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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 65 Documents
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Search results for , issue "Vol 18, No 1: April 2020" : 65 Documents clear
Forecasting rupiah exchange rate with learning vector quantization neural network Linawati Linawati; Made Sudarma; I Putu Oka Wisnawa
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i1.pp24-31

Abstract

The classification technique and data forecasting will probably be one of the techniques that will often be needed in handling or managing big data. So, from that the author analyzes the possible development of the existing algorithms. The purpose is to find possibilities in the use of reliable algorithms in a particular field, then can be adopted and implemented to develop forecasting techniques in the future. Based on these considerations, the authors conducted experiments by applying LVQNN to conduct shortterm forecasting on daily period of the Rupiah exchange rate. The literature that is used as a reference is the discovery of architectural data classification processes that resemble forecasting techniques. So, when there is a combination of Rupiah exchange histories, it is possible to find these combinations into certain classes based on predetermined parameters and historical data combination data and forecast values in the past. In this research the factors chosen as indicators that affect the Rupiah exchange rate are the amount of exports, the amount of imports, the inflation rate and also the world oil price. In this research the highest accuracy value in the testing process for the population reached 99.0991%. The increase in the percentage value of forecasting accuracy is influenced by the composition of the data. In this study the formation of data composition is influenced by distinct data. The selection of parameters which become distinct claused determines how the composition of the data will be formed. If the composition of the data is not correct, the test results will not be good. If the number of weights vector is smaller than the input data, the forecasting accuracy will decrease. Because the weight vector cannot represent data combinations that used during training or testing.
Blockchain technology opportunities in Kurdistan, applications and challenges Hilmi Abdullah; Ali Hikmat Ibrahim
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i1.pp405-411

Abstract

Recently, the blockchain technology has received a vast popularity because it brought revolutionary changes to some industries due to the fact that this technology enables the implementation of secure, decentralized and trustworthy applications. Moreover, this technology has many advantages over centralized systems such as immutability and transparency. The most common application of the blockchain technology is the Bitcoin cryptocurrency, which provides a method of transferring money in a secure way without the involvement of a central authority. In addition to the Bitcoin, there are other applications based on the blockchain technology in a variety of sectors and industries such as governance, healthcare and supply chain. In this paper, we discuss blockchain applications that can be implemented in Kurdistan and we highlight their opportunities and challenges.
Design and simulation of a normalized fuzzy logic controller for the quadruple-tank process Wameedh Riyadh Abdul-Adheem
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i1.pp227-234

Abstract

Industrial processes include multivariable systems and nonlinearities. These conditions must be effectively controlled to ensure a stable operation. A proportional–integral–derivative controller and other classical control techniques provide simple design tools to designers, but cannot accommodate nonlinearities in industrial processes. In this study, the quadruple-tank process, which is one of the most widely used processes in the chemical industry, was selected as the research object.  To examine this process, a fuzzy logic controller, instead of an exact mathematical model, was proposed to ensure the reliability of the experience. A modification was proposed to facilitate the design process. To check the validity of the proposed controller, it was compared with the conventional proportional–integral controller. The former exhibited acceptable performance. Industrial processes include multivariable systems and nonlinearities. These conditions must be effectively controlled to ensure a stable operation. A proportional–integral–derivative controller and other classical control techniques provide simple design tools to designers, but cannot accommodate nonlinearities in industrial processes. In this study, the quadruple-tank process, which is one of the most widely used processes in the chemical industry, was selected as the research object.  To examine this process, a fuzzy logic controller, instead of an exact mathematical model,was proposed to ensure the reliability of the experience. A modification was proposed to facilitate the design process. To check the validity of the proposed controller, it was compared with the conventional proportional–integral controller. The former exhibited acceptable performance.
Glaucoma detection of retinal images based on boundary segmentation Noraina Alia Zainudin; Ain Nazari; Mohd Marzuki Mustafa; Wan NurShazwani Wan Zakaria; Nor Surayahani Suriani; Wan Nur Hafsha Wan Kairuddin
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i1.pp377-384

Abstract

The rapid growth of technology makes it possible to implement in immediate diagnosis for patients using image processing. By using morphological processing and adaptive thresholding method for segmentation of optic disc and optic cup, various sizes of retinal fundus images captured through fundus camera from online databases can be processed. This paper explains the use of color channel separation method for pre-processing to remove noise for better optic disc and optic cup segmentation. Noise removal will improve image quality and in return help to increase segmentation standard. Then, morphological processing and adaptive thresholding method is used to extract out optic disc and optic cup from fundus image. The proposed method is tested on two publicly available online databases: RIM-ONE and DRIONS-DB. On RIM-ONE database, the average PSNR value acquired is 0.01891 and MSE is 65.62625. Meanwhile, for DRIONS-DB database, the best PSNR is 64.0928 and the MSE is 0.02647. In conclusion, the proposed method can successfully filter out any unwanted noise in the image and are able to help clearer optic disc and optic cup segmentation to be performed.
Higher performance and lower complexity turbo decoding scheme for 4G-LTE using unpunctured turbo trellis-coded modulation Elarbi Abderraouf; Abdesselam Bassou; Mohamed Rida Lahcene Rida Lahcene
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i1.pp351-360

Abstract

Thanks to the success of smart phones and mobile-ready laptops, data traffic has recently grown exponentially, and the demand for mobile data has risen very dramatically. These requests in large capacity can only be satisfied by a high efficiency and a very good optimization of the infrastructures of the mobile networks, while taking into account the constraints which are the power, bandwidth and a limited complexity. The task of developing mobile technologies has also evolved from a national or regional focus to a complex and growing mission, supported by global standards development organizations such as 3GPP (3rd Group Partnership Project). Through this research, we present everything related to the simulation of the 4G mobile network system (LTE), which can provide high data flow with good quality, through three model channels known as (EPA, EVA, ETU). In this work we focus on the block ‘iterative decoding channel encoder’ in the LTE system, where the iterative channel coding called ‘Turbo-code’ (TC) is substituted by the iterative coding channel called ‘Unpunctured Turbo Trellis-coded Modulation’ (UTTCM). The simulation results showed that with less decoding complexities, UTTCM's LTE system gives good performance (in terms of BER).
Optimal tuning of PI controller using genetic algorithm for wind turbine application Yamina Belgaid; M’hamed Helaimi; Rachid Taleb; Mohammed Benali Youcef
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i1.pp167-178

Abstract

Nowadays, wind turbine energy has an increased importance in electrical power applications since when it is considered as an essential inexhaustible and broadly available energy resource. An aerogenerator is a device that transforms a part of the kinetic energy of the wind into available mechanical energy on a transmission shaft, and then into electrical energy through a generator, which is in our case a dual power asynchronous machine. An important characteristic of a wind turbine is that the avail, able maximum power is provided only in a single given operating point, called Maximum Power Point. Many classical methods and controllers have been widely developed and implemented to track the maximum power point. Among drawbacks of a classical PI controller is that its parameters are not constant, these conventional control laws may be are insufficient because they are not robust, especially when the accuracy requirements and other dynamic characteristics of the system are strict. The new idea in this paper is to introduce the Genetic Algorithms theory into the controlstrategy that used inthe conversion chain of the wind turbine, in order to improve stability. Simulation results approve that the application of Genetic Algorithms to the PI regulator, minimize or eliminate the drawbacks of the classical PI regulator, and greatly promote the efficiency and stability of the wind turbine systems.
A multi-levels RNG permutation Ammar Khaleel Abdulsadah; Abdullah Aziz Lafta; Mohammad Dosh
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i1.pp412-419

Abstract

The paper proposes a new general method for producing a multilevel permutation functioning as an m-tree traversal. It is composed of two basic steps: a random number generator of period length equal m to determine which child to traverse, and recursive permutation in which permutated the subtree if found. The test results proved that the suggested method of permutation is successful depending on the correlation measure.
Simulation modeling for heart attack patient by mapping cholesterol level Jossy P George; Suhas M Gaikwad
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i1.pp16-23

Abstract

Cholesterol is a complex structural material made up of four-fused hydrocarbon rings. There is a hydrocarbon tail linked at one end of the structure, while the hydroxyl group linked to each other on the other end. To one end of the structure, a hydrocarbon tail linked and to the other end, a hydroxyl group linked to each other. High cholesterol level is one among the major risk factors of a heart attack. It is feasible to compute and control the cholesterol level of a cardiovascular patient by making use of intended Mathematical modeling in System Dynamics (S.D.). Moreover, by simulating proposed set of equations for a heart attack patient, recovery accomplished at a faster pace. Because of S.D., a substantial amount of reduction in the patient's Cardiovascular Disease achieved by control over the sterol level of the heart patient. This simulation modeling is an attempt made in translational research domain and is useful in the healthcare industry health care industry. It will minimize the risk of heart stroke and maintain a healthy life.
Swarm intelligent hyperdization biometric Israa Mohammed Alhamdani; Yahya Ismail Ibrahim
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i1.pp385-395

Abstract

At the last decade the importance of biometrics has been clearly configured due to its important in the daily life that starts from civil applications with security and recently terrorizing. A Footprint recognition is one of the effective personal identifications based on biometric measures. The aim of this research is to design a proper and reliable left human footprint biometrics system addressed (LFBS). In addition, to create a human footprint database which it is very helpful for numerous use such as during authentication. The existing footprint databases were very rare and limited. This paper presents a sturdy combined technique which merges between Image Processing with Artificial Intelligent technique via Bird Swarm Optimization Algorithm (BSA) to recognize the human footprint. The use of (BSA) enhance the performance and the quality of the results in the biometric system through feature selection. The selected features was treated as the optimal feature set in standings of feature set size. The visual database was constructed by capturing life RGB footprint images from nine person with ten images per person. The visual dataset images was pre-processed by successive operations. Chain Code is used with footprint binary image, then statistical features which represent the footprint features. These features were extracted from each image and stored in Excel file to be entered into the Bird Swarm Algorithm. The experimental results show that the proposed algorithm estimates, excellent results with a smaller feature set in comparison with other algorithms. Experimental outcomes show that our algorithm achieves well-organized and accurate result about 100% accuracy in relation with other papers on the same field.
Segmentation of the human body based on frequency of human electromagnetic radiation Siti Zura A. Jalil; Siti Armiza Mohd Aris; Nurul Aini Bani; Mohd Nabil Muhtazaruddin; Sahnius Usman
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i1.pp268-275

Abstract

This paper discusses the body segment recognition based on human electromagnetic radiation frequency. Twenty-three points of human electromagnetic radiation are studied experimentally from thirty-three healthy human subjects. Three human body segments are considered, namely Left, Right and Chakra. For the purpose of recognition, k-Nearest Neighbor (KNN) algorithm is used to classify the segments of the human body. Then, the performances of classification are determined based on the accuracy and Receiving Operating Characteristic (ROC) analysis. It is found that the proposed technique accurately classifies the body segments with 100% accuracy, thus suggest that the proposed technique is significant to classify human body segments.

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