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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 5: October 2020" : 65 Documents clear
Mobile learning architecture using fog computing and adaptive data streaming Shymaa Mohammed Jameel; Muayad Sadik Croock
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 5: October 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i5.16712

Abstract

With the huge development in mobile and network fields, sensor technologies and fog computing help the students for more effective learning, flexible and in and effective manner from anywhere. Using the mobile device for learn encourage the transition to mobile computing (cloud and fog computing) which is led to the ability to design customized system that help student to learn via context aware learning which can be done by set the user preference and use proper methods to show only related manner subject. The presented study works on developing a system of e-learning which has been on the basis of fog computing concepts with deep learning approaches utilized for classification to the data content for accomplishing the context aware learning and use the adaptation of video quality using special equation and the data encrypted and decrypted using 3DES algorithm to ensure the security side of the operation.
TAMEx framework as an alternative for e-exam implementation in wireless network Gede Sukadarmika; Rukmi Sari Hartati; Linawati Linawati; Nyoman Putra Sastra
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 5: October 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i5.15774

Abstract

One of significant change in learning process is exam implementation applying a computer-based test (e-exam) rather than paper-based test. Many institutions currently use wireless network with bring your own device (BYOD) policy for their e-exam implementation, due to limitation of space and user terminals. Moreover it is hard to maintain the availability of reliable signal quality in wireless network for all users during e-exam process. Therefore, this research proposes a development of time adaptive for mobile exam (TAMEx) framework to provide all users with good quality of service of e-exam in wireless network environment when dealing with signal quality variations. The received signal strength indication (RSSI) is the main indicator of the signal quality. The framework supports e-exam implementation in wirelesslocal area network and the use of BYOD mechanism. The research shows that the framework successfully has provided time compensation for the users who experienced temporary connection loss due to bad signal quality. The result exhibits that tiny processing time has been needed for signal loss detection, user’s request of compensation time, and server’s execution. In conclusion, the TAMEx could guarantee good services for all users who doing e-exam in wireless network environment.
Assessment of Landsat 8 TIRS data capability for the preliminary study of geothermal energy resources in West Sumatra Yuhendra Yuhendra; Joshapat Tetuko Sri Sumantyo
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 5: October 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i5.16172

Abstract

West Sumatra is one of has big geothermal energy resources potential. Remote sensing technology can have a role in geothermal exploration activity to measure the distribution of land surface temperatures (LST) and predict the geothermal potential area. Main study to obtain the assessment of Landsat 8 TIRS (Landsat`s Thermal Infrared Sensor) data capability for geothermal energy resources estimation. Mono-window algorithms were used to generate the LST maps. Data set was combined with a digital elevation model (DEM) to identify the potential geothermal energy based on the variation in surface temperature. The result that were derived from LST map of West Sumatra shows that ranged from -8.6 C0 to 32.59 C0 and the different temperatures are represented by a graduated pink to brown shading. A calculated result clearly identifies the hot areas in the dataset, which are brown in colour images. Lima Puluh Kota, Tanah Datar, Solok, and South Solok areas showed the high-temperature value (Brown) in the range of 28.1 C0 to 32.59 C0 color in images which means that they possess high potential for generating thermal energy. In contrast, the temperatures were lower (Pink) in the north-eastern areas and the range distribution was from-8.5 C0 to 5 C0.
Prediction of rainfall using improved deep learning with particle swarm optimization Imam Cholissodin; Sutrisno Sutrisno
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 5: October 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i5.14665

Abstract

Rainfall is a natural factor that is very important for farmers or certain institutions to predict the planting period of a plant. The problem is that rainfall is very difficult to predict. Trials to get optimal rainfall prediction have been carried out by BMKG through research with variety of methods in various fields, including meteorology, climatology and geophysics. The results of the study unfortunately obtained a less optimal success rate in predicting rainfall. Today, there are many new methods for predicting events. These methods include Deep Learning (DL) and Particle Swarm Optimization (PSO). The use of the Deep Learning method is very susceptible to initial weights that are less than optimal, so it requires a process of optimization using a metaheuristic technique, which is the PSO algorithm, because this algorithm has a level of complexity that is much lower than genetic algorithms. In this study, this method is utilized to predict rainfall by determining the exact regression equation model according to the number of layers in hidden nodes based on the size of the kernel and the weight between the layers. This research is approved achieved get more optimal rainfall prediction results that those of previous research that without optimization with PSO.
Modifying Hamming code and using the replication method to protect memory against triple soft errors Wael Toghuj
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 5: October 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i5.13345

Abstract

As technology scaling increases computer memory’s bit-cell density and reduces the voltage of semiconductors, the number of soft errors due to radiation induced single event upsets (SEU) and multi-bit upsets (MBU) also increases. To address this, error-correcting codes (ECC) can be used to detect and correct soft errors, while x-modular-redundancy improves fault tolerance. This paper presents a technique that provides high error-correction performance, high speed, and low complexity. The proposed technique ensures that only correct values get passed to the system output or are processed in spite of the presence of up to three-bit errors. The Hamming code is modified in order to provide a high probability of MBU detection. In addition, the paper describes the new technique and associated analysis scheme for its implementation. The new technique has been simulated, evaluated, and compared to error correction codes with similar decoding complexity to better understand the overheads required, the gained capabilities to protect data against three-bit errors, and to reduce the misdetection probability and false-detection probability of four-bit errors.
An efficient color image compression technique Walaa M. Abd-Elhafiez; Wajeb Gharibi; Mohamed Heshmat
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 5: October 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i5.8632

Abstract

We present a new image compression method to improve visual perception of the decompressed images and achieve higher image compression ratio. This method balances between the compression rate and image quality by compressing the essential parts of the image-edges. The key subject/edge is of more significance than background/non-edge image. Taking into consideration the value of image components and the effect of smoothness in image compression, this method classifies the image components as edge or non-edge. Low-quality lossy compression is applied to non-edge components whereas high-quality lossy compression is applied to edge components. Outcomes show that our suggested method is efficient in terms of compression ratio, bits per-pixel and peak signal to noise ratio.
An overview of internet of things Sebastian Villamil; Cesar Hernandez; Giovanny Tarazona
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 5: October 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i5.15911

Abstract

The internet of things is an emerging technology that is currently present in most processes and devices, allowing to improve the quality of life of people and facilitating the access to specific information and services. The main purpose of the present article is to offer a general overview of internet of things, based on the analysis of recently published work. The added value of this article lies in the analysis of the main recent publications and the diversity of applications of internet of things technology. As a result of the analysis of the current literature, internet of things technology stands out as a facilitator in business and industrial performance but above all in improving the quality of life. As a conclusion to this document, the internet of things is a technology that can overcome the challenges in terms of security, processing capacity and data mobility, as long as the development related to other technologies follows its expected course.
Improving color rendering index of WLEDs with convex-dual-layer remote phosphor geometry using red-emitting CaGa2S4:Mn2+ phosphor Nguyen Thi Phuong Loan; Anh Tuan Le
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 5: October 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i5.14250

Abstract

The white-light light-emitting diode (LED), a conventional illumination solution, usually consists of one chip and one phosphor layer, which leads to the insufficient color rendering index (CRI) in this configuration. To optimize the efficiency of WLED, a new LED package with 2 chips and one phosphor was proposed, this innovative configuration can yield more lights and achieve high CRI. Thus, this study aims at perfecting the color performance with the two chips and dual phosphor layers package with the proportions and densities of phosphor in the silicone constantly changed to find the best option. The white-light LED module is adjusted using a specialized color design model. The comparison results between the measured and the simulation from the color design model CIE 1931 color coordinates suggest that the highest discrepancy is about 0.0063 and is achieved at around 5600K correlated color temperature (CCT). This study’s results lay a firm path in customizing white-light LED modules that guarantee CRI and lumen output qualities.
Secure and reliable wireless advertising system using intellectual characteristic selection algorithm for smart cities Yousra Abdul Alsahib S. Aldeen; Haider Mohammed Abdulhadi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 5: October 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i5.14859

Abstract

Smart cities wireless advertising (smart mobile-AD) filed is one of the well-known area of research where smart devices using mobile ad hoc networks (MANET) platform for advertisement and marketing purposes. Wireless advertising through multiple fusion internet of things (IoT) sensors is one of the important field where the sensors combines multiple sensors information and accomplish the control of self-governing intelligent machines for smart cities advertising framework. With many advantages, this field has suffered with data security. In order to tackle security threats, intrusion detection system (IDS) is adopted. However, the existing IDS system are not able to fulfill the security requirements. This paper proposes an intellectual characteristic selection algorithm (ICSA) integrated with normalized intelligent genetic algorithm-based min-max feature selection (NIGA-MFS). The proposed solution designs for wireless advertising system for business/advertising data security and other transactions using independent reconfigurable architecture. This approach supports the wireless advertising portals to manage the data delivery by using 4G standard. The proposed reconfigurable architecture is validated by using applications specific to microcontrollers with multiple fusion IoT sensors.
Kernal based speaker specific feature extraction and its applications in iTaukei cross language speaker recognition Satyanand Singh; Pragya Singh
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 5: October 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i5.14655

Abstract

Extraction and classification algorithms based on kernel nonlinear features are popular in the new direction of research in machine learning. This research paper considers their practical application in the iTaukei automatic speaker recognition system (ASR) for cross-language speech recognition. Second, nonlinear speaker-specific extraction methods such as kernel principal component analysis (KPCA), kernel independent component analysis (KICA), and kernel linear discriminant analysis (KLDA) are summarized. The conversion effects on subsequent classifications were tested in conjunction with Gaussian mixture modeling (GMM) learning algorithms; in most cases, computations were found to have a beneficial effect on classification performance. Additionally, the best results were achieved by the Kernel linear discriminant analysis (KLDA) algorithm. The performance of the ASR system is evaluated for clear speech to a wide range of speech quality using ATR Japanese C language corpus and self-recorded iTaukei corpus. The ASR efficiency of KLDA, KICA, and KLDA technique for 6 sec of ATR Japanese C language corpus 99.7%, 99.6%, and 99.1% and equal error rate (EER) are 1.95%, 2.31%, and 3.41% respectively. The EER improvement of the KLDA technique-based ASR system compared with KICA and KPCA is 4.25% and 8.51% respectively.

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