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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 :
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Articles 67 Documents
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Search results for , issue "Vol 22, No 1: April 2021" : 67 Documents clear
Designing consensus algorithm for collaborative signature-based intrusion detection system Eko Arip Winanto; Mohd Yazid Idris; Deris Stiawan; Mohammad Sulkhan Nurfatih
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.pp485-496

Abstract

Signature-based collaborative intrusion detection system (CIDS) is highly depends on the reliability of nodes to provide IDS attack signatures. Each node in the network is responsible to provide new attack signature to be shared with other node. There are two problems exist in CIDS highlighted in this paper, first is to provide data consistency and second is to maintain trust among the nodes while sharing the attack signatures. Recently, researcher find that blockchain has a great potential to solve those problems. Consensus algorithm in blockchain is able to increase trusts among the node and allows data to be inserted from a single source of truth. In this paper, we are investigating three blockchain consensus algorithms: proof of work (PoW), proof of stake (PoS), and hybrid PoW-PoS chain-based consensus algorithm which are possibly to be implemented in CIDS. Finally, we design an extension of hybrid PoW-PoS chain-based consensus algorithm to fulfill the requirement. This extension we name it as proof of attack signature (PoAS).
Basic FBG apodization functions effects on the filtered optical acoustic signal Mahmoud M. A. Eid; Ahmed Nabih Zaki Rashed
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.pp287-296

Abstract

This article clarified the basic fiber Bragg grating (FBG) apodization functions effects on the filtered optical acoustic signal (AS). Max optical acoustic power variations after acousto optic filter is clarified with the spectral wavelength variations. FBG apodization functions are uniform, Gaussian, and Tanh. We have tested the max optical acoustic power variations after various apodization FBG functions with the spectral wavelength variations. The max AS power amplitude after the electrical combiner is reported based various Apodization FBG functions. The max optical AS after FBG is studied with various FBG lengths for various FBG apodization functions at the central wavelength of 1.55 μm. The max electrical power after power combiner unit is demonstrated with different FBG lengths for various FBG apodization functions at the central frequency of 193.1 THz. 
Dispatching the problems in implementing mobile payment services from consumer attitude perspective Hoang Thien Van; Vo Anh Tien; Huynh Cong Danh; Hoang-Sy Nguyen
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.pp590-597

Abstract

Due to the abundance of internet and e-commerce (electronic commerce), an excessive amount of data has been generated causing an overload of information to the current network infrastructure. As an attempt to solve this problem, there is a shift to mobile payment in the field of E-commerce. Thus, it is essential to study the adoption level of such service for global markets in general and the Vietnamese market in specific. In this paper, we study the consumers' attitude toward mobile payment, investigated with the theory of planned behavior (TPB) from three perspectives, namely the consumer innovativeness, perceived benefit, and perceived risk. Accordingly, there are six hypotheses proposed to study the consumers' attitude toward the service. Thanks to the structural equation modeling (SEM) method, a population of 250 Vietnamese mobile payment users was analyzed to confirm five out of the six hypotheses. It is drawn that the attitude toward the service is correlated positively with the innovativeness and the perceived benefit, while being correlated negatively with the perceived risk. Besides, the resulted model can elucidate approximately 49% the consumers' intention to reuse the mobile payment service.
Mobility models for next generation wireless mesh network Tsehay Admassu Assegie; Tamilarasi Suresh; R. Subhashni; Deepika M
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.pp379-384

Abstract

Wireless mesh network (WMN) is a new trend in wireless communication promising greater flexibility, reliability, and performance over traditional wireless local area network (WLAN). Test bed analysis and emulation plays an essential role in valuation of software defined wireless network and node mobility is the prominent feature of next generation software defined wireless network. In this study, the mobility models employed for moving mobile stations in software defined wireless network are explored. Moreover, the importance of mobility model within software defined wireless mesh network for enhancing the performance through handover-based load balancing is analyzed. The mobility models for the next generation software defined wireless network are explored. Furthermore, we have presented the mobility models in the mininet-Wi-Fi test bed, and evaluated the performance of Gauss Marko’s mobility model.
Energy audit: types, scope, methodology and report structure Pankaj Sharma; Surender Reddy Salkuti; Seong-Cheol Kim
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.pp45-52

Abstract

The objective of this paper is to study various methods adopted during the energy audit. Many countries are focusing on energy, not only enhancing the tenable power generation sources but also on utilizing the power more proficiently for economic utilization. The energy audit is an important parameter for all the developing and developed countries and they focus on energy efficiency, energy quality, and energy intensity. In the industrial, residential, and commercial sectors the top operating expense is found to be are material, machine, manpower, and energy. Identification of the energy-consuming sector is the prior attention to look for the energy-saving potential and quality improvement. Implementation of an energy audit can enhance the efficiency, quality of power, reduce the tariff of bills, and reduces the wastage of energy. The need for energy audits, different types of energy audits, various types of software used, and the energy audit report structure were presented in this paper.
Automated handwriting analysis based on pattern recognition: a survey Samsuryadi Samsuryadi; Rudi Kurniawan; Fatma Susilawati Mohamad
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.pp196-206

Abstract

Handwriting analysis has wide scopes include recruitment, medical diagnosis, forensic, psychology, and human-computer interaction. Computerized handwriting analysis makes it easy to recognize human personality and can help graphologists to understand and identify it. The features of handwriting use as input to classify a person’s personality traits. This paper discusses a pattern recognition point of view, in which different stages are described. The stages of study are data collection and pre-processing technique, feature extraction with associated personality characteristics, and the classification model. Therefore, the purpose of this paper is to present a review of the methods and their achievements used in various stages of a pattern recognition system. 
IoT and transparent solar cell based automated green house monitoring system for tomato plant cultivation Yus Rama Denny; Endi Permata; Adhitya Trenggono; Vaka Gustiono
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.pp18-27

Abstract

This study aimed to develop and test the feasibility of a smart greenhouse prototype media that is used as a planting medium with an automatic watering system. The method in this study was research and development using the waterfall model. In order to test the feasibility, the prototype was validated with material expert validators, media expert, and farmers. The questionnaire instrument was compiled based on Walker and Hess instrument. The results of the research found are as follows: the results of feasibility research by media experts has an average score of 4.35 with the category "very feasible", assessment by experts the material has an average score of 4.4 with the category "very feasible", and the assessment of the user has an average score of 4.06 with "feasible". The purposed controlled system of smart greenhouse and as a media for farmers was validated. Our results demonstrated that the smart greenhouse is suitable media to help farmers cultivating the tomatoes plant.
Air temperature prediction using different machine learning models Rana Muhammad Adnan; Zhongmin Liang; Alban Kuriqi; Ozgur Kisi; Anurag Malik; Binquan Li; Fatemehsadat Mortazavizadeh
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.pp534-541

Abstract

Air temperature is an essential climatic component particularly in water resources management and other agro-hydrological/meteorological activities planning This paper examines the prediction capability of three machine learning models, least square support vector machine (LSSVM), group method and data handling neural network (GMDHNN) and classification and regression trees (CART) in air temperature forecasting using monthly temperature data of Astore and Gilgit climatic stations of Pakistan. The prediction capability of three machine learning models is evaluated using different time lags input combinations with help of root mean square error (RMSE), the mean absolute error (MAE) and coefficient of determination (R2).statistical indicators. The obtained results indicated that the LSSVM model is more accurate in temperature forecasting than GMDHNN and CART models. LSSVM significantly decreases the mean RMSE of the GMHNN and CART models by 1.47-3.12% and 20.01-25.12% for the Chakdara and Kalam Stations, respectively.
Design and analysis of RNS-based sign detector for moduli set {2^n, 2^n - 1, 2^n + 1} Raj Kumar; Ram Awadh Mishra
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.pp62-70

Abstract

Magnitude comparison, sign detection and overflow detection are essential operations of residue number system (RNS) that are used in digital signal processing (DSP) applications. Moreover, sign detection attracts significant attention in RNS as it can also be used in division and magnitude comparison operations. However, these operations are not easy to perform in RNS. So, there is a need arise to propose a computationally advanced RNS based sign detector. This paper presents an area and power-efficient sign detection circuit for modulo  {2n - 1, 2n, 2n + 1} using mixed radix conversion technique. The proposed sign detector is constructed using a carry save adder (CSA), a modified parallel prefix adder and a carry-generation circuit. Based on the synthesized results using synopsys design compiler, the introduced design offers better results in terms of the area required and power consumption. Although, the speed will remain the same when compared to the recent sign detectors for the same moduli set.
Denoising of EEG signal based on word imagination using ICA for artifact and noise removal on unspoken speech Efy Yosrita; Rosida Nur Aziza; Rahma Farah Ningrum; Givary Muhammad
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.pp83-88

Abstract

The purpose of this research is to observe the effectiveness of independent component analysis (ICA) method for denoising raw EEG signals based on word imagination, which will be used for word classification on unspoken speech. The electroencephalogram (EEG) signals are signals that represent the electrical activities of the human brain when someone is doing activities, such as sleeping, thinking or other physical activities. EEG data based on the word imagination used for the research is accompanied by artifacts, that come from muscle movements, heartbeat, eye blink, voltage and so on. In previous studies, the ICA method has been widely used and effective for relieving physiological artifacts. Artifact to signal ratio (ASR) is used to measure the effectiveness of ICA in this study. If the ratio is getting larger, the ICA method is considered effective for clearing noise and artifacts from the EEG data. Based on the experiment, the obtained ASR values from 11 subjects on 14 electrodes amounted are within the range of 0,910 to 1,080. Thus, it can be concluded that ICA is effective for removing artifacts from EEG signals based on word imagination.

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