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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 9,174 Documents
 520   521   522   523   524 
Dynamic RWX ACM Model Optimizing The Risk on Real Time Unix File System PK Patra; Padma Lochan Pradhan
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 2: February 2015
Publisher : Institute of Advanced Engineering and Science

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

Abstract

The preventive control is one of the well advance controls for recent security for protection of data and services from the uncertainty. Because, increasing the importance of business, communication technologies and growing the external risk is a very common phenomenon now-a-days. The system security risks put forward to the management focus on IT infrastructure (OS). The top management has to decide whether to accept expected losses or to invest into technical security mechanisms in order to minimize the frequency of attacks, thefts as well as uncertainty. This work contributes to the development of an optimization model that aims to determine the optimal cost to be invested into security mechanisms deciding on the measure component of UFS attribute. Our model should be design in such way, the Read, Write & Execute automatically Protected, Detected and Corrected on RTOS. We have to optimize the system attacks and down time by implementing RWX ACM mechanism based on semi-group structure, mean while improving the throughput of the Business, Resources & Technology. DOI: http://dx.doi.org/10.11591/telkomnika.v13i2.7059 
Web design structure with wordpress content management for sports centre booking system Nor Sajidah Ab Ghani; Murizah Kassim; Aziati Husna Awang
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 3: September 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i3.pp1643-1653

Abstract

Sports center booking system need to be more systematic to increase its efficiency. The world wide web (WWW) had been a revolution and it has been utilized to be tools of automation in many applications, including managing booking and payment system in this area of services.  However, existing system needs an ID booking to book the facilities at the court centre and does not delegate any confirmation to users on their booking. This paper aims at integrating stripe payment method by using the WordPress platform where it is one of the content management system (CMS) by using XAMPP. MySQL has been used to store the database while PHP and HTML have been designed to generate QR code. This system was designed based on some function needed for the new member, staffs, and students. The procedure is that the new members will register and pay their members fees. Existing student and staff will just need to sign in using their ID number. This system has provided a booking system which presented the availability of time and date as well as the payment for the new members. Upon booking and payment, email and QR code are given to the user after the confirmation booking by an administrator.  The result shows the increase of efficiency after implementing the new features on the web system which shows 86.66% of increases in term of using the website to book the facilities at the sports centre from the existing system.
Chemical by-Product Diagnostic Technique for Gas Insulated Switchgear Condition Monitoring Visa Musa Ibrahim; Zulkurnain Abdul-Malek; Nor Asiah Muhamad
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 1: July 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v7.i1.pp18-28

Abstract

Chemical by product diagnostic technique is an efficient, cost-effective and reliable diagnostic technique for gas insulate switchgear condition monitoring in view of its high sensitivity and anti- internal and external electromagnetic interference and noise. In this research paper, coaxial simulated gas insulated switchgear chamber and four different types of artificial defect were designed to cause partial discharge that will simulate the decomposition of sulphur hexafluoride gas in the chamber when energize. Fourier transform infrared spectrometer was used as the method of chemical by-product technique to detect the SF6 decomposition product and its concentration. Different numerous by-products were detected (SO2, SOF2, SO2F2, SO2F10, SiF4, CO, C3F8, C2F6 ) under this experiment using four different types of defect and the by-products differs with the type of defect and the generation rate. Gas insulated switchgear health condition can be feasibly diagnosed by analyzing the decomposition products of SF6 to identify its fault. 
Bandpass filter based on complementary split ring resonators at X-band Furqan Furqan; Said Attamimi; Andi Adriansyah; Mudrik Alaydrus
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 1: January 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i1.pp243-248

Abstract

Complementary Split Ring Resonators were used integrated in a substrate integrated waveguide to generate passband charateristics in X-Band. Based on a parameter study with an electromagnetic commercial software, the characteristics of double and quadruple CSRRs according the reflection and transmission factor were observed. The computer simulation showed, the bandpass filter worked in the frequency range 8.12-8.63 GHz and 8.11-8.63 GHz for double and quadruple CSRR, respectively. The insertion loss was 0.12 dB and 0.015 dB. The measurement mit a vector network analyzer verified the simulation results. The frequeny range measured was 8.12-8.67 GHz and 8.12-8.61 GHz for double and quadruple CSRRs, respectively. The measured insertion loss was 0.25 dB and 0.2 dB.
Formulation of an integrated social commerce framework to promote social capital for energy sectors Mohana Shanmugam; Vinitha Karunakaran; Asra Amidi
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 1: July 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i1.pp427-434

Abstract

Social capital refers to the resources available in personal and business networks. In developing a culture that values and practices social capital, social factors are considered one of the main precursors.  With the proliferation of social commerce and the maturing of social media, social capital can be acquired and further developed for productive benefits, particularly for energy sectors in Malaysia. In this study, an integrated social commerce framework to promote social capital is presented and evaluated. The framework attempted to define the relationship between the Theories of Planned Behavior (TPB) and Social Support Theory (SST) alongside satisfaction and perceived value factors towards promoting social capital development in energy sectors. This research uses SPSS to analyse the data collected from employee in the energy sectors in Malaysia. Research reveals that social capital is present when there is trust and loyalty among the users and the significance of social capital is monumental for energy sectors’ productivity, efficiency and profitability. A survey is adapted and distributed to 20 respondents from the energy sector in Malaysia as a mean to study on the validity and reliability of the research factors. Results indicate that all proposed factors are significant in promoting social capital except one, which is the Perceived Behavioral Control (PBC) of the TPB.
Multi-Level of Feature Extraction and Classification for X-Ray Medical Image Mohammed Muayad Abdulrazzaq; Imad FT Yaseen; SA Noah; Moayad A. Fadhil
Indonesian Journal of Electrical Engineering and Computer Science Vol 10, No 1: April 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v10.i1.pp154-167

Abstract

There has been a rise in demand for digitized medical images over the last two decades. Medical images' pivotal role in surgical planning is also an essential source of information for diseases and as medical reference as well as for the purpose of research and training. Therefore, effective techniques for medical image retrieval and classification are required to provide accurate search through substantial amount of images in a timely manner. Given the amount of images that are required to deal with, it is a non-viable practice to manually annotate these medical images. Additionally, retrieving and indexing them with image visual feature cannot capture high level of semantic concepts, which are necessary for accurate retrieval and effective classification of medical images. Therefore, an automatic mechanism is required to address these limitations. Addressing this, this study formulated an effective classification for X-ray medical images using different feature extractions and classification techniques. Specifically, this study proposed pertinent feature extraction algorithm for X-ray medical images and determined machine learning methods for automatic X-ray medical image classification. This study also evaluated different image features (chiefly global, local, and combined) and classifiers. Consequently, the obtained results from this study improved results obtained from previous related studies.
Optical Sensor Based on Dye Sensitized Solar Cell (DSSC) Rahmadwati Rahmadwati; Sapriesty Nainy Sari; Eka Maulana; Akhmad Sabarudin
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.pp685-690

Abstract

An optical sensor is designed to convert a number of light energy in to electrical energy. The sensor hasbeen successfully measured using light illuminance to achieve electric parameters as the sensor output. In this research the optical sensor design was characterized according to the voltage and current output with the stimulus from mercury lamp. The sensor is customized from Dye-Sensitized Solar Cell with photo-electrode and photo-catalysator of Titanium Dioxide and extracted tobacco chlorophyll dye. Spin coating method was conducted to fabricate the thick layer deposition using selected material. Based on the absorbance measurement, it shows that tobacco dye has the characteristics of visible light absorption in the wavelength of 300-000 nm. The result of this research revealed that from 2 variation of optical sensor design square with active area of (2 cm x 2 cm) and (1 cm x 1 cm). Analitycal result shows that the sensor has wide linear characteristic in certain light illuminance both of output current and voltage.
System Diagnosis of Coronary Heart Disease using A Combination of Dimensional Reduction and Data Mining Techniques: A Review Wiharto Wiharto; Hari Kusnanto; Herianto Herianto
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 2: August 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v7.i2.pp514-523

Abstract

Coronary heart disease is a disease with the highest mortality rates in the world. This makes the development of the diagnostic system as a very interesting topic in the field of biomedical informatics, aiming to detect whether a heart is normal or not. In the literature there are diagnostic system models by combining dimension reduction and data mining techniques. Unfortunately, there are no review papers that discuss and analyze the themes to date. This study reviews articles within the period 2009-2016, with a focus on dimension reduction methods and data mining techniques, validated using a dataset of UCI repository. Methods of dimension reduction use feature selection and feature extraction techniques, while data mining techniques include classification, prediction, clustering, and association rules.
High Frequency Transformer for Ship Electrical Power System AnuPriya K R; Sasilatha T
Indonesian Journal of Electrical Engineering and Computer Science Vol 9, No 2: February 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v9.i2.pp347-350

Abstract

The system represented during this paper uses 3 matrix converters and a high frequency electrical device to attain isolation and voltage transformation from primary to secondary aspect. Two matrix converters manufacture high frequency voltage across a transformer, with open all over primary. a 3rd matrix device converts the high frequency cut voltage to line frequency. The non-idealities like outflow inductance of the electrical device have a big impact on the device performance. This paper studies the impact of outflow inductance on the regulation of the output voltage of the device. The simulation study has been carried out in SIMULINK and also the results are presented.
Reservoir water level forecasting using normalization and multiple regression Siti Rafidah M-Dawam; Ku Ruhana Ku-Mahamud
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 1: April 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v14.i1.pp443-449

Abstract

Many non-parametric techniques such as Neural Network (NN) are used to forecast current reservoir water level (RWLt). However, modelling using these techniques can be established without knowledge of the mathematical relationship between the inputs and the corresponding outputs. Another important issue to be considered which is related to forecasting is the preprocessing stage where most non-parametric techniques normalize data into discretized data. Data normalization can influence the the results of forecasting. This paper presents reservoir water level (RWL) forecasting using normalization and multiple regression. In this study, continuous data of rainfall (RF) and changes of reservoir water level (WC) are normalized using two different normalization methods, Min-Max and Z-Score techniques. Its comparative studies and forecasting process are carried out using multiple regression. Three input scenarios for multiple regression were designed which comprise of temporal patterns of WC and RF, in which the sliding window technique has been applied. The experimental results showed that the best input scenario for forecasting the RWLt employs both the RF and the WC, in which the best predictors are three day’s delay of WC and two days’ delay of RF. The findings also suggested that the performance of the RWL forecasting model using multiple regression was dependent on the normalization methods.

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