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Research on the Information Security Problems in Cloud Calculation's Environment Xia Hu; Min Zhou
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 12: December 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

With the development of technology, cloud calculation becomes a widely used technology and is regarded as the third IT revolution following the computers and the Internet. Then only after resolving its security issues, it is able to operate successfully. This paper at first introduces the concept and characteristics of cloud calculation and then elaborates the current situation of cloud calculation's security.Then it analyzes the security risks of cloud calculation. According to these risks, the solution is proposed. DOI: http://dx.doi.org/10.11591/telkomnika.v11i12.3612
Identification information sensors of robot systems Igor Parkhomey; Juliy Boiko; Oleksander Eromenko
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 3: June 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v14.i3.pp1235-1243

Abstract

At the present time, the complexity of identification is to find such a description, in which the image (information) of each class would have identified similar properties. The task is to make the transformed description includes the whole set of input images, united by the similarity class by the given ratio.Using the ordinates of an autocorrelation function is an inseparable shift in the center of gravity of an image, which leads to a change of such description.Nicest, the concept of an invariant description of information arises, this is an autocorrelation function, which is invariant to the description of any displacements of the image in the vertical and horizontal directions.The problem of finding an optimal decision rule arises, which, in a number of cases, can be constructed on the basis of a method, based on the definition of the maximum incomplete coefficient of similarity.Using this method, the solutions, that are almost unintelligible to the errors that arise due to the effects of interference, are found. Therefore, in increments k, this rule passes into the Bayes’ rule.
Hybrid Encryption Algorithm Based on Spatial and Gray Level Information Suolan Liu; Chen Chen; Yue Chen; Hongyuan Wang
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 3: September 2015
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i3.pp569-575

Abstract

Based on the analysis of the defect of traditional image scrambling methods, a new hybrid scrambling algorithm is proposed. It uses image’s spatial and gray level information. Comparative experiments show it has the advantages of easy implementation, large key space, and good scrambling effect by only one time scrambling instead of many times processing.
Key Technology of Agricultural Production and Market Information Matching in Big Data Era Shuo Wang; Shihong Liu
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 3: March 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

This article describes challenges faced by agricultural production and marketing in the era of big data, and then builds the agricultural market information matching platform based on HADOOP & NUTCH combining cloud computing technology, finally details its layers and key technologies, including the use of open source search engine to capture the whole network market information to build agricultural production and market data sources, users’ interest model and the combination of matching algorithm and HADOOP environment. The aim of this paper is to make the agricultural market information matching platform more suitable for Chinese agricultural production and marketing system in order to solve the bottleneck problems such as information overload, lack of storage space, scalability and efficiency of analysis and calculation. As a result, this thesis provides a useful reference and new strategy for analysis and mining of big data in agricultural production and marketing areas. DOI : http://dx.doi.org/10.11591/telkomnika.v12i3.4489  
Robust Security for Health Information by ECC with Signature Hash Function in WBAN G. Sridevi Devasena; S. Kanmani
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 1: July 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i1.pp256-262

Abstract

Wireless Body Area Networks (WBANs) are fundamental technology in health care that permits the information of a patient’s essential body parameters to be gathered by the sensors. However, the safety and concealment defense of the gathered information is a key uncertain problem. A Hybrid Key Management (HKM) scheme [13] is worked based on Public Key Cryptography (PKC)-authentication scheme. This scheme uses a oneway hash function to construct a Merkle Tree. The PKC method increase the computational complexity and lacking scalability. Additionally, it increases expensive computation, communication costs and delay. To overcome this problem, Robust Security for Protected Health Information by ECC with signature Hash Function in WBAN (RSP) is proposed. The system employs hash-chain based key signature technique to achieve efficient, secure transmission from sensor to user in WBAN. Moreover, Elliptical Curve Cryptography algorithm is used to verifies the authenticate sensor. In addition, it describes the experimental results of the proposed system demonstrate the efficient data communication in a network.
Dominance-based Matrix algorithm for Knowledge Reductions in Incomplete Fuzzy Information System Lixin Fan; Qiang Wu
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 12: December 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

In this paper，definitions of knowledge granulation and rough entropy are proposed based on dominance relations in incomplete fuzzy information system, and important properties are obtained. It can be found that using the definitions can measure uncertainty of an attribute set in the incomplete fuzzy information systems. A matrix algorithm for attributes reduction is acquired in the systems. An example illustrates the validity of this algorithm, and results of compared with other existing methods show that the algorithm is an efficient tool for data mining. DOI: http://dx.doi.org/10.11591/telkomnika.v11i12.3725
Evaluation Studies on Client Satisfaction Degree of Railway Statistic Information System Huawen Wu; Xingjun Shi; Chenyang Duan; Fuzhang Wang
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 10: October 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

To increase the accuracy and the efficacy of client satisfaction degree of railway statistic information system, we give an AHP-based comprehensive assessment about satisfaction degree of information system, hoping to solve problems about evaluation difficulties of multi-index, multi-criteria and multi-level. Since the conventional AHP-based method is affected by subjective factors, we develop an enhanced AHP method to decrease limitations of conventional methods. Our method, still based on expert scoring, perform cluster analysis of scoring data, apply the clustering method of Euclid Distance with Weight to eliminate scores with the largest divergence, and utilize the AHP method and Function of Weight Average to obtain weight of evaluation index, which is useful to improve the accuracy and efficacy and can enhance effects of the more pivotal evaluation index on results. Finally, we prove its rationality and reliability in an evaluation of client satisfaction degree of railway statistic information system. DOI: http://dx.doi.org/10.11591/telkomnika.v11i10.3409
Transient Stability Analysis of Grid-connected Wind Turbines with Front-end Speed Control via Information Entropy Energy Function Method Haiying Dong; Shuaibing Li; Shubao Li; Hongwei Li
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 1: January 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

According to the characteristics like time-consuming and can not be quantitatively analyzed of time domain simulation in power system transient stability analysis, a direct method using information entropy combined with transient energy function method is proposed in this paper to analyze the transient stability of wind power system equiped with front-end speed controlled wind turbines (FSCWT) with synchronous generators. In which, the system kinetic energy and potential energy are used as information source to makeup information entropy function, then, a theoretical analysis of system transient stability is conducted. Based on this, simulations are carried out in IEEE 5-machine 14-bus system compared with the time domain’s, which verified the consistency of information entropy energy function (IEEF) method and time domain analysis. Results show that it is more intuitively and effectively to use IEEF method for wind power system transient analysis equiped with FSCWT.DOI : http://dx.doi.org/10.11591/telkomnika.v12i1.3379
Human Presence Recognition in a Closed Space by using Cost-effective CO2 Sensor and the Information Gain Processing Method Kimio Oguchi; Ryoya Ozawa
Indonesian Journal of Electrical Engineering and Computer Science Vol 5, No 3: March 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v5.i3.pp549-555

Abstract

The recent rapid progress in ICT technologies such as smart/intelligent sensor devices, broadband/ubiquitous networks, and Internet of everything (IoT) has advanced the penetration of sensor networks and their applications. The requirements of human daily life, security, energy efficiency, safety, comfort, and ecological, can be achieved with the help of these networks and applications. Traditionally, if we want some information on, for example, environment status, a variety of dedicated sensors is needed. This will increase the number of sensors installed and thus system cost, sensor data traffic loads, and installation difficulty. Therefore, we need to find redundancies in the captured information or interpret the semantics captured by non-dedicated sensors to reduce sensor network overheads. This paper clarifies the feasibility of recognizing human presence in a space by processing information captured by other than dedicated sensors. It proposes a method and implements it as a cost-effective prototype sensor network for a university library. This method processes CO2 concentration, originally designed to check environment status. In the experiment, training data is captured with none, one, or two subjects. The information gain (IG) method is applied to the resulting data, to set thresholds and thus judge the number of people. Human presence (none, one or two people) is accurately recognized from the CO2 concentration data. The experiments clarify that a CO2 sensor in set in a small room to check environment status can recognize the number of humans in the room with more than 70 % accuracy. This eliminates the need for an extra sensor, which reduces sensor network cost.
Cyberbullying identification in twitter using support vector machine and information gain based feature selection Ni Made Gita Dwi Purnamasari; M. Ali Fauzi; Indriati Indriati; Liana Shinta Dewi
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i3.pp1494-1500

Abstract

Cyberbullying is one of the actions that violate the ITE Law where the crime is committed on social media applications such as Twitter. This action is difficult to detect if no one is reporting the tweet. Cyberbullying tweet identification aims to classify tweets that contain bullying. Classification is done using Support Vector Machine method where this method aims to find the dividing hyperplane between negative and positive class. This study is a text classification where more data is used, the more features are produced, therefore this research also uses Information Gain as feature selection to select features that are not relevant to the classification. The process of the system starts from text preprocessing with tokenizing, filtering, stemming and term weighting. Then perform the information gain feature selection by calculating the entropy value of each term. After that perform the classification process based on the terms that have been selected, and the output of the system is identification whether the tweet is bullying or not. The result of using SVM method is accuracy 75%, precision 70.27%, recall 86.66% and f-measure 77.61% on experiment maximum iteration = 20, λ = 0.5, γ = 0.001, ε = 0.000001, and C = 1. The best threshold of information gain is 90%, with accuracy 76.66%, precision 72.22%, recall 86.66% and f-measure 78.78%.

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