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Building student’s performance decision tree classifier using boosting algorithm
Farid Jauhari;
Ahmad Afif Supianto
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 3: June 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v14.i3.pp1298-1304
Student’s performance is the most important value of the educational institutes for their competitiveness. In order to improve the value, they need to predict student’s performance, so they can give special treatment to the student that predicted as low performer. In this paper, we propose 3 boosting algorithms (C5.0, adaBoost.M1, and adaBoost.SAMME) to build the classifier for predicting student’s performance. This research used 1UCI student performance datasets. There are 3 scenarios of evaluation, the first scenario was employ 10-fold cross-validation to compare performance of boosting algorithms. The result of first scenario showed that adaBoost.SAMME and adaBoost.M1 outperform baseline method in binary classification. The second scenario was used to evaluate boosting algorithms under different number of training data. On the second scenario, adaBoost.M1 was outperformed another boosting algorithms and baseline method on the binary classification. As third scenario, we build models from one subject dataset and test using onother subject dataset. The third scenario results indicate that it can build prediction model using one subject to predict another subject.
Badminton player detection using faster region convolutional neural network
Nur Azmina Rahmad;
Nur Anis Jasmin Sufri;
Nurul Hamizah Muzamil;
Muhammad Amir As'ari
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 3: June 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v14.i3.pp1330-1335
Nowadays, coaches and sport analyst are concerning about sport performance analysis through sport video match. However, they still used conventional method which is through manual observation of the full video that is very troublesome because they might miss some meaningful information presence in the video. Several previous studies have discussed about tracking ball movements, identification of player based on jersey color and number as well as player movement detection in various type of sport such as soccer and volleyball but not in badminton. Therefore, this study focused on developing an automated system using Faster Region Convolutional Neural Network (Faster R-CNN) to track the position of the badminton player from the sport broadcast video. In preparing the dataset for training and testing, several broadcast videos were converted into image frames before labelling the region which indicate the players. After that, several different trained Faster R-CNN detectors were produced from the dataset before tested with different set of videos to evaluate the detector performance. In evaluating the performance of each detector model, the average precision was obtained from precision recall graph. As a result, this study revealed that the detector successfully detects the player when the detector is being fed with more generalized dataset.
Design and implementation of modified multilevel sepic converter for PV based apllications
Arunkumari T;
I. Jagadeesh;
Indragandhi V
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 3: June 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v14.i3.pp1125-1133
In this manuscript, a DC-DC converter of modified multilevel sepic model with single switch is proposed here. The designed converter combines the voltage tripler circuit, which improves the voltage gain and reduces the voltage ripple of the system. Another feature of the designed converter is reduces the voltage stress and utilized for PV based applications. The operation of the designed converter in Continuous-Conduction Mode (CCM) is discussed. The converter boosts the PV input voltage of 30 V to 400 V output voltages. The efficiency attained by the designed converter is 94%. The Theoretical analysis of the designed converter is presented and it is done with MATLAB simulink. To analyse the performance of this DC-DC converter a model was developed and tested. From the experimental results obtained, it is analysed that the converter performs better and suitable for PV based application.
A novel index modulation scheme with impedance matching
Hye Yeong LEE;
Soo Young Shin
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 3: June 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v14.i3.pp1203-1209
Index modulation conveys more data given to indices of status of communication transmission item such as antenna and subcarrier. In this proposed system, we gave the index to the conditions of impedance matching or not. In the transmitter, antenna chooses one impedance according to the mapping table as active impedance. The receiver detects impedance index comparing of impedance between received signal and receivers. The proposed system improves not only transmitted information data by using impedance index but also spectral efficiency. In the simulation, Spectral Efficiency (SE) and Bit Error Rate (BER) were analyzed and compared to conventional modulation scheme.
Solving economic dispatch and unit commitment problem in smart grid system using eagle strategy based crow search algorithm
Rachid HABACHI;
Achraf Touil;
Abdellah Boulal;
Abdelkabir Charkaoui;
Abdelwahed Echchatbi
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 3: June 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v14.i3.pp1087-1096
The economic dispatch problem of power plays a very important role in the exploitation of electro-energy systems to judiciously distribute power generated by all plants. The Unit commitment problem (UCP) is mainly finding the minimum cost schedule to a set of generators by turning each one either on or off over a given time horizon to meet the demand load and satisfy different operational constraints. This research article integrates the crow search algorithm as a local optimizer of Eagle strategy to solve economic dispatch and unit commitment problem in smart grid system.
QoS hybrid uplink scheduler based on service type for M2M communications in LTE networks
Mariyam Ouaissa;
Abdallah Rhattoy
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 3: June 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v14.i3.pp1460-1470
The introduction of Machine-to-Machine (M2M) communications in cellular networks creates a new set of challenges because of the unique service requirements and features of M2M devices. One of these challenges is the management of radio resources, especially on the uplink because of the unfairness and poor performance that occurs when allocating resources to users. Long Term Evolution (LTE) and LTE-Advanced (LTE-A) are excellent candidates for supporting M2M communications because of their native IP connectivity and scalability for a variety of devices. Therefore, LTE schedulers should be able to meet the needs of M2M devices such as time constraints and specific Quality of Service (QoS) requirements. In this paper, these constraints are studied and analyzed, focusing on three schedulers; they are Round Robin (RR), First Maximum Expansion (FME) and Maximum Throughput (MT). These methods do not provide QoS to users who use different types of traffic flows. The solution proposed in this work is a hybrid model between two schedulers each of them is the best scheduling solution for the real-time service and the other for the non-real-time service, in order to meet QoS criteria maximizing throughput and minimizing packet loss. Video and voip were selected as real-time traffic and best effort for non-real time. The simulations results show that the proposed scheduler reaches the lowest Packet Loss Rate (PLR), delivering highest throughput and goodput among the other strategies.
Off-Line character recognition using an integrated DBSCAN-ANN scheme
Dhurgham Ali Mohammed;
Alaa Abdul Hussein Mezher;
Hayder Sabeeh Hadi
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 3: June 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v14.i3.pp1443-1451
Handwriting character recognition involves a high degree of variability and imprecision. For that, the main factor to judge the recognition accuracy is the technique that is used to extract the features. This paper developed a novel method for handwritten Arabic characters by combining the Density-Based Clustering method with statistical and morphological features. The first stage in recognition of handwritten character image has been done by binarization the image then applies noise removal techniques. The Density-Based Algorithm used to categorize and find any shape of clusters based on pixel information positions. This technique divided the image into characters. Each character will be decomposing into four regions from the centroid followed by feature extraction. These features include vertical and horizontal projections, upper and lower profile, rectangularity and orientation. The results of the present process will transfer to the Neural Network (NN) stage which generates a high level of correctness and accuracy by training. The testing results compared with two of state-of-art researches. The total accuracy of this proposed work observes a better recognition of characters.
Evaluation of gas fuel and biofuel usage in turbine
Dalya H. Al-Mamoori;
Mohanad H. Aljanabi;
Ali Assim Alobaidi;
Omar Muhammed Neda;
Zaid H. Al-Tameemi
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 3: June 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v14.i3.pp1097-1104
Modern gas turbines are a significant source for power generation and prime mover for marine propulsion. The depleting fossil fuel sources have provided a cue for broader implementation and usage of renewable energy. Biofuel has been touted as a substitute for natural gas to power gas turbines. To confirm the dependability and reliability of this attempt in a complex multi-domain system, for example, the gas turbine, the fuel system of the micro-gas turbine is designed and modelled using MATLAB Simulink. The model; simulates the; transient and steady state of a gas turbine’s nominal functional situations. Evaluations between the field data and; simulation outcomes validate a high degree of correspondence. The fuel system in the micro;-gas turbine simulation model is also optimized with the experimental data.
Reliability optimization of electrical distribution systems considering expenditures on maintenance and customer interruptions
K B Kela;
Bhavik N Suthar;
L D Arya
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 3: June 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v14.i3.pp1057-1064
In this paper, a methodology is proposed which shows enhancement of reliability by optimizing total reliability cost of electrical distribution systems. The total reliability cost consists of cost incurred by utility and customers both. An objective function in terms of failure rates and repair times i.e. primary reliability indices has been formulated which depicts both these costs . Hence, optimization of the objective function will give a balance between these costs with optimized values of primary reliability indices. This optimization has been done considering the constraints of achieving customer and energy based reliability indices below threshold/target values. The methodology has been applied on Roy Billinton Test System- Bus 2 (RBTS-2). The problem has been solved by applying Flower Pollination (FP) algorithm. A comparison has been made with the results obtained by Differential evolution (DE) algorithm also for the system considered.
Test-framework: performance profiling and testing web search engine on non factoid queries
Althaf Ali A;
Mahammad Shafi R
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 3: June 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v14.i3.pp1373-1381
Performance profiling and testing is one of the interesting topics in the big data management and Cloud Computing. In testing, we use test cases composed to different type of queries to evaluate the performance aspects of the information retrieval system for large scale information collection. This test scenarioperforms the evaluation ofretrieval accuracy for all kind of ambiguity and non factoid queries with result set as Training data. This stands difficult to evaluate the retrieval method in order to schedule or optimize the Recommendation and prediction technique of the IR method to the Real time queries. The Queries is considered as requirement specification which has to supply to search engine or web information provider applications for information or web page retrieval. In this paper, we propose a novel technique named as “Test Retrieval Framework“a performance profiling and testing of the web search engines on the information retrieved towards non factoid queries. In this technique, we apply expectation maximization algorithm as an iterative method to find maximum likelihood estimate.We discuss on the important aspects in this work based on Recommendation models integrating domain and web usage, Query optimization for navigational and Transactional queries, Query Result records.The Experimental results demonstrates the proposed technique outperforms of state of arts approaches in terms of set based measures like Precision, Recall and F measure and rank based measures like Mean Average Precision and Cumulative Gain.