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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 67 Documents
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Search results for , issue "Vol 18, No 4: August 2020" : 67 Documents clear
Handwriting identification using deep convolutional neural network method Oka Sudana; I Wayan Gunaya; I Ketut Gede Darma Putra
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 4: August 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i4.14864

Abstract

Handwriting is a unique thing that produced differently for each person. Handwriting has a characteristic that remain the same with single writer, so a handwriting can be used as a variable in biometric systems. Each person have a different form of handwriting style but with a small possibility that same characters have something commons. This paper proposes a handwriting identification method using sentence segmented handwriting forms. Sentence form is used to get more complete handwriting characteristics than using a single characters or words. Dataset used is divided into three categories of images, binary, grayscale, and inverted binary. All datasets have same image with different in color and consist of 100 class. Transfer learning used in this paper are pre-trained model VGG19. Training was conducted in 100 epochs. Highest result is grayscale images with genuince acceptance rate of 92.3% and equal error rate of 7.7%.
Early detection of breast cancer using mammography images and software engineering process Muayad Sadik Croock; Saja Dhyaa Khuder; Ayad Esho Korial; Sahar Salman Mahmood
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 4: August 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i4.14718

Abstract

The breast cancer has affected a wide region of women as a particular case. Therefore, different researchers have focused on the early detection of this disease to overcome it in efficient way. In this paper, an early breast cancer detection system has been proposed based on mammography images. The proposed system adopts deep-learning technique to increase the accuracy of detection. The convolutional neural network (CNN) model is considered for preparing the datasets of training and test. It is important to note that the software engineering process model has been adopted in constructing the proposed algorithm. This is to increase the reliably, flexibility and extendibility of the system. The user interfaces of the system are designed as a website used at country side general purpose (GP) health centers for early detection to the disease under lacking in specialist medical staff. The obtained results show the efficiency of the proposed system in terms of accuracy up to more than 90% and decrease the efforts of medical staff as well as helping the patients. As a conclusion, the proposed system can help patients by early detecting the breast cancer at far places from hospital and referring them to nearest specialist center.
Simulation and optimization of a tuneable rectangular microstrip patch antenna based on hybrid metal-graphene and FSS superstrate for fifth-generation applications Nidal Qasem; Hamzah M. Marhoon
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 4: August 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i4.14988

Abstract

In this paper, a tuneable rectangular microstrip patch antenna (MPA) is simulated and optimized to operate in four frequency bands of the next generation of wireless communication systems. The proposed design incorporates a copper radiating patch with four implanted graphene strips for tuning purposes. The reconfigurable surface impedance of graphene can easily be altered by applying a DC voltage bias directly to the graphene strips, allowing the operating frequency of the antenna to be tuned as desired. The capability of the applied voltage to tune the operating frequency band of the proposed antenna is studied via computer simulation technology (CST) microwave studio (MWS). Frequency selective surfaces (FSSs) are introduced in order to improve the radiation parameters of the antenna. The operating frequency band of the tuneable rectangular MPA increases directly as the applied DC voltage bias is increased. Based on the simulation results, a tuneable rectangular MPA placed between two FSSs is proposed for fifth-generation applications.
Measurements to design a coverage area by using high altitude platform systems Riyam Alaa Johni
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 4: August 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i4.14541

Abstract

This paper proposes the principles of how to design UMTS coverage area for Baghdad city the capital of Iraq country that occupy space about 204.2 km², by using new and promising technology for providing wireless narrowband and broadband telecommunication services as well as broadcasting services with either airships or airplanes which is named HAPs, Viewed from its altitude, HAPs floats within the stratosphere layer in the airspace, positioned between satellite and terrestrial platforms.this study also consider the affect of interference with the current broadband technology It will start with brief introduction for HAPS with its advantages, comparison between HAPS system and other services and specify requirements for design. Such as, enumerate the center of coverage area to find the coordinates. Then, supposed the coverage area for the city, and find the radius, elevation angle, and the location of earth stations which will connect HAPS with other networks and all other services location depending on latitude and longitude, finally the reduction of interference technique.
Approximation of regression-based fault minimization for network traffic Chanintorn Jittawiriyanukoon
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 4: August 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i4.13192

Abstract

This research associates three distinct approaches for computer network traffic prediction. They are the traditional stochastic gradient descent (SGD) using a few random samplings instead of the complete dataset for each iterative calculation, the gradient descent algorithm (GDA) which is a well-known optimization approach in Deep Learning, and the proposed method. The network traffic is computed from the traffic load (data and multimedia) of the computer network nodes via the Internet. It is apparent that the SGD is a modest iteration but can conclude suboptimal solutions. The GDA is a complicated one, can function more accurate than the SGD but difficult to manipulate parameters, such as the learning rate, the dataset granularity, and the loss function. Network traffic estimation helps improve performance and lower costs for various applications, such as an adaptive rate control, load balancing, the quality of service (QoS), fair bandwidth allocation, and anomaly detection. The proposed method confirms optimal values out of parameters using simulation to compute the minimum figure of specified loss function in each iteration.
Spatial association discovery process using frequent subgraph mining Giovanni Daián Rottoli; Hernán Merlino
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 4: August 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i4.13858

Abstract

Spatial associations are one of the most relevant kinds of patterns used by business intelligence regarding spatial data. Due to the characteristics of this particular type of information, different approaches have been proposed for spatial association mining. This wide variety of methods has entailed the need for a process to integrate the activities for association discovery, one that is easy to implement and flexible enough to be adapted to any particular situation, particularly for small and medium-size projects to guide the useful pattern discovery process. Thus, this work proposes an adaptable knowledge discovery process that uses graph theory to model different spatial relationships from multiple scenarios, and frequent subgraph mining to discover spatial associations. A proof of concept is presented using real data.
Internet-offline solution: detail description and benchmarking Onno W. Purbo
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 4: August 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i4.13309

Abstract

In this paper, for the first time, the detail of the Internet-Offline solution for rural/village schools is described, and its benchmarking is reported. For providing offline knowledge access, four (4) different systems have examined. An affordable, the RaspberryPi3 server found to be able to provide web as well as file sharing service for up to 20 clients at 100Mbps throughput. UnixBench shows that the RaspberryPi3 about 25% performance of a four-core i5 system. Using consumer grade power banks at 10000-20000mAh, the RaspberryPi3 server may provide a 6+ hour operation. With reliable electrical power, a mini PC provides a more reliable alternative at an order of magnitude increase in cost. For more than 100 users, one may use i5 or higher engines to keep the price-performance ratio low. Besides, in the Internet-Offline system, teachers no longer have to worry about bullies, hoax, or pornographic contents.
Modified moth swarm algorithm for optimal economic load dispatch problem Phu Trieu Ha; Hanh Minh Hoang; Thuan Thanh Nguyen; Thang Trung Nguyen
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 4: August 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i4.15032

Abstract

In this study, optimal economic load dispatch problem (OELD) is resolved by a novel improved algorithm. The proposed modified moth swarm algorithm (MMSA), is developed by proposing two modifications on the classical moth swarm algorithm (MSA). The first modification applies an effective formula to replace an ineffective formula of the mutation technique. The second modification is to cancel the crossover technique. For proving the efficient improvements of the proposed method, different systems with discontinuous objective functions as well as complicated constraints are used. Experiment results on the investigated cases show that the proposed method can get less cost and achieve stable search ability than MSA. As compared to other previous methods, MMSA can archive equal or better results. From this view, it can give a conclusion that MMSA method can be valued as a useful method for OELD problem.
A simplified spatial Modulation MISO-OFDM scheme Vian S. Al-Doori; Emad H. Al-Hemiary
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 4: August 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i4.13873

Abstract

Index modulation is one of the promising techniques for future communications systems due to many improvement over the classical Orthogonal frequency division multiplexing systems such as single RF chain, increased throughput for the same modulation order, achieved tradeoff between the efficiencies of the power and the spectral, and elimination of inter-channel interference. Many forms of index modulation researches exist where symbols are conveyed in antennas, subcarriers, time slots, and the space-time matrix.  Spatial modulation is one member of index modulation family where symbols are conveyed in activating transmit/receive antennas. In this paper, a modification to a standard multiple input single output scheme by integrating spatial modulation using simplified mathematical procedure is achieved. In the transmitter side, data and activation symbols are distributed simultaneously using mathematical module and floor functions. At the receiver, a simplified maximum likelihood detector is used to obtain transmitted pair of symbols. To verify this, MATLAB SIMULINK is used to simulate a downlink system where spatial modulation is applied to a base station. Results for different transmit antenna number and modulation order are obtained in the form of bit error rate versus signal to noise ratio.
Semantics-based clustering approach for similar research area detection Marion Oluwabunmi Adebiyi; Emmanuel B. Adigun; Roseline Oluwaseun Ogundokun; Abidemi Emmanuel Adeniyi; Peace Ayegba; Olufunke O. Oladipupo
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 4: August 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i4.15001

Abstract

The manual process of searching out individuals in an already existing research field is cumbersome and time-consuming. Prominent and rookie researchers alike are predisposed to seek existing research publications in a research field of interest before coming up with a thesis. From extant literature, automated similar research area detection systems have been developed to solve this problem. However, most of them use keyword-matching techniques, which do not sufficiently capture the implicit semantics of keywords thereby leaving out some research articles. In this study, we propose the use of Ontology-based pre-processing, Latent Semantic Indexing and K-Means Clustering to develop a prototype similar research area detection system, that can be used to determine similar research domain publications. Our proposed system solves the challenge of high dimensionality and data sparsity faced by the traditional document clustering technique. Our system is evaluated with randomly selected publications from faculties in Nigerian universities and results show that the integration of ontologies in preprocessing provides more accurate clustering results.

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