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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 9,199 Documents
 189   190   191   192   193 
Knowledge Management System for Zakat Aulia Rahman Nasution; Irman Hermadi; Wisnu Ananta K.; Irfan Syauqi B.
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 12: December 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Zakat is one of the Islamic pillars that has strategic contribution to the society. Zakat is one of the  Muslim obligation. It is also a form of social solidarity. The collaborative research conducted by Badan Amil Zakat Nasional (BAZNas) and Institut Pertanian Bogor (IPB) estimated the potential of zakat collection in Indonesia could reach about Rp 217 trillion every year that has not been achieved yet. Researchers and practitioners have advised to implement a Knowledge Management System (KMS) to optimize the collection and BAZNas’s objectives. The objective of this research is to develop web-based Zakat Knowledge Management System (ZKMS). The KMS development methodology is done with using Knowledge Management System Life Cycle (KMSLC). Knowledge has been captured from experts consisting of practitioners and scientists from BAZNas of Bogor City, muzakki, documents, books and journals. ZKMS was developed using ASP.NET framework, C# programming language and MySQL database management system. The system has menu that are user, zakat knowledge, questions and answers with experts, interaction between members, about us, profiles and knowledge sources. This system is designed be user friendly to get, know, make, share, store and disseminate actual and contemporary of zakat knowledge. http://dx.doi.org/10.11591/telkomnika.v12i12.6842 
Background Modeling to Detect Foreground Objects Based on ANN and Spatio-Temporal Analysis N. Satish Kumar; Shobha G
Indonesian Journal of Electrical Engineering and Computer Science Vol 2, No 1: April 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v2.i1.pp151-160

Abstract

This paper presented an approach to building background model for moving object detection using unsupervised Artificial Neural Network (ANN) without any prior knowledge about foreground objects. First, using Local Binary Pattern (LBP) which is texture feature, builds a statistical Background Model using ANN, then, comparing the behavior of next incoming frame with model and decide each pixel whether is deviating from a model or not. And based on if method detects foreground objects then background model is updated to make this model adaptive. Also, spatial-temporal information has been exploited in this method to suppress sudden illumination variation and to suppress false foreground pixels.  It was demonstrated and proved, by qualitative and quantitative metrics that the newly presented approach is adaptive, generic and can address all issues and challenges for background subtraction. To evaluate the performance of the presented approach this paper compared with recent approaches by using standard metrics and proved that presented method outperforms many existing recent approaches.
The Application of Virtual Instrument Technology in the Tester Jianhua Ren; Xiaogang Guo; Yanceng Liu; Li Chen
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 8: August 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

Four-ball tester is a device which is used to evaluate the resistance of extreme pressure grease performance and wear resistance with simple structure, less fuel consumption and low cost. It has been widely used in Lubricants research. In this paper, the principle and testing equipment of four-ball tester are introduced. At the same time, some shortcomings such as inconvenient load mechanism and inaccurate measurements are presented. Friction testing and recording system is improved on the basic of the previous system to avoid the defects. Amplification ratio of the friction test result increases significantly.  To improve precision and convenience for data storing, analysis and comparison, data acquisition system is established based on LabVIEW. Then friction measurement process is visualization to realize the measured results being observed visually. DOI: http://dx.doi.org/10.11591/telkomnika.v11i8.3103
Fasting Ontology in Pillars of Islam Sara Afiqah Mohd Zailani; Nurul Aswa Omar; Aida Mustapha; Mohd Hisyam Abdul Rahim
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: November 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i2.pp562-569

Abstract

The development of Fasting Ontology in the Pillars of Islam is presented in this paper and has been built based on reliable sources of Islamic Knowledge. The METHONTOLOGY methodology is used for the ontology development, which include identifying motivation scenarios, creating the competency questions, implementation and evaluation. From the beginning of the development of life cycle, the ontology was appraised from the competency questions and the outcome were clear. Therefore, this ontology can link each concept specifically to the individual verse together with the Tafsir that is related to the topics. The ontology proposed will be part of a larger ontology on Five Pillars of Islam. This development of the ontology is intended to refer to the field of learning for other purpose. For instance, search engine, chatbot, expert system or knowledge-based system.
Fouling Prediction using Neural Network Model for Membrane Bioreactor System Nurazizah Mahmod; Norhaliza Abdul Wahab
Indonesian Journal of Electrical Engineering and Computer Science Vol 6, No 1: April 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v6.i1.pp200-206

Abstract

Membrane bioreactor (MBR) technology is a new method for water and wastewater treatment due to its ability to produce better and high-quality effluent that meets water quality regulations. MBR also is an advanced way to displace the conventional activated sludge (CAS) process. Even this membrane gives better performances compared to CAS, it does have few drawbacks such as high maintenance cost and fouling problem. In order to overcome this problem, an optimal MBR plant operation need to be developed. This can be achieved through an accurate model that can predict the fouling behaviour which could optimise the membrane operation. This paper presents the application of artificial neural network technique to predict the filtration of membrane bioreactor system. The Radial Basis Function Neural Network (RBFNN) is applied to model the developed submerged MBR filtration system. RBFNN model is expected to give good prediction model of filtration system for estimating the fouling that formed during filtration process.
Radial basis function neural network for head roll prediction modelling in a motion sickness study Sarah ‘Atifah Saruchi; Mohd Hatta Mohammed Ariff; Mohd Ibrahim Shapiai; Nurhaffizah Hassan; Nurbaiti Wahid; Noor Jannah Zakaria; Mohd Azizi Abdul Rahman; Hairi Zamzuri
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 3: September 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i3.pp1637-1644

Abstract

Motion Sickness (MS) is the result of uneasy feelings that occurs when travelling. In MS mitigation studies, it is necessary to investigate and measure the occupant’s Motion Sickness Incidence (MSI) for analysis purposes. One way to mathematically calculate the MSI is by using a 6-DOF Subjective Vertical Conflict (SVC) model. This model utilises the information of the vehicle lateral acceleration and the occupant’s head roll angle to determine the MSI. The data of the lateral acceleration can be obtained by using a sensor. However, it is impractical to use a sensor to acquire the occupant’s head roll response. Therefore, this study presents the occupant’s head roll prediction model by using the Radial Basis Function Neural Network (RBFNN) method to estimate the actual head roll responses. The prediction model is modelled based on the correlation between lateral acceleration and head roll angle during curve driving. Experiments have been conducted to collect real naturalistic data for modelling purposes. The results show that the predicted responses from the model are similar with the real responses from the experiment. In future, it is expected that the prediction model will be useful in measuring the occupant’s MSI level by providing the estimated head roll responses.
Research of Function Optimization Algorithm Qinghua Wu; Hanmin Liu; Yuxin Sun; Fang Xie; Jin Zhang; Xuesong Yan
Indonesian Journal of Electrical Engineering and Computer Science Vol 10, No 4: August 2012
Publisher : Institute of Advanced Engineering and Science

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Abstract

Traditional evolutionary algorithm trapped into the local minimum easily. Therefore, based on a simple evolutionary algorithm and combine the base ideology of orthogonal test then applied it to the population initialization, crossover operator, as well as the introduction of Inver-Over operator to prevent local convergence to form a new evolutionary algorithm. Through the series of numerical experiments, the new algorithm has been proved is efficiency for function optimization. DOI: http://dx.doi.org/10.11591/telkomnika.v10i4.877
Research on the Information Security Problems in Cloud Calculation's Environment Xia Hu; Min Zhou
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 12: December 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

With the development of technology, cloud calculation becomes a widely used technology and is regarded as the third IT revolution following the computers and the Internet. Then only after resolving its security issues, it is able to operate successfully. This paper at first introduces the concept and characteristics of cloud calculation and then elaborates the current situation of cloud calculation's security.Then it analyzes the security risks of cloud calculation. According to these risks, the solution is proposed. DOI: http://dx.doi.org/10.11591/telkomnika.v11i12.3612
An SLAM Algorithm Based on Square-root Cubature Particle Filter Xue feng Dai; Zu guo Chen; Chao Yang; Lai hao Jiang; Biao Cai
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 6: June 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

The lack of the latest measurement information and the Particle serious degradation cause low estimation precision in the tradition particle filter SLAM (simultaneous localization and mapping). For solve this problem, a SRCPF-SLAM (square cubature particle filter simultaneous localization and mapping) is proposed in this paper. The algorithm fuses the latest measurement information in the stage of the prior distribution updated of the particle filter SLAM. It designs importance density function by SRCKF (Square-root Cubature kalman filter) that is more close to the posterior density, and it spreads the square root of state covariance. So, the algorithm ensures the symmetry and the positive semi-definiteness of the covariance matrix and improves numerical estimation precision and stability. The simulation results show that the proposed algorithm has higher accuracy of the state estimation when compared with the the PF-SLAM (particle filter simultaneous localization and mapping) algorithm, EPF-SLAM (extend particle filter simultaneous localization and mapping) algorithm and the UPF-SLAM (unscented particle filter simultaneous localization and mapping) algorithm. DOI : http://dx.doi.org/10.11591/telkomnika.v12i6.5059
One Method of Cloud Computing Bandwidth Allocation Based on Fairness Yiquan Kong
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 2: February 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

In order to solve the bandwidth allocation unfairness problem in the cloud computing network, one method uses fairness congestion control algorithm, access control list (ACL) and traffic policing and traffic shaping in the paper. The method can rationally solve the problem after analyzing the reason of cloud computing bandwidth allocation unfairness. For illustration, one network video conference example was utilized to show the method in solving bandwidth allocation unfairness problem.The experimental results show network bandwidths are fairly allocated, packet loss ratio and latency is obvious improvement. The method deals with non-adaptive UDP and TCP adaptive flow congestion and provides the end-to-end quality of service over the differentiated services networks, and the bandwidth allocation problem based on fairness in the cloud computing network is solved well. DOI: http://dx.doi.org/10.11591/telkomnika.v11i2.2059

Page 191 of 920 | Total Record : 9199

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