cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
-
Contact Email
-
Phone
-
Journal Mail Official
-
Editorial Address
-
Location
Kota yogyakarta,
Daerah istimewa yogyakarta
INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
Published by Institute of Advanced Engineering and Science
ISSN : 25024752     EISSN : 25024760     DOI : -
Core Subject :
Arjuna Subject : -
Articles 31 Documents
 1   2   3   4 
Search results for , issue "Vol 7, No 1: July 2017" : 31 Documents clear
Development of Photo Forensics Algorithm by Detecting Photoshop Manipulation using Error Level Analysis Teddy Surya Gunawan; Siti Amalina Mohammad Hanafiah; Mira Kartiwi; Nanang Ismail; Nor Farahidah Za'bah; Anis Nurashikin Nordin
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 1: July 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v7.i1.pp131-137

Abstract

Nowadays, image manipulation is common due to the availability of image processing software, such as Adobe Photoshop or GIMP. The original image captured by digital camera or smartphone normally is saved in the JPEG format due to its popularity. JPEG algorithm works on image grids, compressed independently, having size of 8x8 pixels. For unmodified image, all 8x8 grids should have a similar error level. For resaving operation, each block should degrade at approximately the same rate due to the introduction of similar amount of errors across the entire image. For modified image, the altered blocks should have higher error potential compred to the remaining part of the image. The objective of this paper is to develop a photo forensics algorithm which can detect any photo manipulation. The error level analysis (ELA) was further enhanced using vertical and horizontal histograms of ELA image to pinpoint the exact location of modification. Results showed that our proposed algorithm could identify successfully the modified image as well as showing the exact location of modifications.
Content Based Image Retrieval using Feature Extraction in JPEG Domain and Genetic Algorithm Parvin N; Kavitha P
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 1: July 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v7.i1.pp226-233

Abstract

Content-Based Image Retrieval (CBIR) aims at retrieving the images from the database based on the user query which is visual form rather than the traditional text form. The applications of CBIR extends from surveillance to remote sensing, medical imaging to weather forecasting, security systems to historical research and so on. Though extensive research is made on content based image retrieval in the spatial domain, we have most images in the internet which is JPEG compressed which pushes the need for image retrieval in the compressed domain itself rather than decoding it to raw format before comparison and retrieval. This research addresses the need to retrieve the images from the database based on the features extracted from the compressed domain along with the application of genetic algorithm in improving the retrieval results. The research focuses on various features and their levels of impact on improving the precision and recall parameters of the CBIR system. Our experimentation results also indicate that the CBIR features in compressed domain along with the genetic algorithm usage improves the results considerably when compared with the literature techniques. 
Heat Response Model for Phase Layered Topology in A Photovoltaic Thermal System Mohammad Taghi Hajibeigy; Chockalingam Aravind Vaithilingam; Mushtak Al-atabi; PRP Hoole
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 1: July 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v7.i1.pp52-60

Abstract

The electrical and thermal energy generated by a Photo-voltaic (PV) module is based on the amount of the solar radiation directed on the PV module. In this study, a Photo-voltaic Thermal (PVT) system is constructed to maximize the electrical energy generation through the fast removal of heat through a new phase layered topology. The combinations of aluminum plate and heatsinks are used to transfer heat generated by sunlight radiation on PV modules to heat transfer thermal container. The aluminum plate is attached beneath the PV module and heatsinks welded beneath the alumni plate making it as a phase layered heat removal. The heat transfer on each layer of the photovoltaic thermal system is investigated with the phase changing topology and also investigated for its performance with a heat removal agent. In both cases, with and without water as coolant in the thermal container, the experimental outcome is analysed for performance analysis. It is found the PV temperature reduced by about 10 degrees which is cirtical for the PV performance reducing the wasted thermal energy and thereby increases the electrical energy conversion.
A Condorcet Voting Theory Based AHP Approach for MCDM Problems Sweta Bhattacharya; V Raju
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 1: July 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v7.i1.pp276-286

Abstract

Analytical Hierarchical Process has been used as a useful methodology for multi-criteria decision making environments with substantial applications in recent years. But the weakness of the traditional AHP method lies in the use of subjective judgement based assessment and standardized scale for pairwise comparison matrix creation. The paper proposes a Condorcet Voting Theory based AHP method to solve multi criteria decision making problems where Analytical Hierarchy Process (AHP) is combined with Condorcet theory based preferential voting technique followed by a quantitative ratio method for framing the comparison matrix instead of the standard importance scale in traditional AHP approach. The consistency ratio (CR) is calculated for both the approaches to determine and compare the consistency of both the methods. The results reveal Condorcet – AHP method to be superior generating lower consistency ratio and more accurate ranking of the criterion for solving MCDM problems.
Performance Evaluation of Elliptical-Cylindrical Antenna Array using SaDE Optimized Hyper Beam Gebrehiwet Gebrekrstos Lema
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 1: July 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v7.i1.pp178-188

Abstract

For high performance communication systems, Side Lobe Level (SLL) reduction and improved directivity are the goal of antenna designers. In the recent years, many optimization techniques of antenna design are occupying demanding place over the analytical techniques. Though they have contributed attractive solutions, it is often obvious to select one that meets the particular design need at hand. In this paper, an optimization technique called Self-adaptive Differential Evolution (SaDE) that can be able to learn and behave intelligently along with hyper beam forming is integrated to determine an optimal set of excitation weights in the design of EcAA. Non-uniform excitation weights of the individual array elements of EcAA are performed to obtain reduced SLL, high directivity and flexible radiation pattern. To evaluate the improved performance of the proposed SaDE optimized hyper beam, comparison are done with uniformly excited, SaDE without hyper beam and Genetic Algorithm (GA). In general, the proposed work of pattern synthesis has resulted in much better reduction of SLL and FNBW than both the uniformly excited and thinned EcAA. The results of this study clearly reveal that the SLL highly reduced at a very directive beamwidth.
An Empirical Performance Evaluation of Docker Container, Openstack Virtual Machine and Bare Metal Server Jyoti Shetty; Sahana Upadhaya; Rajarajeshwari H S; Shobha G; Jayant Chandra
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 1: July 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v7.i1.pp205-213

Abstract

Server virtualization is a fundamental technological innovation that is used extensively in IT enterprises. Server virtualization enables creation of multiple virtual machines on single underlying physical machine. It is realized either in form of hypervisors or containers. Hypervisor is an extra layer of abstraction between the hardware and virtual machines that emulates underlying hardware. In contrast, the more recent container-based virtualization technology runs on host kernel without additional layer of abstraction.Thus container technology is expected to provide near native performance compared to hypervisor based technology. We have conducted a series of experiments to measure and compare the performance of workloads over hypervisor based virtual machines, Docker containers and native bare metal machine. We use a standard benchmark workload suite that stress CPU, memory, disk IO and system. The results obtained show that Docker containers provide better or similar performance compared to traditional hypervisor based virtual machines in almost all the tests. However as expected the native system still provides the best performance as compared to either containers or hypervisors.
Artificial Neural Network Based Fast Edge Detection Algorithm for MRI Medical Images Teddy Surya Gunawan; Iza Zayana Yaacob; Mira Kartiwi; Nanang Ismail; Nor Farahidah Za'bah; Hasmah Mansor
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 1: July 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v7.i1.pp123-130

Abstract

Currently, magnetic resonance imaging (MRI) has been utilized extensively to obtain high contrast medical image due to its safety which can be applied repetitively. Edges are represented as important contour features in the medical image since they are the boundaries where distinct intensity changes or discontinuities occur. Many traditional algorithms have been proposed to detect the edge, such as Canny, Sobel, Prewitt, Roberts, Zerocross, and Laplacian of Gaussian (LoG). Moreover, many researches have shown the potential of using Artificial Neural Network (ANN) for edge detection. Although many algorithms have been conducted on edge detection for medical images, however higher computational cost and subjective image quality could be further improved. Therefore, the objective of this paper is to develop a fast ANN based edge detection algorithm for MRI medical images. First, we developed features based on horizontal, vertical, and diagonal difference. Then, Canny edge detector will be used as the training output. Finally, optimized parameters will be obtained, including number of hidden layers and output threshold. Results showed that the proposed algorithm provided better image quality while it has faster processing time around three times time compared to other traditional algorithms, such as Sobel and Canny edge detector.
Distributed Optimal Relay Selection in Wireless Sensor Networks Karthik R; Nagaraju J; Mahendra Vucha
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 1: July 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v7.i1.pp71-74

Abstract

In wireless distributed sensor networks, one open problem is how to guarantee the reliable relay selection based on the quality of services diversity. To address this problem, we focus on the reliable adaptive relay selection approach and adaptive QoS supported algorithm, based on which we present a Markov chain model, in consideration of different packet states and error control algorithm assignment. The mathematical analyses and MATLAB simulation results show that the proposed relay selection approach could perform better in terms of saturation throughput, reliability, and energy efficiency, compared with the traditional approaches. More importantly, the quality of real-time multimedia streaming is improved significantly, in terms of decodable frame ratio and delay.
Performance Evaluation of Ethernet Network for Mobile Fronthual Networks Dawit Hadush Hailu
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 1: July 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v7.i1.pp287-298

Abstract

Increasing mobile data traffic due to the rise of both smartphones and tablets has led to high-capacity demand of mobile data network. To meet the ever-growing capacity demand and reduce the cost of mobile network components, Cloud Radio Access Network (C-RAN) has emerged as a promising solution. In such network, the mobile operator’s Remote Radio Head (RRH) and Base Band Unit (BBU) are often separated and the connection between them has very tight timing and latency requirements imposed by Common Public Radio Interface (CPRI) and 3rd Generation Partnership Project (3GPP). This fronthaul connection is not yet provided by packet based network. To employ packet-based network for C-RAN fronthaul, the carried fronthaul traffic are needed to achieve the requirements of fronthaul streams. For this reason, the aim of this paper is focused on investigating and evaluating the feasibility of Ethernet networks for mobile fronthaul. The fronthaul requirements used to evaluate and investigate this network are maximum End to End (E2E) latency, Packet Loss Ratio (PLR) and Packet Delay Variation (PDV). The simulated results and numerical analysis confirm that the PDV and PLR of High Priority (HP) traffic in Ethernet network meet the requirements of mobile fronthaul using CPRI. However, the PDV of HP traffic meets the fronthaul network when the number of nodes in the Ethernet network is at most four. For Ethernet network, the number of nodes in the network limits the maximum separation distance between BBU and RRH (link length); for increasing the number of nodes, the link length decreases. Consequently, Radio over Ethernet (RoE) traffic should receive the priority and Quality of Service (QoS) HP can provide. On the other hand, Low Priority (LP) classes are not sensitive to QoS metrics and should be used for transporting time insensitive applications and services.
Customized Hardware Crypto Engine for Wireless Sensor Networks Medhat Awadalla; Ahmed Al Maashri; Lavanya Pathuri; Afaq Ahmad
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 1: July 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v7.i1.pp263-275

Abstract

Nowadays, managing for optimal security to wireless sensor networks (WSNs) has emerged as an active research area. The challenging topics in this active research involve various issues such as energy consumption, routing algorithms, selection of sensors location according to a given premise, robustness, and efficiency. Despite the open problems in WSNs, already a high number of applications available shows the activeness of emerging research in this area. Through this paper, authors propose an alternative routing algorithmic approach that accelerate the existing algorithms in sense to develop a power-efficient crypto system to provide the desired level of security on a smaller footprint, while maintaining real-time performance and mapping them to customized hardware. To achieve this goal, the algorithms have been first analyzed and then profiled to recognize their computational structure that is to be mapped into hardware accelerators in platform of reconfigurable computing devices. An intensive set of experiments have been conducted and the obtained results show that the performance of the proposed architecture based on algorithms implementation outperforms the software implementation running on contemporary CPU in terms of the power consumption and throughput.

Page 2 of 4 | Total Record : 31

 1   2   3   4 

Filter by Year

2017 2017


Reset
Filter By Issues
All Issue Vol 41, No 1: January 2026 Vol 40, No 3: December 2025 Vol 40, No 2: November 2025 Vol 40, No 1: October 2025 Vol 39, No 3: September 2025 Vol 39, No 2: August 2025 Vol 39, No 1: July 2025 Vol 38, No 3: June 2025 Vol 38, No 2: May 2025 Vol 38, No 1: April 2025 Vol 37, No 3: March 2025 Vol 37, No 2: February 2025 Vol 37, No 1: January 2025 Vol 36, No 3: December 2024 Vol 36, No 2: November 2024 Vol 36, No 1: October 2024 Vol 35, No 3: September 2024 Vol 35, No 2: August 2024 Vol 35, No 1: July 2024 Vol 34, No 3: June 2024 Vol 34, No 2: May 2024 Vol 34, No 1: April 2024 Vol 33, No 3: March 2024 Vol 33, No 2: February 2024 Vol 33, No 1: January 2024 Vol 32, No 3: December 2023 Vol 32, No 1: October 2023 Vol 31, No 3: September 2023 Vol 31, No 2: August 2023 Vol 31, No 1: July 2023 Vol 30, No 3: June 2023 Vol 30, No 2: May 2023 Vol 30, No 1: April 2023 Vol 29, No 3: March 2023 Vol 29, No 2: February 2023 Vol 29, No 1: January 2023 Vol 28, No 3: December 2022 Vol 28, No 2: November 2022 Vol 28, No 1: October 2022 Vol 27, No 3: September 2022 Vol 27, No 2: August 2022 Vol 27, No 1: July 2022 Vol 26, No 3: June 2022 Vol 26, No 2: May 2022 Vol 26, No 1: April 2022 Vol 25, No 3: March 2022 Vol 25, No 2: February 2022 Vol 25, No 1: January 2022 Vol 24, No 3: December 2021 Vol 24, No 2: November 2021 Vol 24, No 1: October 2021 Vol 23, No 3: September 2021 Vol 23, No 2: August 2021 Vol 23, No 1: July 2021 Vol 22, No 3: June 2021 Vol 22, No 2: May 2021 Vol 22, No 1: April 2021 Vol 21, No 3: March 2021 Vol 21, No 2: February 2021 Vol 21, No 1: January 2021 Vol 20, No 3: December 2020 Vol 20, No 2: November 2020 Vol 20, No 1: October 2020 Vol 19, No 3: September 2020 Vol 19, No 2: August 2020 Vol 19, No 1: July 2020 Vol 18, No 3: June 2020 Vol 18, No 2: May 2020 Vol 18, No 1: April 2020 Vol 17, No 3: March 2020 Vol 17, No 2: February 2020 Vol 17, No 1: January 2020 Vol 16, No 3: December 2019 Vol 16, No 2: November 2019 Vol 16, No 1: October 2019 Vol 15, No 3: September 2019 Vol 15, No 2: August 2019 Vol 15, No 1: July 2019 Vol 14, No 3: June 2019 Vol 14, No 2: May 2019 Vol 14, No 1: April 2019 Vol 13, No 3: March 2019 Vol 13, No 2: February 2019 Vol 13, No 1: January 2019 Vol 12, No 3: December 2018 Vol 12, No 2: November 2018 Vol 12, No 1: October 2018 Vol 11, No 3: September 2018 Vol 11, No 2: August 2018 Vol 11, No 1: July 2018 Vol 10, No 3: June 2018 Vol 10, No 2: May 2018 Vol 10, No 1: April 2018 Vol 9, No 3: March 2018 Vol 9, No 2: February 2018 Vol 9, No 1: January 2018 Vol 8, No 3: December 2017 Vol 8, No 2: November 2017 Vol 8, No 1: October 2017 Vol 7, No 3: September 2017 Vol 7, No 2: August 2017 Vol 7, No 1: July 2017 Vol 6, No 3: June 2017 Vol 6, No 2: May 2017 Vol 6, No 1: April 2017 Vol 5, No 3: March 2017 Vol 5, No 2: February 2017 Vol 5, No 1: January 2017 Vol 4, No 3: December 2016 Vol 4, No 2: November 2016 Vol 4, No 1: October 2016 Vol 3, No 3: September 2016 Vol 3, No 2: August 2016 Vol 3, No 1: July 2016 Vol 2, No 3: June 2016 Vol 2, No 2: May 2016 Vol 2, No 1: April 2016 Vol 1, No 3: March 2016 Vol 1, No 2: February 2016 Vol 1, No 1: January 2016 Vol 16, No 3: December 2015 Vol 16, No 2: November 2015 Vol 16, No 1: October 2015 Vol 15, No 3: September 2015 Vol 15, No 2: August 2015 Vol 15, No 1: July 2015 Vol 14, No 3: June 2015 Vol 14, No 2: May 2015 Vol 14, No 1: April 2015 Vol 13, No 3: March 2015 Vol 13, No 2: February 2015 Vol 13, No 1: January 2015 Vol 12, No 12: December 2014 Vol 12, No 11: November 2014 Vol 12, No 10: October 2014 Vol 12, No 9: September 2014 Vol 12, No 8: August 2014 Vol 12, No 7: July 2014 Vol 12, No 6: June 2014 Vol 12, No 5: May 2014 Vol 12, No 4: April 2014 Vol 12, No 3: March 2014 Vol 12, No 2: February 2014 Vol 12, No 1: January 2014 Vol 11, No 12: December 2013 Vol 11, No 11: November 2013 Vol 11, No 10: October 2013 Vol 11, No 9: September 2013 Vol 11, No 8: August 2013 Vol 11, No 7: July 2013 Vol 11, No 6: June 2013 Vol 11, No 5: May 2013 Vol 11, No 4: April 2013 Vol 11, No 3: March 2013 Vol 11, No 2: February 2013 Vol 11, No 1: January 2013 Vol 10, No 8: December 2012 Vol 10, No 7: November 2012 Vol 10, No 6: October 2012 Vol 10, No 5: September 2012 Vol 10, No 4: August 2012 Vol 10, No 3: July 2012 More Issue