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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 9,049 Documents
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Neural Control based on Incomplete Derivative PID Algorithm QiZhi Wang; Xiaoxia Wang
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 4: April 2013
Publisher : Institute of Advanced Engineering and Science

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

Abstract

In the actual control, complete differential digital PID algorithms have been widely used. But the differential will amplify high-frequency noise. If the differential response is too sensitive, it is easy to cause the control process oscillation, incomplete PID control algorithms can overcome the differential oscillation. Incomplete derivative PID algorithm combined with neural network improves the system control quality, it has the important practical significance. The simulation shows it has good position tracking performance and high robustness. DOI: http://dx.doi.org/10.11591/telkomnika.v11i4.2392
To Improve Feature Extraction and Opinion Classification Issues in Customer Product Reviews Utilizing an Efficient Feature Extraction and Classification (EFEC) Algorithm Palaiyah Solainayagi; Ramalingam Ponnusamy
Indonesian Journal of Electrical Engineering and Computer Science Vol 10, No 2: May 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v10.i2.pp587-595

Abstract

Currently, customer's product review opinion plays an essential role in deciding the purchasing of the online product. A customer prefers to acquire the opinion of other customers by viewing their opinion during online products' reviews, blogs and social networking sites, etc. The majority of the product reviews including huge words. A few users provide the opinion; it is tough to analysis and understands the meaning of reviews. To improve user fulfillment and shopping experience, it has become a general practice for online sellers to allow their users to review or to communicate opinions of the products that they have sold. The major goal of the paper is to solve feature extraction problem and opinion classification problem from customers utilized product reviews which extract the feature words and opinion words from product reviews. To propose an Efficient Feature Extraction and Classification (EFEC) algorithm is implementing to extracts a feature from opinion words. The reviewer usually marks both positive and negative parts of the reviewed product, despite the fact that their general opinion on the product may be positive or negative. An EFEC algorithm is utilized to predict the number of positive and negative opinion in reviews. Based on Experimental evaluations, proposed algorithm improves accuracy 15.05%, precision 13.7%, recall 15.59% and F-measure 15.07% of the proposed system compared than existing methodologies
Energy conservation potentials of an office buildings in Northern Nigeria: A case study of Katsina secretariat complex Muhammad Rabiu Abbas
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 2: May 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i2.pp629-635

Abstract

The importance of energy conservation in our contemporary world cannot be overemphasized, efficient utilization of energy has significant impact in improving economy at all levels of human endeavour. No doubt, adequate and appropriate utilization of energy especially electrical energy boosts up any organizational developmental activities. Recently, research interest has emphasis towards efficient energy utilization and energy conservation as the effective means of reducing energy consumption in buildings thereby reducing its maintenance cost. This paper investigated and analysed the energy consumption characteristics of Katsina state secretariat complex for the period of 3 years (i.e. from 2014 to 2016) based on site surveys and analysis of the energy end users present, using the records of electricity utility bills and Automotive Gas Oil (AGO), being the two energy carriers of the complex. Records have shown that, the secretariat complex average electricity and AGO annual consumptions were found as 1045661.95 kWh and 116650.33 litres of AGO (which is equivalent to 1250491.54 kWh) respectively. The investigation revealed a distinct consumption pattern, indicating peak energy consumption during the hot months of April to August due to significant air conditioning requirements. The result of the investigation of the energy conservation potentials in the secretariat complex have shown that, energy savings of up to 6.5% of the total energy can be achieved by switching-off all security lights during the day. While turning off the air conditioners in the early morning hours of between 8am to 10am would provide a saving of up to 19% of the total energy. Furthermore, a saving of 16.5% of the total energy can be achieved when the incandescent lamps are replaced with the energy efficient ones. The energy conserving measures (ECMs) followed in this research has shown significant savings in terms of both energy and cost, and if well implemented can give way for a sustainable energy management of similar office buildings in future.
Contents of e-Government for Pursuing Value in Indonesian Local Government Alfira Sofia; Jann Hidajat Tjakraatmadja; Sudarso Kader Wiryono; Suhardi Suhardi
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 11: November 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i11.pp7895-7905

Abstract

This research aimed to explore contents of Indonesian e-Government in order to obtain expected value effectively by considering obstacles in implementing e-Government. It was achieved by reviewing basic and applied theory of e-Government development. The study entails compilation of emerged benefits by triangulation of extensive literature review, case study (by best practices city/municipality in Indonesia) and FGD. Some problems in implementing e-Government explored in this research can be solved through simple and creative ways. It found that contents exploration of all relationships between 4 elements which are government, users, system, and environment, can be effective solution, which have been implemented by all successful cities/municipalities. The finding would help government policy and decision makers design and implement policies and strategies to improve e-Government services. The research is undertaken at Indonesian local government level as the first researches in Indonesian e-Government implementation by exploring best practice contents which emerged in each city/municipality.
Electric Price Forecast using Interbreed Approach of Linear Regression and SVM Deepak Saini; Akash Saxena
Indonesian Journal of Electrical Engineering and Computer Science Vol 2, No 3: June 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v2.i3.pp537-544

Abstract

Electricity price forecasting is a hypercritical issue due to the involvement of consumers and producers in electricity markets. Price forecasting plays an important role in planning and managing economic operations related with the electrical power (bidding, trading) and other decisions related with load shedding and generation rescheduling. It is also useful for optimization in electrical energy trade. This paper explores an interbreed technique based on Support Vector Machine (SVM) and linear regression to predict the day ahead electricity price using historical data as a raw insert. Different 27 linear regression models are formed to create initial framework for forecasting engine. Comparison of the performance of different forecasting engines is carried out on the basis of error indices namely Mean Square Error (MSE), Sum Square Error (SSE) and other conventional error indices. A detailed explanation of linear regression system based model is presented and simulation results exhibit that the proposed learning method is able to forecast electricity price in an effective manner.
Effects of the Colored Pump Noise in a Two-Mode Laser Youlin Xiang; Haiyun Lin; Jianchun Cai; Zucheng Dai; Yujiao Wang
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 9: September 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

An inhomogeneously broadened two-mode ring laser system with the colored pump noise is considered. The effects of the auto-correlation time t of the colored pump noise on the competition between two modes in the laser system are investigated for the first time by the computer simulation method. The results show that when the laser system works far above threshold, the stationary properties of the laser intensities of two laser modes changes in quite other ways as the value of increases. It is obvious that the effects of the colored pump noise on the mode competition between two laser modes. Here does not exist mode competition for enough small value of t, it increases and then remain unchanged with increasing value of t. DOI: http://dx.doi.org/10.11591/telkomnika.v11i9.3235
An Improved Prediction Approach on Solar Irradiance of Photovoltaic Power Station Haiying Dong; Lei Yang; Shengrui Zhang; Yuan Li
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 3: March 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

Solar irradiance is the main factor which influences the photovoltaic output power. In order to predict the photovoltaic output power accurately, the prediction accuracy of irradiance should be improved. In terms of unsatisfactory prediction accuracy of irradiance of traditional photovoltaic power station, this paper presents an approach to predict solar irradiance of photovoltaic power station based on wavelet decomposition and extreme learning machine. In this method, the historical solar irradiance data is divided through the wavelet decomposition of three layers. Then the prediction models of irradiance are built based on the extreme learning machine. Finally, the solar irradiance is predicted with 15 minutes’ resolution one day ahead. With the decomposed components and the relative meteorological data as the input and the irradiance forecast data after wavelet reconstruction as the output. The simulation result coming from the actual measured data of a photovoltaic power station in Gansu province indicates that the proposed model is of higher accuracy in comparison with the traditional ones. DOI : http://dx.doi.org/10.11591/telkomnika.v12i3.4017
Research on Web-based Real-time Monitoring System on SVG and Comet Lijing Zhang; Wei Xiong; Xuehui Xian
Indonesian Journal of Electrical Engineering and Computer Science Vol 10, No 5: September 2012
Publisher : Institute of Advanced Engineering and Science

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

Abstract

For the lack of real-time performance of browser technology in existing Web-based real-time monitoring system, takes use of SVG (Scalable Vector Graphics) and the Comet to design a new Web-based real-time monitoring system. In this system, JSON (JavaScript Object Notation) is the data transmission carrier, Comet is the key technology for system communication and data transmission, and SVG is a chart drawing tool in the browser side. So this system has a good real-time and is rich in the form of show. DOI: http://dx.doi.org/10.11591/telkomnika.v10i5.1347
The Study of User Acceptance Toward E-Learning System in Higher Education Dana Indra Sensuse; Darmawan Baginda Napitupulu
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.pp466-473

Abstract

E-learning is a model of delivering learning content electronically with the help of computers and multimedia. ABC University has implemented the e-learning system for two (2) years in order to improve the quality of teaching and learning process. This study aims to determine the level of user acceptance, especially from the perspective of students. In other words, this study also wants to evaluate the implementation of e-learning systems in higher education as well as identifying any factors that encourage students to use e-learning system especially in ABC University. The research method used was survey with the approach of TAM (Technology Acceptance Model) as the technology acceptance evaluation model consisting of two main factors: perceived ease of use and perceived usefulness. The results showed perceived usefulness significantly positive influence on user acceptance, while perceived ease of use did not significantly influence on user acceptance. The perceived ease of use also significantly positive influence perceived usefulness. The variance of user acceptance could be explained by two factors about 50.5%. 
Radio Access Technology (RAT) Selection Mechanism using TOPSIS Method in Heterogeneous Wireless Networks (HWN) Farhat Anwar; Mosharrof Masud; Burhan Ul Islam; Rashidah Funke Olanrewaju
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.pp852-864

Abstract

In next-generation wireless networks, a Multi-Mode Device (MMD) can be connected with available Radio Access Technology (RAT) in a Heterogeneous Wireless Network (HWN). The appropriate RAT selection is essential to achieve expected Quality of Service (QoS) in HWN. There are many factors to select an appropriate RAT in HWN including Data rate, Power consumption, Security, Network delay, Service price, etc. Nowadays, the MMDs are capable to handle with multiple types of services like voice, file downloading, video streaming. Considering numerous factors and multiple types of services, it is a great challenge for MMDs to select the appropriate RAT. A Multi-Attribute Decision Making (MADM) method to deal with numerous attributes to achieve the expected goal is Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). This research utilized TOPSIS method to evaluate its proposed algorithm to choose the proper RAT for single and dual call services. The algorithm applies users' preference of a specific RAT that varies for diverse categories of calls. It also aggregates the assigned call weight and call priority to choose the RAT for group call admission for different scenarios. The highest closeness coefficient has been considered the appropriate networks among other networks. 100 call admission into three networks has been simulated and has been observed.

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