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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 57 Documents
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Search results for , issue "Vol 12, No 1: October 2018" : 57 Documents clear
Paper Money Recognizer Using Feature Descriptor Nur Hadisukmana; Adri Yudianto
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 1: October 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i1.pp117-126

Abstract

People are still using paper money for daily transaction; this, however, will expose some difficulty for visually impaired people. Though they can still read the nominal value of the paper money by the other people or feel the tactile feature, they cannot depend upon others all the time and the tactile feature does not work well if the paper money is worn out. Some alternatives have been proposed and conducted. One of them is using money value recognition application. The application will recognize nominal value of paper money comparing the image of the paper with database. This process is using a feature extraction algorithm called ORB feature descriptor. It has been used for six (6) different types of currencies that are 5 most traded currencies and Indonesia currency and also for different types of nominals (bills).
Machine Learning with PySpark - Review Raswitha Bandi; J Amudhavel; R Karthik
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 1: October 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i1.pp102-106

Abstract

A reasonable distributed memory-based Computing system for machine learning is Apache Spark. Spark is being superior in computing when compared with Hadoop. Apache Spark is a quick, simple to use for handling big data that has worked in modules of Machine Learning, streaming SQL, and graph processing. We can apply machine learning algorithms to big data easily, which makes it simple by using Spark and its machine learning library MLlib, even this can be made simpler by using the Python API PySpark. This paper presents the study on how to develop machine learning algorithms in PySpark. 
A Modified Boltzmann Machine for Solving Distribution System Expansion Planning in Malaysia Siti Hajar Mohd Tahar; Shamshul Bahar Yaakob; Amran Ahmed
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 1: October 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i1.pp193-200

Abstract

This paper proposes an effective technique to solve Distribution System Expansion Planning (DSEP) problem by using the artificial neural network. The proposed technique will be formulated by using mean-variance analysis (MVA) approach in the form of mixed-integer quadratic programming problem. It consists of two layers neural network which combine Hopfield network and Boltzmann machine (BM) in upper and lower layer respectively named as Modified BM. The originality of the proposed technique is it will delete the unit of the second layer, which is not selected in the first layer in its execution. Then, the second layer is restructured using the selected units. Due to this feature, the proposed technique will improve time consuming and accuracy of solution. Referring to the case study demonstrated in this paper, the significance outputs obtained are the improvement in computational time and accuracy of solution provided. As the solution provided various of options, the proposed technique will help decision makers in solving DSEP problem. As a result, the performance of strategic investment planning in DSEP certainly enhanced.
Discrete Evolutionary Programming for Network Splitting Strategy: Different Mutation Technique N.Z. Saharuddin; Zainal Abidin; H. Mokhlis
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 1: October 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i1.pp261-268

Abstract

Network splitting is performed to prevent the power system network from blackout event during severe cascading failures. This action will split the power system network into few islands by disconnecting the proper transmission lines. It is very important to select the optimal splitting solution (transmission lines to be removed) to ensure that the implementation of network splitting does not cause the system to worsen. Therefore, this paper investigates two different mutation techniques; single-level and three-level mutation, utilized in Discrete Evolutionary Programming (DEP) optimization to find the optimal splitting solution following a critical line outage. Initial cutsets based heuristic technique is employed to help the convergence of the DEP optimization with minimal power flow disruptions as its fitness function. The techniques are validated using the IEEE 30 and IEEE 118-bus system. The results show that three-level mutation technique produces better optimal splitting solution as compared to single mutation technique.
Optimization of Dempster-Shafer’s Believe Value Using Genetic Algorithm for Identification of Plant Diseases Jatropha Curcas Triando Hamonangan Saragih; Wayan Firdaus Mahmudy; Yusuf Priyo Anggodo
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 1: October 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i1.pp61-68

Abstract

Jatropha curcas is a plant that can be used as a substitute for diesel fuel. Lack of knowledge of farmers and the limited number of experts and extension agents into the problem of dealing with the disease Jatropha curcas plant which resulted in lower quality of Jatropha curcas. Dempster-Shafer method can be a solution for decision making based on previous research. The difference in beliefs of every expert in seeing Jatropha diseases are important because Dempster-Shafer can not solve this problem. Optimization using genetic algorithms can solve this problem. Optimization of belief values using genetic algorithms can improve the accuracy of the results of this system are using Dempster-Shafer. On the results of this system provides the highest system accuracy value, opimization of belief values using genetic algorithms gives a more significant result than the use of Dempster-Shafer only.
Optimal Economic Load Dispatch using Multiobjective Cuckoo Search Algorithm Z.M. Yasin; N.F.A. Aziz; N.A. Salim; N.A. Wahab; N.A. Rahmat
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 1: October 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i1.pp168-174

Abstract

In this paper, Multiobjective Cuckoo Search Algorithm (MOCSA) is developed to solve Economic Load Dispatch (ELD) problem. The main goal of the ELD is to meet the load demand at minimum operating cost by determining the output of the committed generating unit while satisfying system equality and inequality constraints. The problem formulation is based on a multiobjective model in which the multiobjective are defined as fuel cost minimization and carbon emission minimization. MOCSA is based on the inspiration from the brooding parasitism of cuckoo species in nature. Three cases are considered to test the effectiveness of the proposed technique which are fuel cost minimization, carbon emission minimization and multiobjective function with fixed weighted sum. The effectiveness of the MOCSA’s performances are illustrated through comparative study with other techniques such as Multiobjective Genetic Algorithm (MOGA) and Multiobjective Particle Swarm Optimization (MOPSO) in terms of fitness functions. The proposed study was conducted on three generating unit system at various loading condition. The result proved that MOCSA provide better solution in minimizing fuel cost and carbon emission usage as compared to other techniques.
Faults Signature Extraction in Wind Farm Integrated Transmission Line Topology Osaji Emmanuel; Mohammad Lutfi Othman; Hashim Hizam; Muhammad M. Othman; Elhad Akar E.; Okeke Chidiebere A.; Nwagbara Samuel O.
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 1: October 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i1.pp246-253

Abstract

The integration of Renewable Green Energy Sources (RGES) like Wind Farm Generators (WFG), and Photo Voltaic (PV) systems into convention power system as a future solution to the increase in global energy demands, generation cost reduction, and limited climate impact. The innovation introduced protection compromise challenges in power system due to in-feeds fault current penetration from RGES on existing system, leading to an undesired trip of the healthy section of TL, equipment damages, and safety failure. A comparison study of extracted faults signature from two proposed Transmission Line (TL) network topologies with and without WFG integration, for onward fault identification, and classification model design. Descrete wavelet multiresolution Analysis (DWMRA) of extracted one-cycle fault signal signatures from 11 faults type’s scenarios in Matlab. Result demonstrated a unique fault signatures across all simulated faults scenarios harness for future work of an adaptive unit protection model for this new area of DG integration.
Star Coordinate Dimension Arrangement using Euclidean Distance and Pearson Correlation Noor Elaiza Abdul Khalid; Izyan Izzati Kamsani
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 1: October 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i1.pp348-355

Abstract

Star Coordinate (SC) is a circular visualization technique that maps k-dimensional data. Its interactive features allow user to manipulate projections to search for hidden information. Without prior knowledge of relationship between dimensions users will be blindly searching for clusters. This paper proposes dimension rearrangement using Euclidean Distance and Pearson Correlations to reveal the clusters in SC. The methodology consists of four phases; Calculate the distance between individual attributes against a dependent attribute using Euclidean distance; Pearson correlation is used to obtain the correlation data attributes; Sort the correlation values in ascending order; finally, attributes table are reordered with the positive values to the right and negative values to the left according to the correlation value. The resulting tables are applied to produce the SC. This method is successful in producing clusters that makes it easier for the users to further manipulate the SC for their data analysis.
Random Forest Approach for Sentiment Analysis in Indonesian Language M. Ali Fauzi
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 1: October 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i1.pp46-50

Abstract

Sentiment analysis become very useful since the rise of social media and online review website and, thus, the requirement of analyzing their sentiment in an effective and efficient way. We can consider sentiment analysis as text classification problem with sentiment as its categories. In this study, we explore the use of Random Forest for sentiment classification in Indonesian language. We also explore the use of bag of words (BOW) features with some term weighting methods variation such as Binary TF, Raw TF, Logarithmic TF and TF.IDF. The experiment result showed that sentiment analysis system using random forest give good performance with average OOB score 0.829. The result also depicted that all of the four term weighting method has competitive result. Since the score difference is not very significant, we can say that the term weighting method variation in study has no remarkable effect for sentiment analysis using Random Forest.
802.11p Profile Adaptive MAC Protocol for Non-Safety Messages on Vehicular Ad Hoc Networks Shamsul J Elias; M. Elshaikh; M. Yusof Darus; Jamaluddin Jasmis; Angela Amphawan
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 1: October 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i1.pp208-217

Abstract

Vehicular Ad hoc Networks (VANET) play a vital Vehicle to Infrastructure (V2I) correspondence frameworks where vehicle are convey by communicating and conveying data transmitted among each other. Because of both high versatility and high unique network topology, congestion control should be executed distributedly. Optimizing the congestion control in term of delay rate, packet delivery ratio (PDR) and throughput could limit the activity of data packet transmissions. These have not been examined altogether so far – but rather this characteristic will be fundamental for VANET system execution and network system performance. This paper exhibits a novel strategy for congestion control and data transmission through Service Control Channel (SCH) in VANET. The Taguchi strategy has been connected in getting the optimize value of parameter for congstion control in highway environment. This idea lessens the pointless activity of data transmission and decreases the likelihood of congested in traffic in view of execution for measuring the delay rate, packet delivery ratio (PDR) and throughput. The proposed execution performance is estimated with the typical VANET environment in V2I topology in highway driving conditions and the simulation results demonstrate and enhance network execution performance with effective data transmission capacity.

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