Garuda - Garba Rujukan Digital

Article Per Year (5 Year)

All

International Journal of Electrical and Computer Engineering

IJECE
Website

Published by Institute of Advanced Engineering and Science

ISSN : 20888708 EISSN : 27222578 DOI : -

Core Subject : Science, Engineering,

Computer Science & IT Electrical & Electronics Engineering

International Journal of Electrical and Computer Engineering (IJECE, ISSN: 2088-8708, a SCOPUS indexed Journal, SNIP: 1.001; SJR: 0.296; CiteScore: 0.99; SJR & CiteScore Q2 on both of the Electrical & Electronics Engineering, and Computer Science) is the official publication of the Institute of Advanced Engineering and Science (IAES). The journal is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication and computer engineering from the global world.

Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)

Articles 128 Documents

1 2 3 4 5

Search results for , issue "Vol 9, No 6: December 2019" : 128 Documents clear

An accurate pattern classification for empty fruit bunch based on the age profile of oil palm tree using neural network Wafi Aziz; Afif Kasno; Nurkamilia Kamarudin; Zaidi Tumari; Shahrieel Aras; Herdy Rusnandi; Kamal Musa
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 6: December 2019
Publisher : Institute of Advanced Engineering and Science

This paper proposes an efficient method for pattern classification system of empty fruit bunch (EFB) by using a neural network technique. The main advantage of this method is the accuracy and speed of algorithm such that it can be computed rapidly with the proposed system. To test the effectiveness of the proposed method, 120 of EFB’s data with different ages and length that been obtained from Malaysian Palm Oil Board (MPOB) are use in the pattern classification process. In addition, there are three classes of EFB in this system, which are Class 1 (less than 7 year old), Class 2 (8 to 17 year old) and Class 3 (more than 17 year old). It is envisaged that the proposed method is very useful in classifying the EFB and 90% of the sample parameters are successfully classified to its class.

Image multiplexing using residue number system coding over MIMO-OFDM communication system Mohamed Ibrahim Youssif; Amr ElSayed Emam; Mohamed Abd ElGhany
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 6: December 2019
Publisher : Institute of Advanced Engineering and Science

Image transmission over Orthogonal Frequency-Division Multiplexing (OFDM) communication system is prone to distortion and noise due to the encountered High-Peak-to-Average-Power-Ratio (PAPR) generated from the OFDM block. This paper studies the utilization of Residue Number System (RNS) as a coding scheme for digital image transmission over Multiple-Input-Multiple-Output (MIMO) – OFDM transceiver communication system. The use of the independent parallel feature of RNS, as well as the reduced signal amplitude to convert the input signal to parallel smaller residue signals, enable to reduce the signal PAPR, decreasing the signal distortion and the Bit Error Rate (BER). Consequently, improving the received Signal-to-Noise Ratio (SNR) and enhancing the received image quality. The performance analyzed though BER, and PAPR. Moreover, image quality measurement is achieved through evaluating the Mean Squared Error (MSE), Peak Signal to Noise Ratio (PSNR), and the correlation values between the initial and retrieved images. Simulation results had shown the performance of transmission/reception model with and without RNS coding implementation.

Optimizing the performance of photovoltaic cells IBC (contact back interdigitated) by numerical simulation Nadjat Benadla; Kheireddine Ghaffour
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 6: December 2019
Publisher : Institute of Advanced Engineering and Science

Solar energy is the most widely shared and abundant source all over the world. This kind of energy is exploited to produce electricity directly by the solar photovoltaic cell. Indeed, silicon photovoltaic cells are the most widely spread technology. In the present article, we reported a numerical simulation of the interdigitated back contact (IBC) solar cell in order to obtain a higher conversion efficiency. The structure was realized on a p-type multi-crystalline silicon substrate, a p+ type amorphous silicon FSF, an n- type amorphous silicon based emitter, and a p- type BSF. The position of the emitter and the BSF were interdigitated and covered with ohmic contacts. The numerical simulation was carried out by SILVACO software under the Atlas module. The surface of structure was of a value of 10 cm2 under illumination AM1.5g. We studied the effect of the geometrical and the physical parameters of the structure with IBC on the performance of the cell. The optimum obtained conversion efficiency was 20.83%; this result confirms the potential of the heterojunction silicon technology.

Design and implementation of a three dimensions (3D) printer for modeling and pre-manufacturing applications Ghazi Qaryouti; Abdel Rahman Salbad; Sohaib A. Tamimi; Anwar Almofleh; Wael A. Salah; Qazem Jaber
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 6: December 2019
Publisher : Institute of Advanced Engineering and Science

The three-dimensional (3D) printing technologies represent a revolution in the manufacturing sector due to their unique characteristics. These printers arecapable to increase the productivitywithlower complexity in addition tothe reduction inmaterial waste as well the overall design cost prior large scalemanufacturing.However, the applications of 3D printing technologies for the manufacture of functional components or devices remain an almost unexplored field due to their high complexity. In this paper the development of 3D printing technologies for the manufacture of functional parts and devices for different applications is presented. The use of 3D printing technologies in these applicationsis widelyused in modelingdevices usually involves expensive materials such as ceramics or compounds. The recent advances in the implementation of 3D printing with the use of environmental friendly materialsin addition to the advantages ofhighperformance and flexibility. The design and implementation of relatively low-cost and efficient 3D printer is presented. The developed prototype was successfully operated with satisfactory operated as shown from the printed samples shown.

RB-Bayes algorithm for the prediction of diabetic in Pima Indian dataset Rajni Rajni; Amandeep Amandeep
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 6: December 2019
Publisher : Institute of Advanced Engineering and Science

Diabetes is a major concern all over the world. It is increasing at a fast pace. People can avoid diabetes at an early stage without any test. The goal of this paper is to predict the probability of whether the person has a risk of diabetes or not at an early stage. This would lead to having a great impact on their quality of human life. The datasets are Pima Indians diabetes and Cleveland coronary illness and consist of 768 records. Though there are a number of solutions available for information extraction from a huge datasets and to predict the possibility of having diabetes, but the accuracy of their mining process is far from accurate. For achieving highest accuracy, the issue of zero probability which is generally faced by naïve bayes analysis needs to be addressed suitably. The proposed framework RB-Bayes aims to extract the required information with high accuracy that could survive the problem of zero probability and also configure accuracy with other methods like Support Vector Machine, Naive Bayes, and K Nearest Neighbor. We calculated mean to handle missing data and calculated probability for yes (positive) and no (negative). The highest value between yes and no decide the value for the tuple. It is mostly used in text classification. The outcomes on Pima Indian diabetes dataset demonstrate that the proposed methodology enhances the precision as a contrast with other regulated procedures. The accuracy of the proposed methodology large dataset is 72.9%.

Analysis study on R-Eclat algorithm in infrequent itemsets mining Mustafa Man; Julaily Aida Jusoh; Syarilla Iryani Ahmad Saany; Wan Aezwani Wan Abu Bakar; Mohd Hafizuddin Ibrahim
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 6: December 2019
Publisher : Institute of Advanced Engineering and Science

There are rising interests in developing techniques for data mining. One of the important subfield in data mining is itemset mining, which consists of discovering appealing and useful patterns in transaction databases. In a big data environment, the problem of mining infrequent itemsets becomes more complicated when dealing with a huge dataset. Infrequent itemsets mining may provide valuable information in the knowledge mining process. The current basic algorithms that widely implemented in infrequent itemset mining are derived from Apriori and FP-Growth. The use of Eclat-based in infrequent itemset mining has not yet been extensively exploited. This paper addresses the discovery of infrequent itemsets mining from the transactional database based on Eclat algorithm. To address this issue, the minimum support measure is defined as a weighted frequency of occurrence of an itemsets in the analysed data. Preliminary experimental results illustrate that Eclat-based algorithm is more efficient in mining dense data as compared to sparse data.

Optimization of discrete wavelet transform features using artificial bee colony algorithm for texture image classification Fthi M. Albkosh; Muhammad Suzuri Hitam; Wan Nural Jawahir Hj Wan Yussof; Abdul Aziz K Abdul Hamid; Rozniza Ali
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 6: December 2019
Publisher : Institute of Advanced Engineering and Science

Selection of appropriate image texture properties is one of the major issues in texture classification. This paper presents an optimization technique for automatic selection of multi-scale discrete wavelet transform features using artificial bee colony algorithm for robust texture classification performance. In this paper, an artificial bee colony algorithm has been used to find the best combination of wavelet filters with the correct number of decomposition level in the discrete wavelet transform. The multi-layered perceptron neural network is employed as an image texture classifier. The proposed method tested on a high-resolution database of UMD texture. The texture classification results show that the proposed method could provide an automated approach for finding the best input parameters combination setting for discrete wavelet transform features that lead to the best classification accuracy performance.

Convolutional neural network-based model for web-based text classification Satyabrata Aich; Sabyasachi Chakraborty; Hee-Cheol Kim
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 6: December 2019
Publisher : Institute of Advanced Engineering and Science

There is an increasing amount of text data available on the web with multiple topical granularities; this necessitates proper categorization/classification of text to facilitate obtaining useful information as per the needs of users. Some traditional approaches such as bag-of-words and bag-of-ngrams models provide good results for text classification. However, texts available on the web in the current state contain high event-related granularity on different topics at different levels, which may adversely affect the accuracy of traditional approaches. With the invention of deep learning models, which already have the capability of providing good accuracy in the field of image processing and speech recognition, the problems inherent in the traditional text classification model can be overcome. Currently, there are several deep learning models such as a convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long-short term memory that are widely used for various text-related tasks; however, among them, the CNN model is popular because it is simple to use and has high accuracy for text classification. In this study, classification of random texts on the web into categories is attempted using a CNN-based model by changing the hyperparameters and sequence of text vectors. We attempt to tune every hyperparameter that is unique for the classification task along with the sequences of word vectors to obtain the desired accuracy; the accuracy is found to be in the range of 85–92%. This model can be considered as a reliable model and applied to solve real-world problem or extract useful information for various text mining applications.

Assessing completeness of a WEB site from quality perspective Sasi Bhanu Jammalamadaka; Kamesh DBK; Jammalamadaka Kodanda Rama Sastry
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 6: December 2019
Publisher : Institute of Advanced Engineering and Science

Assessing quality of a web site is most important especially because people world over are dependent on the content hosted on the WEB site for various purposes. May factors are to be considered for assessing the quality. Quality of every factor must be considered individual and also the total quality of the WEB site must be computed. This paper is primarily focused on the factor called “Completeness” which is one of the factors that can be considered for computing the quality of the WEB sites. There can be much of the disconnected in the content hosted on the web site such as missing href, columns in the tables and forms. The more of the disconnectedness in the content that is hosted on the WEB site, the less the quality, as the information hosted on the WEB site is incomplete and less readable

Real time implementation of embedded devices as a security system in intelligent vehicles connected via Vanets Senthilnathan Palaniapan; Mohammed Ahsan Kollathodi
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 6: December 2019
Publisher : Institute of Advanced Engineering and Science

The fast boom of technology has made our lives easier. The number of computer based functions embedded in cars have multiplied extensively over the past two decades. These days, many embedded sensors allowing localization and verbal exchange are being advanced to enhance reliability, protection and define new exploitation modes in intelligent guided transports. An in-car embedded electronic architecture is a complex setup machine, the improvement of that particular system is related to unique manufacturers and providers. There are several factors required in an efficient and secure system along with protection features, real time monitoring, reliability, robustness, and many other integrated features[1-2]. The appearance of modern era has also expanded the use of vehicles and its associated dangers. Dangers and the road accidents take place often which causes loss of lives and assets due to the bad emergency centres, lack of safety features and limitations within devices embedded within a vehicle. A rpm-speed calculating device can be used in a vehicle such that risku situations while driving can be detected. A system with Ultra sonic sensor can be used as a crash detector of the automobile in the course of the event and also after a crash. With indicators from the device, extreme coincidences also can be recognized. .As the amount of urban automobile grows automobile theft has become a shared difficulty for all citizens. As a solution an antitheft system can be implemented using PIR motion sensors where the system can be attached to the peripheral surface of the vehicle. When these sensors are interfaced with Arduino microcontroller an efficient and reliable security system can be developed[3].

Page 2 of 13 | Total Record : 128

1 2 3 4 5

Filter by Year

2019 2019

Filter By Issues

All Issue Vol 16, No 1: February 2026 Vol 15, No 6: December 2025 Vol 15, No 5: October 2025 Vol 15, No 4: August 2025 Vol 15, No 3: June 2025 Vol 15, No 2: April 2025 Vol 15, No 1: February 2025 Vol 14, No 6: December 2024 Vol 14, No 5: October 2024 Vol 14, No 4: August 2024 Vol 14, No 3: June 2024 Vol 14, No 2: April 2024 Vol 14, No 1: February 2024 Vol 13, No 6: December 2023 Vol 13, No 5: October 2023 Vol 13, No 4: August 2023 Vol 13, No 3: June 2023 Vol 13, No 2: April 2023 Vol 13, No 1: February 2023 Vol 12, No 6: December 2022 Vol 12, No 5: October 2022 Vol 12, No 4: August 2022 Vol 12, No 3: June 2022 Vol 12, No 2: April 2022 Vol 12, No 1: February 2022 Vol 11, No 6: December 2021 Vol 11, No 5: October 2021 Vol 11, No 4: August 2021 Vol 11, No 3: June 2021 Vol 11, No 2: April 2021 Vol 11, No 1: February 2021 Vol 10, No 6: December 2020 Vol 10, No 5: October 2020 Vol 10, No 4: August 2020 Vol 10, No 3: June 2020 Vol 10, No 2: April 2020 Vol 10, No 1: February 2020 Vol 9, No 6: December 2019 Vol 9, No 5: October 2019 Vol 9, No 4: August 2019 Vol 9, No 3: June 2019 Vol 9, No 2: April 2019 Vol 9, No 1: February 2019 Vol 8, No 6: December 2018 Vol 8, No 5: October 2018 Vol 8, No 4: August 2018 Vol 8, No 3: June 2018 Vol 8, No 2: April 2018 Vol 8, No 1: February 2018 Vol 7, No 6: December 2017 Vol 7, No 5: October 2017 Vol 7, No 4: August 2017 Vol 7, No 3: June 2017 Vol 7, No 2: April 2017 Vol 7, No 1: February 2017 Vol 6, No 6: December 2016 Vol 6, No 5: October 2016 Vol 6, No 4: August 2016 Vol 6, No 3: June 2016 Vol 6, No 2: April 2016 Vol 6, No 1: February 2016 Vol 5, No 6: December 2015 Vol 5, No 5: October 2015 Vol 5, No 4: August 2015 Vol 5, No 3: June 2015 Vol 5, No 2: April 2015 Vol 5, No 1: February 2015 Vol 4, No 6: December 2014 Vol 4, No 5: October 2014 Vol 4, No 4: August 2014 Vol 4, No 3: June 2014 Vol 4, No 2: April 2014 Vol 4, No 1: February 2014 Vol 3, No 6: December 2013 Vol 3, No 5: October 2013 Vol 3, No 4: August 2013 Vol 3, No 3: June 2013 Vol 3, No 2: April 2013 Vol 3, No 1: February 2013 Vol 2, No 6: December 2012 Vol 2, No 5: October 2012 Vol 2, No 4: August 2012 Vol 2, No 3: June 2012 Vol 2, No 2: April 2012 Vol 2, No 1: February 2012 Vol 1, No 2: December 2011 Vol 1, No 1: September 2011 More Issue

Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name
Tole Sutikno

Contact Email
ijece@iaesjournal.com

Phone
-

Journal Mail Official
ijece@iaesjournal.com

Editorial Address
-

Location
Kota yogyakarta,

Daerah istimewa yogyakarta

INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name Tole Sutikno

Contact Email ijece@iaesjournal.com

Phone -

Journal Mail Official ijece@iaesjournal.com

Editorial Address -

Location Kota yogyakarta, Daerah istimewa yogyakarta INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Contact Name
Tole Sutikno

Contact Email
ijece@iaesjournal.com

Phone
-

Journal Mail Official
ijece@iaesjournal.com

Editorial Address
-

Location
Kota yogyakarta,

Daerah istimewa yogyakarta

INDONESIA