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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 52 Documents
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Search results for , issue "Vol 11, No 3: September 2018" : 52 Documents clear
Simulation Model on Movement of Goods in Sea Freight for Small and Medium Enterprise Zirawani Baharum; Muhammad Hanif; Muhammad Imran Qureshi; Syazwa Nabila Mohd Raidzuan; Hairulnizam Mahdin
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i3.pp1214-1222

Abstract

Sea transportation is one of the major transportation in the scope of transport industry and plays important role towards the growth of performance in the industry that involves the movement of good (MOG). With the crucial operations, it is also essential to concern about the employee’s welfare, such as long working hours that occurred due to non-systematic procedure for the MOG. The long working hours been potentitially impact to the psychological factors of works stress and physical and health effects. Therefore, this research is important to be studied in order to develop the simulation model on MOG in sea freight for small and medium-sized enterprises (SMEs), effectively and efficiency. Initially, this research is startup by defining all existed activities with the duration as required. Subsequently, the business model of MOG in sea freight is developed according to the case study in order to develop the simulation model. This research is give a guide for future research towards providing a well-computer-based by applying the decision support system, especially to manage and control the movement of goods in sea freight.
The Fuzzy Inference System with Least Square Optimization for Time Series Forecasting Samingun Handoyo; Marji Marji
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i3.pp1015-1026

Abstract

The rule base on the fuzzy inference system (FIS) has a major role since the output generated by the system is highly dependent on it. The rule base is usually obtained from an expert but in this study proposed the rule base generated based on input-output data pairs with generating rule bases using lookup table scheme, then consequent part of each rule optimized with ordinary least square(OLS), so finally formed rule base from model FIS Takagi-Sugeno orde zero. The exchange rate dataset of EURO to USD is used for the development and validation of the system. In this study, 12 FISs were developed from a combination of linguistic values of n = 3,5,7, 9 with the number of lag (k) assumed to have an effect on output for k = 2,3,5. In training data, values R2 ranged between 0.989 and 0.993, MAPE values ranged between 0.381% and 0.473% where the FIS with the combination of n = 9 and k = 5 has the best performance. In the testing data, values R2 ranged between 0.203 and 0.7858, MAPE values ranged between 0.5136% and 0.9457% where FIS n = 3 and k = 2 perform best.
FPGA Implementation of a Novel Gaussian Filter Using Power Optimized Approximate Adders Jamshid M Basheer; Murugesh V
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i3.pp1048-1059

Abstract

Smoothing filters are essential for noise removal and image restoration. Gaussian filters are used in many digital image and video processing systems. Hence the hardware implementation of the Gaussian filter becomes a reliable solution for real time image processing applications. This paper discusses the implementation of a novel Gaussian smoothing filter with low power approximate adders in Field Programmable Gate Array (FPGA). The proposed Gaussian filter is applied to restore the noisy images in the proposed system. Original test images with 512x512 pixels were taken and divided in to 4x4 blocks with 256x256 pixels. The proposed technique has been applied and the performance metrics were measured for various simulation criteria. The proposed algorithm is also implemented using approximate adders, since approximate adders had been recognized as a reliable alternate for error tolerant applications in circuit based metrics such as power, area and delay where the accuracy may be considered for trade off.
Signal Processing in Telecommunications with Forward Correction of Errors Juliy Boiko; Oleksander Eromenko
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i3.pp868-877

Abstract

The development of mechanisms of increase efficiency of frequency-shift keying signals processing in telecommunications using algorithms of noise immunity channel coding in obstacle effect conditions is held in the article. The synthesis of the frequency-shift keying signal processing unit accounting intersymbol communication which is inherent for such signals with continuous phase is held. The conditions of the compromise implementation in the telecommunication information transmission channel with frequency shift keying and error correction coding for setting the optimal encoding rate in the range of the bandwidth of the information transmission system are explored. Linear cyclic codes Bose-Chaudhuri-Hocquenghem (BCH) are used for studying. By means of Matlab the article focuses on the definition of energetic benefit compared to uncoded system in case of equality of the bandwidth of the information transmission system with coding and without coding.
The Factors Affecting on Managing Sensitive Data in Cloud Computing Haifaa Jassim Muhasin; Rodziah Atan; Marzanah A. Jabar; Salfarina Abdullah
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i3.pp1168-1175

Abstract

Cloud computing represents the most important shift in computing and information technology (IT). However, security and privacy remain the main obstacles to its widespread adoption. In this research we will review the security and privacy challenges that affect critical data in cloud computing and identify solutions that are used to address these challenges. Some questions that need answers are: (a) User access management, (b) Protect privacy of sensitive data, (c) Identity anonymity to protect the Identity of user and data file. To answer these questions, a systematic literature review was conducted and structured interview with several security experts working on cloud computing security to investigate the main objectives of proposed framework, a pilot study by using a structured questionnaire was conducted. Framework using multilevel to enhance management information system on sensitive data in cloud environment.
An Improved Flexible Partial Histogram Bayes Learning Algorithm Haider O. Lawend; Anuar Muad; Aini Hussain
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i3.pp975-986

Abstract

This paper presents a proposed supervised classification technique namely flexible partial histogram Bayes (fPHBayes) learning algorithm. In our previous work, partial histogram Bayes (PHBayes) learning algorithm showed some advantages in the aspects of speed and accuracy in classification tasks. However, its accuracy declines when dealing with small number of instances or when the class feature distributes in wide area. In this work, the proposed fPHBayes solves these limitations in order to increase the classification accuracy. fPHBayes was analyzed and compared with PHBayes and other standard learning algorithms like first nearest neighbor, nearest subclass mean, nearest class mean, naive Bayes and Gaussian mixture model classifier. The experiments were performed using both real data and synthetic data considering different number of instances and different variances of Gaussians. The results showed that fPHBayes is more accurate and flexible to deal with different number of instances and different variances of Gaussians as compared to PHBayes.
Comparative Performance of Machine Learning Algorithms for Cryptocurrency Forecasting Nor Azizah Hitam; Amelia Ritahani Ismail
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i3.pp1121-1128

Abstract

Machine Learning is part of Artificial Intelligence that has the ability to make future forecastings based on the previous experience. Methods has been proposed to construct models including machine learning algorithms such as Neural Networks (NN), Support Vector Machines (SVM) and Deep Learning. This paper presents a comparative performance of Machine Learning algorithms for cryptocurrency forecasting. Specifically, this paper concentrates on forecasting of time series data. SVM has several advantages over the other models in forecasting, and previous research revealed that SVM provides a result that is almost or close to actual result yet also improve the accuracy of the result itself. However, recent research has showed that due to small range of samples and data manipulation by inadequate evidence and professional analyzers, overall status and accuracy rate of the forecasting needs to be improved in further studies. Thus, advanced research on the accuracy rate of the forecasted price has to be done.
Advanced Optimal For Three Phase Rectifier in Power Electronic System Salam Waley Shneen
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i3.pp821-830

Abstract

Interest in the power electronic system which used in many applications is increasing day by day. So, many researchers have focused on the analyses, design and control of these systems. In this study, Optimal for Three Phase Rectifier in Power Electronic System control strategy has been proposed for PSO-PI  fuzzy logic controller (FLC) based Three Phase Rectifier in Power Electronic System. Proposed Power Electronic System(PES) consists of input, isolation and output stages. In order to test dynamic performance of PSO-PI  based PES, simulation study was carried out by MATLAB/Simulink. The results obtained from the PSO-PI  based PES are not only superior in the rise time, settling time and overshoot but can prevent from voltage and has improved power quality.
Review of Advancements in Multi-tenant Framework in Cloud Computing K Suresh; R Jagadeesh Kannan
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i3.pp1102-1108

Abstract

As the cloud computing is gaining more user base the problem of simultaneously catering computational resources to multitude of users or their application is on rise. It remains a critical problem and pose hindrance in scalability of cloud computing. Thus, in order to layout the proper solution for the mentioned problem; it is necessary to sum up a proper knowledge based of the existing solution, there drawbacks and a detail analysis of its performances. In this study we present a review of multi-tenant frameworks and approaches used in the industry which reaps advantages to facilitate multi-tenancy.
An Effective Pre-Processing Phase for Gene Expression Classification Choon Sen Seah; Shahreen Kasim; Mohd Farhan Md Fudzee; Mohd Saberi Mohamad; Rd Rohmat Saedudin; Rohayanti Hassan; Mohd Arfian Ismail; Rodziah Atan
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i3.pp1223-1227

Abstract

A raw dataset prepared by researchers comes with a lot of information. Whether the information is usefull or not, completely depends on the requirement and purposes. In machine learning, data pre-processing is the very initial stage. It is a must to make sure the dataset is totally suitable for the requirement. In significant directed random walk (sDRW), there are three steps in data pre-processing stage. First, we remove unwanted attributes, missing value and proper arrangement, followed by normalization of the expression value and lastly, filtering method is applied. The first two steps are completed by Bioconductor package while the last step is works in sDRW.

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