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Yogyakarta, Indonesia

Handoko S.,UGM | Handoko S.,Diponegoro University | Hadi S.P.,UGM | Suharyanto,UGM | Firmansyah E.,UGM
Journal of Theoretical and Applied Information Technology

This paper presents the parameter optimization of proportional integral (PI) controller in four-leg inverter for DG application when installed in a three-phase four-wire distribution system. The inverter can be utilized as power converter to inject power generated from renewable source to the grid and as shunt active power filter to compensate load current harmonics, load reactive power demand, and current unbalance. To achieve those functions, a reference current needs to be determined. In this study, DC voltage regulator used PI controller to generate the peak value of reference grid current. Optimal tuning of PI gain was required to obtain the best performance of PI controller. An algorithm based on the ant colony optimization (ACO) method was used to optimize the PI parameters. The objective function of optimization was to minimize the integral time absolute error (ITAE) of dc-link voltage and average total harmonic distortion of grid currents (THDiave). The usefulness of the approach was demonstrated by a simulation. © 2005 - 2015 JATIT & LLS. All rights reserved. Source

Putra J.T.,UGM | Sarjiya,UGM | Isnaeni BS M.,UGM
ICITACEE 2015 - 2nd International Conference on Information Technology, Computer, and Electrical Engineering: Green Technology Strengthening in Information Technology, Electrical and Computer Engineering Implementation, Proceedings

Voltage and power flow changes caused by Photovoltaic Generation (PV) source will emerge a new challenge towards a conventional distribution system. This study aims to measure the effect of PV source presence on voltage fluctuation disturbance occured in an electrical power transmission network. In this paper, 70 kV-voltage transmission systems were decreased to 10 kV-distribution feeders and modelled in OpenDSS and MATLAB to investigate the impact of PV generation. A comparison between distribution system without and with PV source was shown. The voltage magnitude of each bus of the distribution systems and transmission systems was analysed. This study then showed that power change from PV source per hour could affect voltage magnitude in distribution and transmission system. © 2015 IEEE. Source

Putranto L.M.,UGM | Perdana J.W.,UGM | Isnaeni M.,UGM
Proceedings - 2013 International Conference on Information Technology and Electrical Engineering: "Intelligent and Green Technologies for Sustainable Development", ICITEE 2013

The line outage of a power system may cause overloads on the lines, overvoltage on buses, and undervoltage on buses that can threat the power system security itself. The effect of the contingency of each power system element is vary. Power Load Performance Indexes as one of the contingency indexes can be implemented to rank the contingency level of each power system lines. N-1 contingency line is applied at 500 kV Jawa Bali Transmission System to rank the severe of contingency and to evaluate the effect of contingency of each element. Tanjung Jati-Ungaran line has the biggest contingency index which means it would be the worst scenario of the line outage. © 2013 IEEE. Source

Mardiana T.,UGM | Mardiana T.,University of Tanjungpura | Adji T.B.,UGM | Hidayah I.,UGM
Telkomnika (Telecommunication Computing Electronics and Control)

In this paper we would like to discuss about stemming effect by using Nazief and Adriani algorithm against similarity detection result of Indonesian written abstract. The contents of the publication abstract similarity detection can be used as an early indication of whether or not the act of plagiarism in a writing. Mostly in processing the text adding a pre-process, one of it which is called a stemming by changing the word into the root word in order to maximize the searching process. The result of stemming process will be changed as a certain word n-gram set then applied an analysis of similarity using Fingerprint Matching to perform similarity matching between text. Based on the F1-score which used to balance the precision and recall number, the detection that implements stemming and stopword removal has a better result in detecting similarity between the text with an average is 42%. It is higher comparing to the similarity detection by using only stemming process (31%) or the one that was done without involving the text pre-process (34%) while applying the bigram. © 2016 Universitas Ahmad Dahlan. Source

Gunadi I.G.A.,UGM | Harjoko A.,UGM | Wardoyo R.,UGM | Ramdhani N.,UGM
Journal of Theoretical and Applied Information Technology

Psychologically, emotion is related to someone’s feeling in particular condition. Some fields like: health, psychology, and police investigation need the information of emotion recognition. Human’s emotion can be classified into six types include happy, sad, angry, fear, disgusted, and normal. Psychologically, there are some methods that can be used to emotion recognition, like self-report analysis, automatic measure, startle response magnitude, FMRI analysis (Functional Magnetic Response Imaging), and behavior response. Each of those methods has their own advantage and disadvantage. The aim of this research is to determine someone’s emotion in a video scene. The video was decomposed into image frame and in each image frame was extracted into feature (component) face, which include mouth, eyes, nose, and forehead. The feature extraction was done by combining two methods based on the color and the facial geometric figure. The state of each face feature related to AU’s (Action Unit) face that used to emotion recognition. State recognition of mouth and eyes can be seen based on the feature elongation, state on the forehead and nose are known based on the wrinkle density. In the last part of emotion, recognition is done with certainty factor method to determine the quality of each emotion, the classification of actor’s emotion is determined based on the quality level of maximum emotion. The results showed recognition of emotion in a single image, the average accuracy of 77%, while in the video, the average accuracy of 76.6%. © 2005 - 2015 JATIT & LLS. All rights reserved. Source

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