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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 2,614 Documents
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Analysis of FAM in satisfaction of inpatient services Muhammad Sabir Ramadhan; Nizwardi Jalinus; Refdinal Refdinal; Marsono Marsono; Yohanni Syahra; Asyahri Hadi Nasyuha; Buyung Solihin Hasugian; Erika Fahmi Ginting; Masyuni Hutasuhut
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 5: October 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i5.20295

Abstract

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.
Characterization and structural analysis of RF magnetron sputtered strontium stannate thin films Yusmar Palapa Wijaya; Khairul Anuar Mohamad; Abu Bakar Abdul Rahman; Afishah Alias; Mohammad Syahmi Nordin
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 4: August 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i4.18790

Abstract

This paper presents physical and morphology properties of strontium stannate (SrSnO3) perovskite-type as a candidate of an n-type material thin film for organic-inorganic hybrid diode heterojunction for optoelectronics application. Typical wet-process of SrSnO3 deposition produce thick film and having 10-8 S/cm order in conductivity. The SrSnO3 thin films were deposited on ITO glass substrates by RF magnetron sputtering using a purity 99.9% SrSnO3 target with 5.0 mTorr of gas pressure and 100 W of RF power at room temperature. The gas composition of pure argon (75%) and reactive oxygen gas (25%) was used for 60 min. XRD diffraction patterns revealed that the thin films are orthorhombic crystal structure with lattice parameter a=5.7040 Ǻ, b=8.06 Ǻ and c=5.7080 Ǻ with a strong orientation in the (002) direction. SEM images showed that films exhibited uniform surface morphology with a roughness average of Ra=2.258 nm and thickness of 311 nm. The EDX spectrum confirmed the presence of O, Sr, and Sn elements in the films with 75.22%, 8.29%, 16.49% in atomic number, respectively. The films were having a conductivity of 8.33x102 S/cm with low resistivity of 12.4x10-3 W-cm.
A novel design of circularly polarized pentagonal planar antenna for ISM band applications F. Ouberri; A. Tajmouati; J. Zbitou; I. Zahraoui; M. Latrach
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 5: October 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i5.19393

Abstract

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.
Adopting explicit and implicit social relations by SVD++ for recommendation system improvement Mohsin Hasan Hussein; Akeel Abdulkareem Alsakaa; Haydar A. Marhoon
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 2: April 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i2.18149

Abstract

Recommender systems suffer a set of drawbacks such as sparsity. Social relations provide a useful source to overcome the sparsity problem. Previous studies have utilized social relations or rating feedback sources. However, they ignored integrating these sources. In this paper, the limitations of previous studies are overcome by exploiting four sources of information, namely: explicit social relationships, implicit social relationships, users’ ratings, and implicit feedback information. Firstly, implicit social relationships are extracted through the source allocation index algorithm to establish new relations among users. Secondly, the similarity method is applied to find the similarity between each pair of users who have explicit or implicit social relations. Then, users’ ratings and implicit rating feedback sources are extracted via a user-item matrix. Furthermore, all sources are integrated into the singular value decomposition plus (SVD++) method. Finally, missing predictions are computed. The proposed method is implemented on three real-world datasets: Last.Fm, FilmTrust, and Ciao. Experimental results reveal that the proposed model is superior to other studies such as SVD, SVD++, EU-SVD++, SocReg, and EISR in terms of accuracy, where the improvement of the proposed method is about 0.03% for MAE and 0.01% for RMSE when dimension value (d) = 10.
Performance evaluation of campus network involving VLAN and broadband multimedia wireless networks using OPNET modeler Dhurgham Abdulridha Jawad Al-Khaffaf; Mohammed G. Al-Hamiri
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 5: October 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i5.18531

Abstract

Modern technology is essential for all healthy, economic, and educational sectors. Using modern technology involves high-performance networks in terms of quality of service (QoS) parameters such as delay, throughput, bandwidth, and security. A campus network involves wire and the wireless environment with and without virtual local area network (VLAN) technology has been simulated using optimized network engineering tools (OPNET). The simulation model includes four scenarios that involve heavy-loaded File transfer protocol (FTP) and web browsing applications with two logical groups of users. The simulation results show that the VLAN overcome LAN networks in terms of bandwidth and security. This has been done by reducing the throughput in both sending and receiving levels to the confidential servers. The VLAN has also reduced the broadcast domain which results in a high-power efficiency. Moreover, the VLAN network technology has been proved to have lower values of delay in transferring files and packets than LAN network technology. In addition, VLAN technology generally has been decreased values of throughput regardless of the way of connection between servers and workstations. This, in turn, allows taking advantage of wireless connection features in terms of flexibility of installation and speed of configuration.
Classification using semantic feature and machine learning: Land-use case application Hela Elmannai; Abeer Dhafer AlGarni
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 4: August 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i4.18359

Abstract

Land cover classification has interested recent works especially for deforestation, urban are monitoring and agricultural land use. Traditional classification approaches have limited accuracy especially for non-heterogeneous land cover. Thus, using machine may improve the classification accuracy. The presented paper deals with the land-use scene recognition on very high-resolution remote sensing imagery. We proposed a new framework based on semantic features, handcrafted features and machine learning classifiers decisions. The method starts by semantic feature extraction using a convolutional neural network. Handcraft features are also extracted based on color and multi-resolution characteristics. Then, the classification stage is processed by three learning machine algorithms. The final classification result performed by majority vote algorithm. The idea behind is to take advantages from semantic features and handcrafted features. The second scope is to use the decision fusion to enhance the classification result. Experimentation results show that the proposed method provides good accuracy and trustable tool for land use image identification.
Effect of random sampling on spectrum sensing for cognitive radio networks Asmaa Maali; Hayat Semlali; Sara Laafar; Najib Boumaaz; Abdallah Soulmani
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 4: August 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i4.20399

Abstract

Cognitive radio is a mechanism allowing dynamic access to spectrum channels. Since its beginnings, researchers have been working on using this inventive technology to control and manage the spectrum resources. Consequently, this research field has been progressing rapidly and important advances have been made. Spectrum sensing is a key function of cognitive radios that helps prevent the harmful interference with licensed users, as well as identifies the available spectrum to improve its utilization. Several spectrum sensing techniques are found in scientific literature. In this paper, we investigate the effect of the random sampling in spectrum sensing. We propose a spectrum sensing approach based on the energy detection and on the maximum eigenvalue detection (MED) combined with random sampling. The performance of the proposed approach is evaluated in terms of the receiver operating characteristics curves and in terms of the detection probability for different values of signal to noise ratio. The obtained results are compared to the uniform sampling case to show the added value of random sampling.
Enabling seamless communication over several IoT messaging protocols in OpenFlow network Fauzi Dwi Setiawan Sumadi; Agus Eko Minarno; Lailis Syafa’ah; Muhammad Irfan
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 5: October 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i5.20412

Abstract

The most prominent protocols for data transfer in internet of things (IoT) are message queuing telemetry transport (MQTT) and constrained application protocol (CoAP). The existing clients from both sides are unable to communicate directly because of the packet’s header structure difference in application and transport layer. In response, this paper aims to develop a bidirectional conversion server used to translate the specified messaging protocol interchangeably in the OpenFlow network and transmit the converted packet from both sides. The conversion server integrated the MQTT subscriber and CoAP POST object for converting the MQTT message into CoAP data. Similarly, the CoAP-MQTT translation was processed by CoAP GET and MQTT publisher object. The research was evaluated by analysing the round trip time (RTT) value, conversion delay, and power consumption. The RTT value for MQTT-CoAP required 0.5 s while the CoAP-MQTT was accumulated in 0.1 s for single-packet transmission. In addition, the SDN controller and the conversion server only consumed less than 1% central processing unit (CPU) usage during the experiment. The result indicated that the proposed conversion server could handle the translation even though there was an overwhelming request from the clients.
Analysis of hybrid non-linear autoregressive neural network and local smoothing technique for bandwidth slice forecast Mohamed Khalafalla Hassan; Sharifah H. S. Ariffin; Sharifah Kamilah Syed- Yusof; N. Effiyana Ghazali; Mohamed EA Kanona
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 4: August 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i4.17024

Abstract

The demand for high steady state network traffic utilization is growing exponentially. Therefore, traffic forecasting has become essential for powering greedy application and services such as the internet of things (IoT) and Big data for 5G networks for better resource planning, allocation, and optimization. The accuracy of forecasting modeling has become crucial for fundamental network operations such as routing management, congestion management, and to guarantee quality of service overall. In this paper, a hybrid network forecast model was analyzed; the model combines a non-linear auto regressive neural network (NARNN) and various smoothing techniques, namely, local regression (LOESS), moving average, locally weighted scatterplot smoothing (LOWESS), the Sgolay filter, Robyn loess (RLOESS), and robust locally weighted scatterplot smoothing (RLOWESS). The effects of applying smoothing techniques with varied smoothing windows were shown and the performance of the hybrid NARNN and smoothing techniques discussed. The results show that the hybrid model can effectively be used to enhance forecasting performance in terms of forecasting accuracy, with the assistance of the smoothing techniques, which minimized data losses. In this work, root mean square error (RMSE) is used as performance measures and the results were verified via statistical significance tests.
Detection of brain stroke in the MRI image using FPGA Dheyaa Alhelal; Ahmed Khazal Younis; Ruaa H. Ali Al-Mallah
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 4: August 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i4.18988

Abstract

One of the most important difficulties which doctors face in diagnosing is the analysis and diagnosis of brain stroke in magnetic resonance imaging (MRI) images. Brain stroke is the interruption of blood flow to parts of the brain that causes cell death. To make the diagnosis easier for doctors, many researchers have treated MRI images with some filters by using Matlab program to improve the images and make them more obvious to facilitate diagnosis by doctors. This paper introduces a digital system using hardware concepts to clarify the brain stroke in MRI image. Field programmable gate arrays (FPGA) is used to implement the system which is divided into four phases: preprocessing, adjust image, median filter, and morphological filters alternately. The entire system has been implemented based on Zynq FPGA evaluation board. The design has been tested on two MRI images and the results are compared with the Matlab to determine the efficiency of the proposed system. The proposed hardware system has achieved an overall good accuracy compared to Matlab where it ranged between 90.00% and 99.48%.

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