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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 16, No 2: November 2019" : 65 Documents clear
Spectrum sensing in single channel and multi-channel cognitive radio networks Amira Osama Hashesh; Heba A.Tag El-Dien; Ahmad A.Aziz El-Banna; Adly Tag El-Din
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 2: November 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i2.pp812-817

Abstract

Sensing the existence or absence of primary user is the major chore of cognitive radio networks. Nevertheless, Spectrum sensing is the core process of cognitive radio and with target to find idle channels.Various detection techniques exist, however, energy detection is considered as the most used detector because of its lower computational cost. In this paper, we proposed a study of throughput for a cognitive radio system. We had two scenarios, in the first scenario; a study of throughput against probability of false alarm was done; where, only one channel is sensed, to maximize the individual channel throughput. In the second scenario, multi-channel is sensed to maximize the overall system capacity. In addition, different number of channels is considered with different sensing times and at different throughput costs.The performance of the network has been investigated in terms of maximum throughput for optimal number of CR channels.      
Modelling emotion expression through agent oriented methodology S.Filzah Zulkifli; CW Shiang; N Jali; M.A. Khairuddin
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 2: November 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i2.pp972-977

Abstract

This paper presents Modelling Emotion Expression through Agent Oriented Methodology. Considering emotions of the intended users in the software engineering can uncover new requirements to improve and more accepted the system. While emotion is paying much attention nowadays, there is lacking systematic way to model the emotion based system. Without the systematic approach, it is hard to debug, design and develop an emotion based system. Since the emotional requirement of people has not being fully investigated, the research outcome propose the emotion modelling as part of the complete set of agent-oriented modelling for virtual character in eLearning system, The contribution of this paper is to introduce agent oriented modelling to systematic model an emotion based solution for an eLearning system and instructional video design. With the emotion model, it can serve as a guide to design, redesign, and discuss the emotion elements among the software development team. This is important for better debugging and project management especially for emotion led system.
OpenGL 3D crowd evacuation simulation at universiti tun hussein onn malaysia (UTHM) hostel Jamaludin, M.N; Mohamad, S.; Sunar, M.S.; Isa, K.; Hanifa, R.M.; Nasir, F.M.; Shah, S.M.
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 2: November 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i2.pp1034-1041

Abstract

Crowd simulation is the process of simulating characterized agents or entities using computer application to analyse it in virtual scene or virtual environment. This paper investigates the best route path for agents to act in avoiding the fire hazards with different designated type of stairs in shop lots that were converted to hostel dormitory for students. 3D social force agent’s model and 3D fire hazards were designed in Microsoft Visual Studio C++ software and OpenGL library. A research was conducted using social force model behaviour and were taken by 10 and 15 agents to analyse the time taken to complete the evacuation process. The acceleration produced where it is related with route path taken by agents, interaction forces of agents and interaction forces of wall are the main research system to analyse agents’ behaviour during simulation. Different simulations have been used to determine the best and fastest route taken by agents. In summary, the lower the number of agents, the lower the time allocated by agents to complete the evacuation. Finally, less number of agents using the designated straight stairs gave a lower time to complete evacuation process and reached high level of security to avoid being exposed to fire hazards. 
Privacy preserving outsourcing algorithm for two-point linear boundary value problems Nedal Mohammed; Laman R. Sultan; Santosh Lomte
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 2: November 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i2.pp1065-1069

Abstract

One of a powerful application in the age of cloud computing is the outsourcing of scientific computations to cloud computing which makes cloud computing a very powerful computing paradigm, where the customers with limited computing resource and storage devices can outsource the sophisticated computation workloads into powerful service providers. One of scientific computations problem is Two-Point Boundary Value Problems(BVP) is a basic engineering and scientific problem, which has application in various domains. In this paper, we propose a privacy-preserving, verifiable and efficient algorithm for Two-Point Boundary Value Problems in outsourcing paradigm. We implement the proposed schema on the customer side laptop and using AWS compute domain elastic compute cloud (EC2) for the cloud side.
Automating quranic verses labeling using machine learning approach A. Adeleke; N. Samsudin; A. Mustapha; S. Ahmad Khalid
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 2: November 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i2.pp925-931

Abstract

Classification of Quranic verses into predefined categories is an essential task in Quranic studies. However, in recent times, with the advancement in information technology and machine learning, several classification algorithms have been developed for the purpose of text classification tasks. Automated text classification (ATC) is a well-known technique in machine learning. It is the task of developing models that could be trained to automatically assign to each text instances a known label from a predefined state. In this paper, four conventional ML classifiers: support vector machine (SVM), naïve bayes (NB), decision trees (J48), nearest neighbor (k-NN), are used in classifying selected Quranic verses into three predefined class labels: faith (iman), worship (ibadah), etiquettes (akhlak). The Quranic data comprises of verses in chapter two (al-Baqara) of the holy scripture. In the results, the classifiers achieved above 80% accuracy score with naïve bayes (NB) algorithm recording the overall highest scores of 93.9% accuracy and 0.964 AUC.
Principles of reforming an agile-compliant performance appraisal Mawarny Md. Rejab; Mazni Omar; Mazida Ahmad; Syahida Hassan
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 2: November 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i2.pp1009-1017

Abstract

This paper presents principles of reforming an Agile-compliant performance appraisal. In this study, several semi-structured interviews have been carried out and discovered eight principles for reforming an Agile-compliant performance appraisal for Agile teams. Performance appraisal for software engineers in an Agile software development environment is complex and different from the traditional software development.  Performance appraisal should be aligned to Agile values, principles, and practices, which advocate interactions, collaborations, teamwork, and knowledge transfer among Agile team members. Therefore, a transition to Agile Software Development requires the implementation of Agile-compliant performance appraisal. These principles embark the proper practices and guidance to support management and Agile teams in deriving and implementing an Agile-compliant performance appraisal. Therefore, the emerged principles can be a baseline in generating an Agile-compliant performance appraisal to assess Agile team members in a fair and consistent manner. This indirectly increases motivation amongst team members and tends to produce capable workforce to perform at a higher level.
A comparative study on dimensionality reduction between principal component analysis and k-means clustering Norsyela Muhammad Noor Mathivanan; Nor Azura Md.Ghani; Roziah Mohd Janor
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 2: November 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i2.pp752-758

Abstract

The curse of dimensionality and the empty space phenomenon emerged as a critical problem in text classification. One way of dealing with this problem is applying a feature selection technique before performing a classification model. This technique helps to reduce the time complexity and sometimes increase the classification accuracy. This study introduces a feature selection technique using K-Means clustering to overcome the weaknesses of traditional feature selection technique such as principal component analysis (PCA) that require a lot of time to transform all the inputs data. This proposed technique decides on features to retain based on the significance value of each feature in a cluster. This study found that k-means clustering helps to increase the efficiency of KNN model for a large data set while KNN model without feature selection technique is suitable for a small data set. A comparison between K-Means clustering and PCA as a feature selection technique shows that proposed technique is better than PCA especially in term of computation time. Hence, k-means clustering is found to be helpful in reducing the data dimensionality with less time complexity compared to PCA without affecting the accuracy of KNN model for a high frequency data.
An optimization of facial feature point detection program by using several types of convolutional neural network Shyota Shindo; Takaaki Goto; Tadaaki Kirishima; Kensei Tsuchida
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 2: November 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i2.pp827-834

Abstract

Detection of facial feature points is an important technique used for biometric authentication and facial expression estimation. A facial feature point is a local point indicating both ends of the eye, holes of the nose, and end points of the mouth in the face image. Many researches on face feature point detection have been done so far, but the accuracy of facial organ point detection is improving by the approach usingConvolutional Neural Network (CNN). However, CNN not only takes time to learn but also the neural network becomes a complicated model, so it is necessary to improve learning time and detection accuracy. In this research, the improvement of the detection accuracy of the learning speed is improved by increasing the convolution layer.
Design and modeling of optical reflectors for a PV panel adapted by MPPT control Belhadj Mohammed; Boufeldja Kadri; Nasri Abdelfatah; Benlaria Ismail
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 2: November 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i2.pp653-660

Abstract

Due to the highly non-linear electrical characteristics of photovoltaic generators (PVGs), the efficiency of PV systems can be improved by forcing the GPV to operate at their maximum power point (MPP). In this article, we are interested in concentrating Photovoltaic design to improve the output current of the panelwhile maintaining the DCDC boost element, after presenting the basic structure of Boost DC-DC converter, which shows the existence of a limitation on the voltage gain for this converter. In order to meet the specifications (high voltage gain and low ripple of the input current), existing structures will be presented that are able to provide a high voltage gain (Photovoltaic concentration) compared to another structure
Human face detection and recognition using contour generation and matching algorithm Arulananth T.S; Baskar M.; Sateesh R.
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 2: November 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i2.pp709-714

Abstract

Face detection, monitoring of human face and recognition is a high-quality venture in safety, surveillance and regulation enforcement systems with greater accuracy. There are many motives at the back of in this trouble. Which include function of the human face; pose version, negative environmental conditions, terrible lightning and picture tilt etc,. So we must locate a few feasible solutions to clear up those issues by means of imposing a brand new system. Our proposed venture might be improving the issues on Face detection, monitoring of human face and recognition issues.

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