2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE)最新文献

Root Cause Analysis of Transformer and Generator Stator Failure on Hydropower Plant in Indonesia 印度尼西亚水电站变压器、发电机定子故障的根本原因分析

2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2018-07-01 DOI: 10.1109/ICITEED.2018.8534825

N. W. Priambodo, B. Harsono, B. S. Munir

{"title":"Root Cause Analysis of Transformer and Generator Stator Failure on Hydropower Plant in Indonesia","authors":"N. W. Priambodo, B. Harsono, B. S. Munir","doi":"10.1109/ICITEED.2018.8534825","DOIUrl":"https://doi.org/10.1109/ICITEED.2018.8534825","url":null,"abstract":"This paper presents an investigation related to the transformer and generator failure on a hydropower plant. Comprehensive visual inspection was conducted after the failure and the result showed visible dry band arcing mark along the surface of a transformer cable termination. Further analysis on transformer and generator historical assessment data followed by simulation process using apparatuses specification data and configuration were conducted to get possible root cause of the failure. Transformer historical assessment data showed abnormal result on insulation resistance test which increased the possibility of ground fault and also short circuit between high voltage and low voltage winding of the transformer during failure. According to ground fault and short circuit simulation between high voltage and low voltage winding of the transformer, the voltage at high voltage side of the transformer reached 1.73 times higher than the nominal value while the generator stator voltage reached over 7 times higher than the nominal value. Therefore, the possible cause of transformer and generator stator failure was internal ground fault and arcing between high voltage and low voltage winding of the transformer which caused flashover on cable termination attached to the high voltage side of the transformer and insulation breakdown of generator stator.","PeriodicalId":142523,"journal":{"name":"2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125837263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Impact of Piracy on Music Sales in Digital Music Transformation - A Systematic Literature Review 数字音乐转型中盗版对音乐销售的影响——系统文献综述

2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2018-07-01 DOI: 10.1109/ICITEED.2018.8534868

Nanang Husin, A. Hidayanto

引用次数: 1

Denoising Speech for MFCC Feature Extraction Using Wavelet Transformation in Speech Recognition System 语音识别系统中基于小波变换的MFCC特征提取去噪

2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2018-07-01 DOI: 10.1109/ICITEED.2018.8534807

Risanuri Hidayat, Agus Bejo, Sujoko Sumaryono, A. Winursito

{"title":"Denoising Speech for MFCC Feature Extraction Using Wavelet Transformation in Speech Recognition System","authors":"Risanuri Hidayat, Agus Bejo, Sujoko Sumaryono, A. Winursito","doi":"10.1109/ICITEED.2018.8534807","DOIUrl":"https://doi.org/10.1109/ICITEED.2018.8534807","url":null,"abstract":"Mel frequency cepstral coefficient (MFCC) is a popular feature extraction method for a speech recognition system. However, this method is susceptible to noise even though it generates a high accuracy. The conventional MFCC method has a degraded performance when the input signal has noises. This paper presents the implementation of denoising wavelet on speech input of MFCC feature extraction method. The addition of denoising process using wavelet transformation was expected to improve the MFCC performance on noisy signals. The study used 120 speech data, with 30 data were used as the reference, and the other 90 were used as the testing data. The testing data were mixed with white Gaussian noise and then tested to the speech recognition system that already had the reference data. Parameters used in the wavelet denoising process were soft thresholding with the Minimaxi thresholding rule. Eleven wavelet methods on decomposition level 10 were tested on the denoising process. The classification process used K-nearest neighbor (KNN) method. The Fejer-Korovkin 6 wavelet was the best denoising speech signal method that achieved the highest accuracy on input signals with SNR of 5-15dB. Meanwhile, the Daubechies 5 method had a high accuracy on input signal with SNR of 3 dB. All of the tested denoising methods using wavelet transformation were able to improve the accuracy of the speech recognition system on input signals with SNR of 0-10 dB compared to the system without denoising method.","PeriodicalId":142523,"journal":{"name":"2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122429820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 32

Maximum Allowable Intermittent Renewable Energy Source Penetration in Java-Bali Power System 爪哇-巴厘电力系统中最大允许间歇性可再生能源渗透

2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2018-07-01 DOI: 10.1109/ICITEED.2018.8534845

H. B. Tambunan, A. A. Kusuma, B. S. Munir

引用次数: 9

CNN Based Posture-Free Hand Detection 基于CNN的无姿势手部检测

2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2018-07-01 DOI: 10.1109/ICITEED.2018.8534743

Richard Adiguna, Y. Soelistio

引用次数: 3

Exploring practices and engagement of Instagram by Indonesia Government Ministries 探索印尼政府部门对Instagram的实践和参与

2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2018-07-01 DOI: 10.1109/ICITEED.2018.8534799

Achmad Fauzi Azmi, I. Budi

引用次数: 8

Comparative Analysis of Dispersion Compensating Fiber in DWDM System Using 10 Gbps and 40 Gbps Bit Rate 采用10gbps和40gbps码率的DWDM系统色散补偿光纤的比较分析

2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2018-07-01 DOI: 10.1109/ICITEED.2018.8534851

Fauza Khair, I. Mustika, Fahmi, D. Zulherman, Fakhriy Hario

{"title":"Comparative Analysis of Dispersion Compensating Fiber in DWDM System Using 10 Gbps and 40 Gbps Bit Rate","authors":"Fauza Khair, I. Mustika, Fahmi, D. Zulherman, Fakhriy Hario","doi":"10.1109/ICITEED.2018.8534851","DOIUrl":"https://doi.org/10.1109/ICITEED.2018.8534851","url":null,"abstract":"Chromatic dispersion becomes non-negligible in high bitrate and long-haul optical transmission that is necessary to compensate to maintain the system performance. One of the most effective and practical ways to compensate the chromatic dispersion is through Dispersion-Compensating Fiber (DCF) implementation for its negative dispersion to reduce the positive one in optical transmission. This paper presents the DCF implementation in DWDM transmission with bitrate and optical launch power variation. The DWDM model using 16 channels with channel spacing of 200 GHz, 300 km optical transmission length, and Erbium Doped Fiber Amplifier (EDFA) was implemented in OptiSystem. The system performance comparison was observed with bit error rate (BER), Q-factor, and received power for variation of the optical power launch -4, -2, 0, 2, 4, 6, 8, and 10 dBm at bitrate 10 Gbps and 40 Gbps. Based on the results, all of the 16 channels using DCF at bitrate 10 Gbps and 40 Gbps completely reduced the dispersion. The optical power launch remarkably affected the system performance in high bitrate.","PeriodicalId":142523,"journal":{"name":"2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130427728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Development of Enterprise Security Framework in SKK Migas Based on Integration of ISO 27000 and SABSA Model 基于ISO 27000和SABSA模型集成的SKK Migas企业安全框架开发

2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2018-07-01 DOI: 10.1109/ICITEED.2018.8534747

W. Najib, Sujoko Sumaryono, L. Nugroho, G. D. Putra

引用次数: 1

How SVM Can Compensate Logit Based Response Label with Various Characteristics in Predictor? A Simulation Study 支持向量机如何补偿预测器中具有不同特征的Logit响应标签?模拟研究

2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2018-07-01 DOI: 10.1109/ICITEED.2018.8534762

M. A. A. Riyadi, D. Prastyo, S. W. Purnami

{"title":"How SVM Can Compensate Logit Based Response Label with Various Characteristics in Predictor? A Simulation Study","authors":"M. A. A. Riyadi, D. Prastyo, S. W. Purnami","doi":"10.1109/ICITEED.2018.8534762","DOIUrl":"https://doi.org/10.1109/ICITEED.2018.8534762","url":null,"abstract":"In general, supervised machine learning methods for classification can be categorized into two approaches, namely parametric and nonparametric. Parametric method has limitations in term of the assumptions must be satisfied. One way to handle this problem is using non parametric approaches. The state of the art classification method is support vector machine (SVM). However, the computational burden of kernel SVM limits its application to large scale datasets that demand high computational time. So, one way to cope the limitation is using ensemble approach that splits the data and applies learning procedure at each subset of data. In this work, the Clustered Support Vector Machine (CSVM) is chosen. So far, the studies of CSVM are limited to theoretical and direct application for real dataset. The application to real dataset directly has a weakness that we never know in detail how various characteristic in predictor affect the learning process. So, it is necessary to do a simulation study to further explore how complex the data, particularly in predictor, that can be handled by SVM and CSVM. There are ten scenarios conducted in this simulation study. The response label is generated using Iogistic regression model with various characteristic setting in predictor in each scenario. Given the true response label is generated using Iogit model, the results of this simulation study show that SVM and CSVM can compensate the performance of Iogistic regression in some scenarios. These results showed that SVM is powerful in classification method regardless how the response label is generated.","PeriodicalId":142523,"journal":{"name":"2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115364303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

DFT-Based Channel Estimation for GFDM on Multipath Channels 多径信道下基于dft的GFDM信道估计

2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2018-07-01 DOI: 10.1109/ICITEED.2018.8534919

Al Kautsar Permana, Effrina Yanti Hamid

引用次数: 2