Chanintorn Jittawiriyanukoon
Assumption University

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Journal : Indonesian Journal of Electrical Engineering and Computer Science

Performance evaluation of listwise deletion for impaired datasets in multiple regression-based prediction Chanintorn Jittawiriyanukoon
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 2: August 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i2.pp1009-1018

Abstract

Multiple Regression-Based Prediction (MRBP) is an emerging calculation to or analysis technique cope with the future by compiling the history of data. The MRBP characteristic will include an approximation for the associations between physical observations and predictions. MRBP is a predictive model, which will be an important source of knowledge in terms of an interesting trend to be followed in the future. However, there is impairment in the MRBP dataset, wherein each form of missing and noisy data has caused an error and is unavailable further analysis. To overcome this unavailability, so that the data analytics can be moved on, two treatment approaches are introduced. First, the given dataset is denoised; next, listwise deletion (LD) is proposed to handle the missing data. The performance of the proposed technique will be investigated by dealing with datasets that cannot be executed. Employing the Massive Online Analysis (MOA) software, the proposed model is investigated, and the results are summarized. Performance metrics, such as mean squared error (MSE), correlation coefficient (COEF), mean absolute error (MAE), root mean squared error (RMSE), and the average error percentage, are used to validate the proposed mechanism. The proposed LD projection is confirmed through actual values. The proposed LD outperforms other treatments as it only requires less state space, which reflects low computation cost, and proves its capability to overcome the limitation of analysis.
Evaluation of computer network security using attack undirected geography Chanintorn Jittawiriyanukoon
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 3: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i3.pp1508-1514

Abstract

To secure a wealth of data traversing the computer network at your fingertips is compulsory. But when attack arises at various parts of the network it is difficult to protect, especially when each incident is investigated separately. Geography is a necessary construct in computer networks. The analytics of geography algorithms and metrics to curate insight from a security problem are a critical method of analysis for computer systems. A geography based representation is employed to highlight aspects (on a local and global level) of a security problem which are Eigenvalue, eccentricity, clustering coefficient and cliques. Network security model based on attack undirected geography (AUG) is familiarized. First, analysis based upon association rules is presented then the attack threshold value is set from AUG. The probability of an individual attack edge and associated network nodes are computed in order to quantify the security threat. The simulation is exploited to validate that results are effective.
Performance evaluation of proposed load balancing algorithm with unstable concurrent programs Chanintorn Jittawiriyanukoon
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.pp1452-1459

Abstract

IoT is the succeeding cohort of the digital computing environment. A swift progression in the IoT deployment and its applications are on the rise. Improving load balancing mechanisms induces healthier performance of the internet based computing as higher number of users can be comfortable. Implementing full services for tasks with unstable concurrency is an uphill process. One of the encounters allied with this administration is the task partition among the applications, regularly referred as concurrent programs. Through load balancing not only resources are equally utilized but also concurrent job’s response time can be promoted. Therefore, in this paper the widely used load balancing algorithms are investigated and yet the proposed algorithm is introduced. Simulation is employed in order to compare the performance metrics such as mean queue length, utilization and throughput between the recommended and existing algorithms. The proposed algorithm confirms the load balancing and outperforms when processing unstable concurrent programs.