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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 67 Documents
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Search results for , issue "Vol 22, No 1: April 2021" : 67 Documents clear
Face Recognition with Frame size reduction and DCT compression using PCA algorithm Padmaja vijaykumar; Jeevan K Mani
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 1: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i1.pp168-178

Abstract

Face recognition has become a very important study of research because it has a variety of applications in research field such as human computer interaction, pattern recognition (PR). A successful face recognition procedure, be it mathematical or numerical, depends on the particular choice of the features used by the classifier. Feature selection in pattern recognition consists of the derivation of salient features present in the raw input data in order to reduce the amount of data used for classification. For the successful face recognition, the database images must have sufficient information so that when presented with the probe image, the recognition must be possible. Majority of times, there is always excess information present in the database images, leads higher storage, hence optimum size of the images needs to be stored in the database for good performance, are compressed with reduction in frame size and then compressed with that of the DCT. 
Efficient intelligent system for diagnosis pneumonia (SARS-COVID19) in X-Ray images empowered with initial clustering Salam Saad Mohamed Ali; Ali Hakem Alsaeedi; Dhiah Al-Shammary; Hassan Hakem Alsaeedi; Hadeel Wajeeh Abid
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 1: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i1.pp241-251

Abstract

This paper proposes efficient models to help diagnose respiratory (SARS-COVID19) infections by developing new data descriptors for standard machine learning algorithms using X-Ray images. As COVID-19 is a significantly serious respiratory infection that might lead to losing life, artificial intelligence plays a main role through machine learning algorithms in developing new potential data classification. Data clustering by K-Means is applied in the proposed system advanced to the training process to cluster input records into two clusters with high harmony. Principle Component Analysis PCA, histogram of orientated gradients (HOG) and hybrid PCA and HOG are developed as potential data descriptors. The wrapper model is proposed for detecting the optimal features and applied on both clusters individually. This paper proposes new preprocessed X-Ray images for dataset featurization by PCA and HOG to effectively extract X-Ray image features. The proposed systems have potentially empowered machine learning algorithms to diagnose Pneumonia (SARS-COVID19) with accuracy up to %97.
The trend malware source of IoT network Susanto Susanto; M. Agus Syamsul Arifin; Deris Stiawan; Mohd. Yazid Idris; Rahmat Budiarto
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 1: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i1.pp450-459

Abstract

Malware may disrupt the internet of thing (IoT) system/network when it resides in the network, or even harm the network operation. Therefore, malware detection in the IoT system/network becomes an important issue. Research works related to the development of IoT malware detection have been carried out with various methods and algorithms to increase detection accuracy. The majority of papers on malware literature studies discuss mobile networks, and very few consider malware on IoT networks. This paper attempts to identify problems and issues in IoT malware detection presents an analysis of each step in the malware detection as well as provides alternative taxonomy of literature related to IoT malware detection. The focuses of the discussions include malware repository dataset, feature extraction methods, the detection method itself, and the output of each conducted research. Furthermore, a comparison of malware classification approaches accuracy used by researchers in detecting malware in IoT is presented.
Adaptive security approach for wireless sensor network using RSA algorithm Maha Salah Asaad; Muayad Sadik Croock
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 1: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i1.pp361-368

Abstract

A type of distributed and self-regulating network is the wireless sensor network (WSN). The sensor nodes have limited computing capabilities, memory, battery power are needed to ensure a strong security design. In this paper, an adaptive cryptographic scheme for WSN that is operating on routing ad hoc on-demand vector routing (AODV) protocol. The adaptive term refers to the adopted mechanism between heavy and light asymmetric cryptography techniques of RSA. The heavy technique adopts the complete version of RSA algorithm, while the light one considers a reduced complexity version. This is to control the security operation over the included nodes even with low power ratio. In various case studies, the proposed scheme is checked and the result obtained shows the high efficiency of results in terms of protection guarantee.
A state-of-the-art survey on semantic similarity for document clustering using GloVe and density-based algorithms Shapol M. Mohammed; Karwan Jacksi; Subhi R. M. Zeebaree
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 1: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i1.pp552-562

Abstract

Semantic similarity is the process of identifying relevant data semantically. The traditional way of identifying document similarity is by using synonymous keywords and syntactician. In comparison, semantic similarity is to find similar data using meaning of words and semantics. Clustering is a concept of grouping objects that have the same features and properties as a cluster and separate from those objects that have different features and properties. In semantic document clustering, documents are clustered using semantic similarity techniques with similarity measurements. One of the common techniques to cluster documents is the density-based clustering algorithms using the density of data points as a main strategic to measure the similarity between them. In this paper, a state-of-the-art survey is presented to analyze the density-based algorithms for clustering documents. Furthermore, the similarity and evaluation measures are investigated with the selected algorithms to grasp the common ones. The delivered review revealed that the most used density-based algorithms in document clustering are DBSCAN and DPC. The most effective similarity measurement has been used with density-based algorithms, specifically DBSCAN and DPC, is Cosine similarity with F-measure for performance and accuracy evaluation.
Particle swarm optimization for airlines fleet assignment Abdallah A. Abouzeid; Mostafa Mohei Eldin; Mohammed Abdel Razek
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 1: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i1.pp427-434

Abstract

Airline fleet assignment is the process of assigning aircraft types to scheduled flight legs in order to minimize operating cost and achieve maximize revenue, while satisfying a set of constraints. This paper formulate the fleet assignment problem for airlines that optimization goal is to minimize the total assignment cost. Particle swarm optimization proposed to solve this model. The model successfully applied to Egyptair airline dataset using the particle swarm optimization and mixed integer programming. The proposed method compared with mixed integer programming and current Egyptair assignment methodology. The results showed that the particle swarm optimization is the best method for the Egyptair fleet assignment process. The solution quality is better than mixed integer programming and Egyptair assignment methodology where we saw a daily cost reduction with a percentage of 14.6% and 19.3% respectively.
Design and monitoring body temperature and heart rate in humans based on WSN using star topology Setiyo Budiyanto; Freddy Artadima Silaban; Lukman Medriavin Silalahi; Selamet Kurniawan; Fajar Rahayu I. M.; Ucuk Darusalam; Septi Andryana
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 1: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i1.pp326-334

Abstract

Electronic health (E-health) uses information and communication technology including electronics, telecommunications, computers, and informatics to process various types of medical information, to carry out clinical services (diagnosis or therapy). Health is the most important asset in human life, therefore maintaining health is a top priority and serious attention needed. Heart rate and body temperature are vital signs that the hospital routinely checks for clinical signs and are useful for strengthening the diagnosis of a disease. In this research monitoring heart rate and body temperature with the wireless sensor network (WSN) method that uses NodeMCU 1.0 as a controller module and wireless as communication between nodes, the wireless network used in this research Wi-Fi network. As a data taker, a DS18b20 temperature sensor and a heart rate sensor (pulse sensor) are needed, which will be displayed by the ThingSpeak web and smartphones. From the test results, the success rate of the system in detecting heart rates is 97.17%. Whereas in detecting body temperature the success rate of the system is 99.28%. For data transmission, the system can send data smoothly at a maximum distance of 15 meters with a barrier.
Models of improved multilink reverse charging network by utilizing the bit error rate QoS attribute Fitri Maya Puspita; Rohania Rohania; Evi Yuliza; Wenny Herlina; Yunita Yunita
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 1: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i1.pp460-468

Abstract

In this paper, a modification model for single-link reverse charging of internet is formed on a multi-link wireless network. The pricing scheme also takes into account the base costs and quality of services provided by the service provider. Bit error rate (BER) was utilized as one of the well-known quality of service (QoS) attribute that can guarantee best performance for internet service provider (ISP) and users. The base price is determined as a decision variable to help ISP to maximize profit. This optimization model can be solved using the LINGO 13.0 program to gain optimal values. The computational results show that by setting costs as constants and service quality as variables, optimal results are obtained for ISPs. This can make ISP considerations in determining the base price that can benefit the ISP and according to the services provided.
New efficient GAF routing protocol using an optimized weighted sum model in WSN Hanane Aznaoui; Arif Ullah; Said Raghay; Layla Aziz; Mubashir Hayat Khan
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 1: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i1.pp396-406

Abstract

A wireless sensor network (WSN) composed by a large number of sensor nodes that are insufficient in terms of processing power, storage and energy. The principal tasks of nodes is gathering and transmitting data collected to the base station (BS). Consequently the major essential criteria for designing a WSN are the network lifetime. In this paper an efficient GAF routing protocol for gathered data is introduced. It proposes an energy-efficient routing in WSN based on the basic version. In this system sensor nodes are distributed using Gaussian law and an active leader is elected for each virtual grid to reduce the energy dissipated using an optimized weighted sum model where maximum remaining energy and minimum distance criteria are considered. Moreover routing data is based on transmission range for enhancing the energy efficiency during data routing. The experimental results shows that the proposed EE-GAF produces better performance than the existing GAF basic and optimized-GAF routing protocol in terms of number of dead node  and energy consumption. It is obviously proves that the proposed EE-GAF can improve the network lifetime
Real-time FPGA implementation of concatenated AES and IDEA cryptography system Sara M. Hassan; Gihan. G. Hamza
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 1: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i1.pp71-82

Abstract

The data encryption is one of the most critical issues in the communication system design. Nowadays, many encryption algorithms are being updated to keep pace with the remarkable progress in the communication field. The advanced encryption standard (AES) is a common algorithm that has proved its efficacy. The main drawback of AES is that it uses too simple algebraic structures, since every block is always encrypted in the same way that makes the hacking process possible if the hacker captures the key and the uses S-Box in the input stage. This especially applies to the unwired communication systems where chances of hacking exceed those found in the wired systems. The paper proposes a security enhancement method that is based on utilizing concatenated AES and international data encryption algorithm (IDEA) algorithms. Upon applying the proposed algorithm, the hacking process becomes a great challenge. The paper incorporates the real-time FPGA implementation of the proposed algorithm in the encryption and the decryption stages. Besides, the paper presents a clear analysis of the system’s performance.

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