Pub Date : 2020-12-10DOI: 10.1109/ISRITI51436.2020.9315412
Muhammad Farin Akhsanta, S. Suyanto
The Speaker identification system is widely applied in various fields to detect the identity of a person by detecting the sound signal energy released by a person and not driven by a particular text. The challenges are how to differentiate the voices characteristic of the speaker, such as intonation style, rhythm, the pattern of pronunciation, accent, and vocabulary. In this paper, a speaker identification system using Principal Component Analysis (PCA) and Support Vector Machine (SVM) is developed. Besides, the Mel Frequency Cepstral Coefficient (MFCC) is used as the feature extraction. The system is then evaluated using unseen noisy utterances with various signal-noise ratio (SNR). The evaluation is performed using a confusion matrix to calculate the accuracy, precision, and recall to determine the relevance of the output results on the system. Experimental results show that the developed system is quite robust. It is capable of identifying speakers with high performance, an accuracy of 88.97%, a precision of 91,87%, and a recall of 94,39%, for a low noise level with SNR of 15dB. The performance slowly decreases as the noise level increases. For a high noise level with SNR of up to 0dB, it is still able to recognize the unseen speakers with an average accuracy of 70.93%, precision of 74.68%, and recall of 83.51%.
{"title":"Text-Independent Speaker Identification Using PCA-SVM Model","authors":"Muhammad Farin Akhsanta, S. Suyanto","doi":"10.1109/ISRITI51436.2020.9315412","DOIUrl":"https://doi.org/10.1109/ISRITI51436.2020.9315412","url":null,"abstract":"The Speaker identification system is widely applied in various fields to detect the identity of a person by detecting the sound signal energy released by a person and not driven by a particular text. The challenges are how to differentiate the voices characteristic of the speaker, such as intonation style, rhythm, the pattern of pronunciation, accent, and vocabulary. In this paper, a speaker identification system using Principal Component Analysis (PCA) and Support Vector Machine (SVM) is developed. Besides, the Mel Frequency Cepstral Coefficient (MFCC) is used as the feature extraction. The system is then evaluated using unseen noisy utterances with various signal-noise ratio (SNR). The evaluation is performed using a confusion matrix to calculate the accuracy, precision, and recall to determine the relevance of the output results on the system. Experimental results show that the developed system is quite robust. It is capable of identifying speakers with high performance, an accuracy of 88.97%, a precision of 91,87%, and a recall of 94,39%, for a low noise level with SNR of 15dB. The performance slowly decreases as the noise level increases. For a high noise level with SNR of up to 0dB, it is still able to recognize the unseen speakers with an average accuracy of 70.93%, precision of 74.68%, and recall of 83.51%.","PeriodicalId":325920,"journal":{"name":"2020 3rd International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126035942","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}
Pub Date : 2020-12-10DOI: 10.1109/ISRITI51436.2020.9315353
Arif Sudaryanto, E. Purwanto, I. Ferdiansyah, Syechu Dwitya Nugraha, O. Qudsi, M. Rifadil, M. R. Rusli
The electric motor has replaced motor fuel as the main mover of the equipment. One of them is the use of a three-phase induction motor in the industrial sector. Equipment in an industry requires many speed controllers in operation. The induction motor speed can be changed by changing the number of poles, changing the stator voltage, and changing the frequency source. This method has many disadvantages, such as changes in motor dimensions and the occurrence of flux saturation. This paper provides method of controlling the speed of a three-phase induction motor with constant V/f. Speed regulation with constant V/f can prevent saturation flux when changing the input frequency and can maintain maximum motor torque along the speed regulation area. The speed regulation use an inverter Three-phase SVPWM by implementing PI control. The results of using constant V/f control show that motor speed response at 1300 rpm has a rise time of 0.13 second, a settling time of 0.164 second, an overshoot of 0%, and a THD of 19.26%.
{"title":"Design and Implementation of SVPWM Inverter to Reduce Total Harmonic Distortion (THD) on Three Phase Induction Motor Speed Regulation Using Constant V/F","authors":"Arif Sudaryanto, E. Purwanto, I. Ferdiansyah, Syechu Dwitya Nugraha, O. Qudsi, M. Rifadil, M. R. Rusli","doi":"10.1109/ISRITI51436.2020.9315353","DOIUrl":"https://doi.org/10.1109/ISRITI51436.2020.9315353","url":null,"abstract":"The electric motor has replaced motor fuel as the main mover of the equipment. One of them is the use of a three-phase induction motor in the industrial sector. Equipment in an industry requires many speed controllers in operation. The induction motor speed can be changed by changing the number of poles, changing the stator voltage, and changing the frequency source. This method has many disadvantages, such as changes in motor dimensions and the occurrence of flux saturation. This paper provides method of controlling the speed of a three-phase induction motor with constant V/f. Speed regulation with constant V/f can prevent saturation flux when changing the input frequency and can maintain maximum motor torque along the speed regulation area. The speed regulation use an inverter Three-phase SVPWM by implementing PI control. The results of using constant V/f control show that motor speed response at 1300 rpm has a rise time of 0.13 second, a settling time of 0.164 second, an overshoot of 0%, and a THD of 19.26%.","PeriodicalId":325920,"journal":{"name":"2020 3rd International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"30 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128590005","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}
Pub Date : 2020-12-10DOI: 10.1109/ISRITI51436.2020.9315424
Farah Nur Alfi, M. Anggraeni, Rosiyah Faradisa
Indonesia established Analog Switch-Off (ASO) in 2018 and was not fully implemented. In this study, we assessed the quality of terrestrial digital TV from end-users, which was also complemented by field measurements of CNR, SNR, and BER values. Based on the results of the assessment, shown 59% of respondents still use analog TV. The TV migration process in Indonesia has not been widely known by the public, 78% of respondents are not aware of the ASO condition, and 74% of respondents claim to have never heard of digital terrestrial TV. More than 50% of respondents of terrestrial digital TV users stated that experienced broadcast dropouts and almost 50% experienced broadcast delays. This relates to the results of field measurements based on a technology-centered approach that shows a higher bit error rate than the simulation data, blank spots at two points, and are still points that classified as low signal categories.
{"title":"Quality Assessment of Digital Terrestrial Television Broadcast in Surabaya","authors":"Farah Nur Alfi, M. Anggraeni, Rosiyah Faradisa","doi":"10.1109/ISRITI51436.2020.9315424","DOIUrl":"https://doi.org/10.1109/ISRITI51436.2020.9315424","url":null,"abstract":"Indonesia established Analog Switch-Off (ASO) in 2018 and was not fully implemented. In this study, we assessed the quality of terrestrial digital TV from end-users, which was also complemented by field measurements of CNR, SNR, and BER values. Based on the results of the assessment, shown 59% of respondents still use analog TV. The TV migration process in Indonesia has not been widely known by the public, 78% of respondents are not aware of the ASO condition, and 74% of respondents claim to have never heard of digital terrestrial TV. More than 50% of respondents of terrestrial digital TV users stated that experienced broadcast dropouts and almost 50% experienced broadcast delays. This relates to the results of field measurements based on a technology-centered approach that shows a higher bit error rate than the simulation data, blank spots at two points, and are still points that classified as low signal categories.","PeriodicalId":325920,"journal":{"name":"2020 3rd International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132993610","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}
Pub Date : 2020-12-10DOI: 10.1109/ISRITI51436.2020.9315411
M. H. Ibrahim, A. Hanifa, S. Pramono, M. E. Sulistyo, I. Iftadi
Bit error rate (BER) is a fundamental performance measurement of data transmission and communication link. BER measures. Incorporating with digital baseband processing in transceiver, BER measurement can be integrated in a field programmable gate array (FPGA). A Cyclone IV E EP4CE115 is implemented as BER tester to measure performance of visible light communication (VLC) link. The flexibility of FPGA allows the proposed BER measurement system design to add features such as pseudo random bit sequence (PRBS) generator, burst error generator and delay control for synchronization. It shows that design capable to measure VLC link up to 2 Mbps due to limitation of VLC analog front end (AFE).
误码率是衡量数据传输和通信链路性能的基本指标。方方面面的措施。结合收发器中的数字基带处理，可以将误码率测量集成到现场可编程门阵列(FPGA)中。采用Cyclone IV E EP4CE115作为误码率测试仪，测量可见光通信(VLC)链路的性能。FPGA的灵活性允许所提出的误码率测量系统设计增加诸如伪随机比特序列(PRBS)发生器、突发错误发生器和同步延迟控制等功能。结果表明，由于VLC模拟前端(AFE)的限制，该设计只能测量高达2mbps的VLC链路。
{"title":"Design and Development of Bit Error Measurement using FPGA for Visible Light Communication","authors":"M. H. Ibrahim, A. Hanifa, S. Pramono, M. E. Sulistyo, I. Iftadi","doi":"10.1109/ISRITI51436.2020.9315411","DOIUrl":"https://doi.org/10.1109/ISRITI51436.2020.9315411","url":null,"abstract":"Bit error rate (BER) is a fundamental performance measurement of data transmission and communication link. BER measures. Incorporating with digital baseband processing in transceiver, BER measurement can be integrated in a field programmable gate array (FPGA). A Cyclone IV E EP4CE115 is implemented as BER tester to measure performance of visible light communication (VLC) link. The flexibility of FPGA allows the proposed BER measurement system design to add features such as pseudo random bit sequence (PRBS) generator, burst error generator and delay control for synchronization. It shows that design capable to measure VLC link up to 2 Mbps due to limitation of VLC analog front end (AFE).","PeriodicalId":325920,"journal":{"name":"2020 3rd International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133438444","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}
Pub Date : 2020-12-10DOI: 10.1109/ISRITI51436.2020.9315465
S. Zahara, Sugianto
Multivariate time series forecasting affords an opportunity to forecast future recent trends or possibility incident based on historical observations. Forecasting in economic world becomes global interest particularly for researchers seeking for best accuracy result using several methods. Consumer Price Index is the primary instrument used by central banks to set inflation targets. However, most of previous studies commonly only used univariate factor to forecast Consumer Price Index. Furthermore, mostly model development of forecasting system is done by personal and physical server facing the problem of impractical yet time consuming. Since measuring method of Consumer Price Index commonly is pick an average of the period-to-period price move for the different products, we conducted multivariate Consumer Price Index forecasting based Cloud Computing utilizing 28 types of Surabaya daily food price from 2014 to 2018 using Multilayer Perceptron and Long Short Term Memory (LSTM) of deep learning. Furthermore, we implement architectural variations of the number of neurons, epoch, and hidden layers. The whole development of forecasting system is built in Amazon Web Service (AWS) Cloud. The result indicated the best accuracy value was obtained from the Multilayer Perceptron with 3.380 of RMSE consist of a configuration of 2 hidden layers, 10 neurons of first hidden layer, 10 neurons of second hidden layer also 1000 of epoch.
{"title":"Multivariate Time Series Forecasting Based Cloud Computing For Consumer Price Index Using Deep Learning Algorithms","authors":"S. Zahara, Sugianto","doi":"10.1109/ISRITI51436.2020.9315465","DOIUrl":"https://doi.org/10.1109/ISRITI51436.2020.9315465","url":null,"abstract":"Multivariate time series forecasting affords an opportunity to forecast future recent trends or possibility incident based on historical observations. Forecasting in economic world becomes global interest particularly for researchers seeking for best accuracy result using several methods. Consumer Price Index is the primary instrument used by central banks to set inflation targets. However, most of previous studies commonly only used univariate factor to forecast Consumer Price Index. Furthermore, mostly model development of forecasting system is done by personal and physical server facing the problem of impractical yet time consuming. Since measuring method of Consumer Price Index commonly is pick an average of the period-to-period price move for the different products, we conducted multivariate Consumer Price Index forecasting based Cloud Computing utilizing 28 types of Surabaya daily food price from 2014 to 2018 using Multilayer Perceptron and Long Short Term Memory (LSTM) of deep learning. Furthermore, we implement architectural variations of the number of neurons, epoch, and hidden layers. The whole development of forecasting system is built in Amazon Web Service (AWS) Cloud. The result indicated the best accuracy value was obtained from the Multilayer Perceptron with 3.380 of RMSE consist of a configuration of 2 hidden layers, 10 neurons of first hidden layer, 10 neurons of second hidden layer also 1000 of epoch.","PeriodicalId":325920,"journal":{"name":"2020 3rd International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130520228","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}
Pub Date : 2020-12-10DOI: 10.1109/ISRITI51436.2020.9315417
Radityo Putro Wibisono, P. Rusmin, S. Notodarmojo
Internet of Things (IoT) is a concept that aims to expand the benefits of continuously connected internet connectivity, while Artificial Intelligence is intelligence that is created and inserted into a machine to do work like humans do. In this study, a prototype system was built that can control the requirement of chemicals for the coagulation process based on measuring the quality of raw water in the PDAM intake channel using several sensor parameters including Turbidity, pH, and Dissolved Oxygen (DO), by utilizing Internet of Things (IoT) communication. System processing is carried out by a microcontroller. The Artificial Neural Network (ANN) method is used to determine the amount of chemicals or coagulants required for the coagulation process based on raw water quality data, this system can also display raw water quality monitoring data from all sensor parameters used and the status of the dosing pump by IoT communications. By using this system, the amount of doses of chemicals or coagulants used in coagulation through the intake will be more optimal when compared to the current system.
{"title":"Optimization Coagulation Process of Water Treatment Plant Using Neural Network and Internet of Things (IoT) Communication","authors":"Radityo Putro Wibisono, P. Rusmin, S. Notodarmojo","doi":"10.1109/ISRITI51436.2020.9315417","DOIUrl":"https://doi.org/10.1109/ISRITI51436.2020.9315417","url":null,"abstract":"Internet of Things (IoT) is a concept that aims to expand the benefits of continuously connected internet connectivity, while Artificial Intelligence is intelligence that is created and inserted into a machine to do work like humans do. In this study, a prototype system was built that can control the requirement of chemicals for the coagulation process based on measuring the quality of raw water in the PDAM intake channel using several sensor parameters including Turbidity, pH, and Dissolved Oxygen (DO), by utilizing Internet of Things (IoT) communication. System processing is carried out by a microcontroller. The Artificial Neural Network (ANN) method is used to determine the amount of chemicals or coagulants required for the coagulation process based on raw water quality data, this system can also display raw water quality monitoring data from all sensor parameters used and the status of the dosing pump by IoT communications. By using this system, the amount of doses of chemicals or coagulants used in coagulation through the intake will be more optimal when compared to the current system.","PeriodicalId":325920,"journal":{"name":"2020 3rd International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126137791","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}
Pub Date : 2020-12-10DOI: 10.1109/ISRITI51436.2020.9315344
S. Sa'adah, Melati Suci Pratiwi
Development of technology have influenced all aspect, especially in financial sector in this pandemic situation, where most people tend to use digital money to conduct daily financial transactions. In one side, there is security point that need to be concern much. Like several disadvantages using credit cards by undue owners, social engineering, and transactions to commit fraud. In this paper, PaySim Mobile Money Simulator data is used with a machine learning algorithm called probabilistic neural network (PNN) to classify whether the customer's actions are normal or fraudulent actions. This PNN approach combined using binary classification to prevent fraudulent actions in transactions that have been or are being used by customers. And the result indicated that this system able to classify class 0 (as a normal class customer) and 1 (as a fraudulent class customer). Based on this result, maybe it would help many sectors that involved as a tool to classify a genuine customer. Especially in this pandemic covid-19, the fraud needs to detect often, to mitigate the fraud early.
{"title":"Classification of Customer Actions on Digital Money Transactions on PaySim Mobile Money Simulator using Probabilistic Neural Network (PNN) Algorithm","authors":"S. Sa'adah, Melati Suci Pratiwi","doi":"10.1109/ISRITI51436.2020.9315344","DOIUrl":"https://doi.org/10.1109/ISRITI51436.2020.9315344","url":null,"abstract":"Development of technology have influenced all aspect, especially in financial sector in this pandemic situation, where most people tend to use digital money to conduct daily financial transactions. In one side, there is security point that need to be concern much. Like several disadvantages using credit cards by undue owners, social engineering, and transactions to commit fraud. In this paper, PaySim Mobile Money Simulator data is used with a machine learning algorithm called probabilistic neural network (PNN) to classify whether the customer's actions are normal or fraudulent actions. This PNN approach combined using binary classification to prevent fraudulent actions in transactions that have been or are being used by customers. And the result indicated that this system able to classify class 0 (as a normal class customer) and 1 (as a fraudulent class customer). Based on this result, maybe it would help many sectors that involved as a tool to classify a genuine customer. Especially in this pandemic covid-19, the fraud needs to detect often, to mitigate the fraud early.","PeriodicalId":325920,"journal":{"name":"2020 3rd International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126182577","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}
Pub Date : 2020-12-10DOI: 10.1109/ISRITI51436.2020.9315421
Nomarhinta Solihah, M. I. Nashiruddin, Eliandri Shintani Wulandari
Video services on Passive Optical Networks (PON) are widely used for the IPTV multicast services and proliferating. One of the new PON technologies used by telecommunication operators in Indonesia is the 10-Gigabit-capable symmetric passive optical network (XGS-PON). However, there is no technical standardization related to multicast services on the XGS-PON system. Therefore, this study will develop a test method and evaluate multicast services' performance on Optical Line Termination (OLT) equipment of XGS-PON. The OLT has the most critical function in managing services, including distributing Internet Protocol Television (IPTV) service to customers. Six parameters proposed as standardization regulation to determine the XGS-PON OLT capability are as follows: IGMP version 2, IGMP version 3, IGMP Proxy, IGMP transparent snooping, IGMP snooping with proxy reporting, and IGMP Multicast Group. The experiment result confirmed that XGS-PON OLT supports multicast protocols following ITU-T G.9807.1 recommendations, namely IGMP version 2 and IGMP version 3. It also shows that XGS-PON OLT supports IGMP mode capabilities such as IGMP proxy mode, IGMP transparent snooping mode, and IGMP snooping with proxy reporting. Furthermore, XGS-PON OLT supports the maximum number of multicast groups simultaneously for 2048 IGMP multicast groups following the TR-101 guideline from Broadband Forum. These results can be used as a reference for technical standardization regulations development of IPTV multicast service in XGS-PON.
无源光网络(PON)上的视频业务在IPTV组播业务中得到了广泛的应用并呈激增趋势。印尼电信运营商使用的一种新型PON技术是10千兆对称无源光网络(XGS-PON)。但是，在XGS-PON系统上没有与组播业务相关的技术标准化。因此，本研究将开发一种测试方法并评估多播业务在XGS-PON光线路终端(OLT)设备上的性能。OLT在业务管理中具有最关键的功能，包括向客户分发IPTV (Internet Protocol Television)业务。作为决定XGS-PON OLT能力的标准化规则，提出了6个参数:IGMP version 2、IGMP version 3、IGMP Proxy、IGMP transparent snooping、IGMP snooping with Proxy reporting、IGMP Multicast Group。实验结果证实，XGS-PON OLT支持符合ITU-T G.9807.1推荐的组播协议，即IGMP version 2和IGMP version 3。同时也说明了XGS-PON OLT支持IGMP模式的功能，如IGMP代理模式、IGMP透明snooping模式、带代理报告的IGMP snooping等。此外，XGS-PON OLT还支持2048个IGMP组播组同时组播组的最大数量，遵循宽带论坛TR-101指南。研究结果可为XGS-PON中IPTV组播业务的技术标准化规程制定提供参考。
{"title":"Performance Evaluation of IPTV Multicast Service Testing for XGS-PON Optical Line Termination","authors":"Nomarhinta Solihah, M. I. Nashiruddin, Eliandri Shintani Wulandari","doi":"10.1109/ISRITI51436.2020.9315421","DOIUrl":"https://doi.org/10.1109/ISRITI51436.2020.9315421","url":null,"abstract":"Video services on Passive Optical Networks (PON) are widely used for the IPTV multicast services and proliferating. One of the new PON technologies used by telecommunication operators in Indonesia is the 10-Gigabit-capable symmetric passive optical network (XGS-PON). However, there is no technical standardization related to multicast services on the XGS-PON system. Therefore, this study will develop a test method and evaluate multicast services' performance on Optical Line Termination (OLT) equipment of XGS-PON. The OLT has the most critical function in managing services, including distributing Internet Protocol Television (IPTV) service to customers. Six parameters proposed as standardization regulation to determine the XGS-PON OLT capability are as follows: IGMP version 2, IGMP version 3, IGMP Proxy, IGMP transparent snooping, IGMP snooping with proxy reporting, and IGMP Multicast Group. The experiment result confirmed that XGS-PON OLT supports multicast protocols following ITU-T G.9807.1 recommendations, namely IGMP version 2 and IGMP version 3. It also shows that XGS-PON OLT supports IGMP mode capabilities such as IGMP proxy mode, IGMP transparent snooping mode, and IGMP snooping with proxy reporting. Furthermore, XGS-PON OLT supports the maximum number of multicast groups simultaneously for 2048 IGMP multicast groups following the TR-101 guideline from Broadband Forum. These results can be used as a reference for technical standardization regulations development of IPTV multicast service in XGS-PON.","PeriodicalId":325920,"journal":{"name":"2020 3rd International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127178515","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}
Pub Date : 2020-12-10DOI: 10.1109/ISRITI51436.2020.9315347
B. L. Widjiantoro, K. Indriawati, Egy Josua Simbolon
In this research, speed sensorless control design for induction motors is done by using the Particle Filter algorithm (PF) as a speed estimator and Direct Torque Control (DTC) as a control scheme used to control the speed of an induction motor. For testing with a close loop control system, the test range is at speeds of 50 to 500 rpm, with a steady state error obtained less than 5%. Based on the value of the error obtained it can be said that the design of the speed sensorless control for the induction motor is running well, however at high speeds such as 350 and 500 rpm the results obtained have a high overshoot value and a long settling time.
{"title":"Particle Filter Based Speed Estimator for Speed Sensorless Control in Induction Motor","authors":"B. L. Widjiantoro, K. Indriawati, Egy Josua Simbolon","doi":"10.1109/ISRITI51436.2020.9315347","DOIUrl":"https://doi.org/10.1109/ISRITI51436.2020.9315347","url":null,"abstract":"In this research, speed sensorless control design for induction motors is done by using the Particle Filter algorithm (PF) as a speed estimator and Direct Torque Control (DTC) as a control scheme used to control the speed of an induction motor. For testing with a close loop control system, the test range is at speeds of 50 to 500 rpm, with a steady state error obtained less than 5%. Based on the value of the error obtained it can be said that the design of the speed sensorless control for the induction motor is running well, however at high speeds such as 350 and 500 rpm the results obtained have a high overshoot value and a long settling time.","PeriodicalId":325920,"journal":{"name":"2020 3rd International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121819269","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}
Pub Date : 2020-12-10DOI: 10.1109/ISRITI51436.2020.9315461
A. Sultoni, L. Hanafi, Zaenal Panutup Aji
Maximum Power Point Tracking (MPPT) is used to find and maintain the maximum power output from photovoltaic array due to weather changing. MPPT works by observe the power located at peak or not, by add disturbance signal. In this paper, We design fuzzy-PID MPPT charge controller for 1.75 KWP photovoltaic system with stand alone configuration. The array consists of 6 modules @280kWP in series configuration. Output power is compared with existing MPPT charge controller. Result shows that the proposed design increases PDC 14% compare to existing MPPT charge controller.
最大功率点跟踪(Maximum Power Point Tracking, MPPT)用于寻找并保持光伏阵列在天气变化时的最大功率输出。MPPT的工作原理是观察功率是否处于峰值位置，加入干扰信号。本文针对单机配置的1.75 KWP光伏系统，设计了模糊pid MPPT充电控制器。该阵列由6个@280kWP模块串联配置而成。输出功率与现有的MPPT充电控制器进行了比较。结果表明，与现有的MPPT充电控制器相比，所设计的充电控制器的PDC值提高了14%。
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