquaculture with natural language processing M. Udin Harun Al-Rasyid; Sritrusta Sukaridhoto; Muhammad Iskandar Dzulqornain; Ahmad Rifai
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 2: April 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i2.14788

Abstract

The development of internet of things (IoT) technology is very fast lately. One sector that can be implemented by IoT technology is the aquaculture sector. One important factor in the success of aquaculture is a good and controlled water quality condition. But the problem for the traditional aquaculture farmers is to monitor and increase the water quality quickly and efficiently. To resolve the above-mentioned problem, this paper proposes a real-time monitoring system for aquaculture and supported with chatbot assistant to facilitate the user. This system was composed of IoT system, cloud system, and chatbot system. The proposed system consists of 7 main modules: smart sensors, smart aeration system, local network system, cloud computing system, client visualization data, chatbot system, and solar powered system. The smart aeration system consists of NodeMCU, relay, and aerator. The smart sensors consist of several sensors such as dissolved oxygen, pH, temperature, and water level sensor. Natural language processing is implemented to build the chatbot system. By combining text mining processing with naive Bayes algorithm, the result shows the very good performance with high precision and recall for each class to monitor the quality of water in aquaculture sector.
An optimal control for complete synchronization of 4D Rabinovich hyperchaotic systems Shaymaa Y. Al-Hayali; Saad Fawzi Al-Azzawi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 2: April 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i2.14301

Abstract

This paper derives new results for the complete synchronization of 4D identical Rabinovich hyperchaotic systems by using two strategies: active and nonlinear control. Nonlinear control strategy is considered as one of the powerful tool for controlling the dynamical systems. The stabilization results of error dynamics systems are established based on Lyapunov second method. Control is designed via the relevant variables of drive and response systems. In comparison with previous strategies, the current controller (nonlinear control) focuses on convergence speed and the minimum limits of relevant variables. Better performance is to achieve full synchronization by designing the control with fewer terms. The proposed control has certain significance for reducing the time and complexity for strategy implementation.
Artifact elimination in ECG signal using wavelet transform Thanh-Nghia Nguyen; Thanh-Hai Nguyen; Van-Thuyen Ngo
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 2: April 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i2.14403

Abstract

Electrocardiogram signal is the electrical actvity of the heart and doctors can diagnose heart disease based on this electrocardiogram signal. However, the electrocardiogram signals often have noise and artifact components. Therefore, one electrocardiogram signal without the noise and artifact plays an important role in heart disease diagnosis with more accurate results. This paper proposes a wavelet transform with three stages of decomposition, filter, and reconstruction for eliminating the noise and artifact in the electrocardiogram signal. The signal after decomposing produces approximation and detail coefficients, which contains the frequency ranges of the noise and artifact components. Hence, the approximation and detail coefficients with the frequency ranges corresponding to the noise and artifact in the electrocardiogram signal are eliminated by filters before they are reconstructed. For the evaluation of the proposed algorithm, filter evaluation metrics are applied, in which signal-to-noise ratio and mean squared error along with power spectral density are employed. The simulation results show that the proposed wavelet algorithm at level 8 is effective, in which the with the “dmey” wavelet function was selected be the best based power spectrum density.
Combined ILC and PI regulator for wastewater treatment plants Lanh Van Nguyen; Nam Van Bach; Hai Trung Do; Minh Tuan Nguyen
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 2: April 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i2.14895

Abstract

Due to high nonlinearity with features of large time constants, delays, and interaction among variables, control of the wastewater treatment plants (WWTPs) is a very challenging task. Modern control strategies such as model predictive controllers or artificial neural networks can be used to deal with the non-linearity. Another characteristic of this system should be considered is that it works repetitively. Iterative learning control (ILC) is a potential candidate for such a demanding task. This paper proposes a method using ILC for WWTPs to achieve new results. By exploiting data from the previous iterations, the learning control algorithm can improve gradually tracking control performance for the next runs, and hence outperforms conventional control approaches such as feedback controller and model predictive control (MPC). The benchmark simulation model No.1-BSM1 has been used as a standard for performance assessment and evaluation of the control strategy. Control of the dissolved oxygen in the aerated reactors has been performed using the PD-type ILC algorithms. The obtained results show the advantages of ILC over a classical PI control concerning the control quality indexes, IEA and ISE, of the system. Besides, the conventional feedback regulator is designed in a combination with the iterative learning control to deal with uncertainty. Simulation results demonstrate the potential benefits of the proposed method.
MILA: Low-cost BCI framework for acquiring EEG data with IoT Rolly Maulana Awangga; Syafrial Fachri Pane; Dzikri Ahmad Ghifari; Tri Angga Dio Simamora; Mochamad Yusuf Asyhari
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 2: April 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i2.14884

Abstract

The brain is a vital organ in the human body that acts as the center of the human nervous system. Brain-computer interface (BCI) uses electroencephalography (EEG) signals as information on brain activity. Hospitals usually use EEG as a diagnosis of brain disease. Combining EEG as part of IoT (Internet of Things) with high mobility is challenging research. This research tries to make a low-cost BCI framework for motorcycle riders. Analysis of brain activity from EEG data when motorcycle riders turn left or turn right. Therefore, the method of further installation must produce the right features to obtain precise and accurate brainwave characteristics from EEG signals. This research uses the concept of IoT with software engineering to recording human brain waves so that it becomes a practical device for the wearer. The purpose of this study is to create a low-cost BCI framework for obtaining EEG data.
Evaluation of deep neural network architectures in the identification of bone fissures Fredy Martinez; César Hernández; Fernando Martínez
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 2: April 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i2.14754

Abstract

Automated medical image processing, particularly of radiological images, can reduce the number of diagnostic errors, increase patient care and reduce medical costs. This paper seeks to evaluate the performance of three recent convolutional neural networks in the autonomous identification of fissures over two-dimensional radiological images. These architectures have been proposed as deep neural network types specially designed for image classification, which allows their integration with traditional image processing strategies for automatic analysis of medical images. In particular, we use three convolutional networks: ResNet (residual neural network), DenseNet (dense convolutional network), and NASNet (neural architecture search network) to learn information from a set of 200 images labeled half as fissured bones and half as seamless bones. All three networks are trained and adjusted under the same conditions, and their performance was evaluated with the same metrics. The final results consider not only the model's ability to predict the characteristics of an unknown image but also its internal complexity. The three neural models were optimized to reduce classification errors without producing network over-adjustment. In all three cases, generalization of behavior was observed, and the ability of the models to identify the images with fissures, however the expected performance was only achieved with the NASNet model.
Brain computer interface based smart keyboard using neurosky mindwave headset Thair A. Salih; Yasir M. Abdal
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 2: April 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i2.13993

Abstract

In the last decade, numerous researches in the field of ‎electro-encephalo-graphy (EEG) and brain-computer-interface ‎‎(BCI) have been accomplished. BCI has been developed to aid ‎disabled/partially disabled people to efficiently communicate ‎with the community. This paper presents a control tool using ‎the Neurosky Mindwave headset, which detects brainwaves ‎‎(voluntary blinks and attention) to form a brain-computer ‎interface (BCI) by receiving the system signals from the frontal lobe. This paper proposed an alternative computer input device ‎for those disabled people (who are physically challenged) ‎rather than the conventional one. The work suggested to use ‎two virtual keyboard designs. The conducted experiment ‎revealed a significant result in developing user printing skills ‎on PCs. Encouraging results (1.55-1.8 word per minute ‎‎(WPM)) were obtained in this research in comparison to other ‎studies.
Patterns of sidemount four-bay FM antenna system Gerino Mappatao
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 2: April 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i2.14877

Abstract

This paper presents the radiation characteristics of a 4-bay collinear FM antenna system, both in free-space and with the presence of a metallic tower where the bays are mounted, with the use of powerful computers and accurate antenna simulation software. The radiation characteristics of the array are presented and discussed, such as the total gain, polarization components, circularity, beamwidth and minor lobe of the array. This is to determine the conformity of the array performance with existing standards. The possible effects of the metallic tower and the downward radiation from the minor lobe are emphasized. Being aware with these radiation characteristics, broadcast practitioners can optimize the use of this popular array. Results of numerical analyses show that the array is basically a vertically polarized radiator, the beamwidth is quite small which makes it disadvantageous for high-elevated antenna systems, the metallic tower affects the circularity of the azimuth pattern, and the downward radiation from the minor lobes can cause adverse effects. Adjustments on the basic elements and bay placements are recommended.
Glasses for the blind using ping ultrasonic, ATMEGA8535 and ISD25120 Hartono Siswono; Widyastuti Widyastuti
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 2: April 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i2.12419

Abstract

For doing their activities, blind people need tools. The idea for designing this device is for helping the blind person. This device is a glasses specially for blind person which gives information in the form of voices through an earphone if there is an obstacle in the range of 0–58 cm. The device is using PING ultrasonic sensor, ATMEGA8535 microcontroller, and ISD25120 for recording and saving the voices. After designing and making the device, we tested the device to take the data. We use three PING ultrasonic sensors which are put at the sides of the glasses. The device will give eight different kinds of voices through the earphone. The voices depend upon the output of the PING ultrasonic sensors.
Mobile-based monitoring system for an automatic cat feeder using Raspberry Pi Nenny Anggraini; Dzul Fadli Rahman; Luh Kesuma Wardhani; Nashrul Hakiem
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 2: April 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i2.14819

Abstract

In a Saheeh hadith it is explained that the cat is a clean animal that is free from najis, so keeping a cat is not something that is forbidden. One of the things that is important when keeping a cat is feeding. However, keeping a cat at home takes time and effort. In this digital era, the use of technology has penetrated all aspects of life. The objective of this research is to create a monitoring system for an automatic cat feeder using a webcam and a stepper motor that is connected to a Raspberry Pi as the main controller. The webcam can take pictures (photographs or videos) processed with the fswebcam and the avconv functions on the Raspberry Pi. The stepper motor can rotate the feed valve by utilising a General-Purpose Input Output (GPIO) pin and a program which is inserted into the Raspberry Pi. Next, the Raspberry Pi will be connected to the Internet and a server network so that the system control can be done remotely by using a web browser or web view on a mobile. The overall function of the system in the form of feeding the cat either directly or scheduled, as well as monitoring of photographs or videos around the feed. The results of a questionnaire showed that this system has a need value of 87.3% of 79 respondent cat keepers, meaning cat keepers will be greatly helped by the existence of this system.

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