Pub Date : 2018-08-01DOI: 10.1109/ISITIA.2018.8711115
Eko Prasetyo, R. Adityo, N. Suciati, C. Fatichah
The previous research in mango leaf classification which used 270 features consisted of 256 texture features, 2 color features, and 2 shape features, could not achieve high classification performance. In this study, we conduct improvement by combining the previous features with the Boundary Moments of Centroid Contour Distance (CCD) and classify the combination features using Support Vector Machine with Linear and RBF kernels. The experiment results show that the combination features achieve higher classification performance compared to the previous features.
{"title":"Mango Leaf Classification with Boundary Moments of Centroid Contour Distances as Shape Features","authors":"Eko Prasetyo, R. Adityo, N. Suciati, C. Fatichah","doi":"10.1109/ISITIA.2018.8711115","DOIUrl":"https://doi.org/10.1109/ISITIA.2018.8711115","url":null,"abstract":"The previous research in mango leaf classification which used 270 features consisted of 256 texture features, 2 color features, and 2 shape features, could not achieve high classification performance. In this study, we conduct improvement by combining the previous features with the Boundary Moments of Centroid Contour Distance (CCD) and classify the combination features using Support Vector Machine with Linear and RBF kernels. The experiment results show that the combination features achieve higher classification performance compared to the previous features.","PeriodicalId":388463,"journal":{"name":"2018 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133029095","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 : 2018-08-01DOI: 10.1109/ISITIA.2018.8710837
Miftah Rahmalia Arivati, A. Nasution
Studies on the classification of heart rhythms from Electrocardiogram (ECG) signal interpretation have been widely reported. Several techniques for recognizing the abnormalities on left bundle branch (LBBB), right bundle branch (RBBB) and premature ventricular contraction (PVC) using the Taguchi optimization method and the Naïve Bayes classification method have been reported. Unfortunately results from the Naïve Bayes classification method are not as good as those using method such as SVM classification method. In the paper we propose a Hybrid PSO-Neural Network (NN) as a classification method and a Neural Independent Component Analysis (Neural-ICA) as a filter method. Neural ICA aims to separate the original signal and the noise signal on the ECG signal record. In this research the ICA method implements the Neural algorithm for the process of updating the weights after filter process. The Hybrid PSO-Neural Network is a Neural Network method that optimized by PSO to optimize the classification result. Hybrid PSO-NN method can improve the classification accuracy up to 2%, i.e. 99% accuracy, in comparison to NN method 98% accuracy and SVM method 96% accuracy, respectively.
{"title":"Heart Rhythm Classification from Electrocardiogram Signals Using Hybrid PSO-Neural Network Method and Neural ICA","authors":"Miftah Rahmalia Arivati, A. Nasution","doi":"10.1109/ISITIA.2018.8710837","DOIUrl":"https://doi.org/10.1109/ISITIA.2018.8710837","url":null,"abstract":"Studies on the classification of heart rhythms from Electrocardiogram (ECG) signal interpretation have been widely reported. Several techniques for recognizing the abnormalities on left bundle branch (LBBB), right bundle branch (RBBB) and premature ventricular contraction (PVC) using the Taguchi optimization method and the Naïve Bayes classification method have been reported. Unfortunately results from the Naïve Bayes classification method are not as good as those using method such as SVM classification method. In the paper we propose a Hybrid PSO-Neural Network (NN) as a classification method and a Neural Independent Component Analysis (Neural-ICA) as a filter method. Neural ICA aims to separate the original signal and the noise signal on the ECG signal record. In this research the ICA method implements the Neural algorithm for the process of updating the weights after filter process. The Hybrid PSO-Neural Network is a Neural Network method that optimized by PSO to optimize the classification result. Hybrid PSO-NN method can improve the classification accuracy up to 2%, i.e. 99% accuracy, in comparison to NN method 98% accuracy and SVM method 96% accuracy, respectively.","PeriodicalId":388463,"journal":{"name":"2018 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131502407","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 : 2018-08-01DOI: 10.1109/ISITIA.2018.8711225
Y. U. Nugraha, M. N. Yuniarto, Herviyandi Herizal, D. A. Asfani, D. Riawan, M. Wahyudi
The design of an optimal BLDC motor with high efficiency is the most important thing especially for electric scooter application since its performance is very depended on power output of BLDC. This paper presented design of 5 kW axial flux permanent magnet of BLDC motor based on Solidwork and Ansys Maxwell. The motor parameters were designed by modeling of physical parameters through calculation, such as number of pole, stator core diameter, and selection of material type. These physical parameters are then designed its blueprint through Solidwork and simulated through Ansys Maxwell with Rmxprt (Rotational Machine Expert) feature. The analyzed electrical parameters were speed, efficiency, flux density, and losses. The results showed the designed axial flux permanent magnet motor BLDC with 12 slot stator and 8 pole rotor presented the torque = 9.5 Nm, rated speed = 5050 rpm, and motor efficiency = 94.49 %.
{"title":"Design Analysis of Axial Flux Permanent Magnet BLDC Motor 5 kW for Electric Scooter Application","authors":"Y. U. Nugraha, M. N. Yuniarto, Herviyandi Herizal, D. A. Asfani, D. Riawan, M. Wahyudi","doi":"10.1109/ISITIA.2018.8711225","DOIUrl":"https://doi.org/10.1109/ISITIA.2018.8711225","url":null,"abstract":"The design of an optimal BLDC motor with high efficiency is the most important thing especially for electric scooter application since its performance is very depended on power output of BLDC. This paper presented design of 5 kW axial flux permanent magnet of BLDC motor based on Solidwork and Ansys Maxwell. The motor parameters were designed by modeling of physical parameters through calculation, such as number of pole, stator core diameter, and selection of material type. These physical parameters are then designed its blueprint through Solidwork and simulated through Ansys Maxwell with Rmxprt (Rotational Machine Expert) feature. The analyzed electrical parameters were speed, efficiency, flux density, and losses. The results showed the designed axial flux permanent magnet motor BLDC with 12 slot stator and 8 pole rotor presented the torque = 9.5 Nm, rated speed = 5050 rpm, and motor efficiency = 94.49 %.","PeriodicalId":388463,"journal":{"name":"2018 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115451437","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 : 2018-08-01DOI: 10.1109/isitia.2018.8710828
Muhammad Rizki Nurriansyah, A. Sudarmaji, D. Handoko, Luthfi Azmaiza Hadsyah, Arnold Fedriko
In this research, an optical system is made and aims for Faraday rotation apparatus. This system was designed and made to measure the rotation angle of plane of polarization on analyzer, light intensity, and value of magnetic field, where as the analyzer angle setting is done by using a stepper motor which connected to the lens of analyzer by a gear set, for the light intensity the writer measured it with a lux meter IC BH1750, and the magnetic field measured based on the current which given by constant current power supply. Number of pulses on the stepper motor and the data from the IC BH1750 is being acquired using a microcontroller. In this research, the writer used two variable wave length from different color on 30 watt LED as the light sources, all of these light sources are being controlled by the microcontroller. Based on this research, the writer conclude that there are transfer function (p= 17.832θ), where (θ) is the rotation angle of analyzer and (P) is the pulse that is generated from the stepper motor. All of the control system is controlled by a microcontroller that is integrated with the computer.
{"title":"Design and Data Acquisition of Faraday Rotation Instrumentation System Based on Microcontroller","authors":"Muhammad Rizki Nurriansyah, A. Sudarmaji, D. Handoko, Luthfi Azmaiza Hadsyah, Arnold Fedriko","doi":"10.1109/isitia.2018.8710828","DOIUrl":"https://doi.org/10.1109/isitia.2018.8710828","url":null,"abstract":"In this research, an optical system is made and aims for Faraday rotation apparatus. This system was designed and made to measure the rotation angle of plane of polarization on analyzer, light intensity, and value of magnetic field, where as the analyzer angle setting is done by using a stepper motor which connected to the lens of analyzer by a gear set, for the light intensity the writer measured it with a lux meter IC BH1750, and the magnetic field measured based on the current which given by constant current power supply. Number of pulses on the stepper motor and the data from the IC BH1750 is being acquired using a microcontroller. In this research, the writer used two variable wave length from different color on 30 watt LED as the light sources, all of these light sources are being controlled by the microcontroller. Based on this research, the writer conclude that there are transfer function (p= 17.832θ), where (θ) is the rotation angle of analyzer and (P) is the pulse that is generated from the stepper motor. All of the control system is controlled by a microcontroller that is integrated with the computer.","PeriodicalId":388463,"journal":{"name":"2018 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115654708","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 : 2018-08-01DOI: 10.1109/ISITIA.2018.8710761
Brian Raafiu, P. A. Darwito
Technology Four Wheel Mobile Robotic is a choice with a variety of the functions in the industry and the application of the other, reliability and intelligence system of wheeled mobile robot become an option on a 4.0 generation industry. Stabilization of four-wheel mobile robot is an important case for the system control of the mobile robot. This paper presents system identification process of Four Wheel Mobile Robot (FWMR). In the first phase, it is investigating a part of the system as multi-input single output (MISO) system. The current and duty cycle of motors as input, and speed of rotation wheel as outputs. Model of Four Wheel Mobile Robot is constructed by parametric models in system identification. There are two parametric models used in this study, those are autoregressive exogenous (ARX) and autoregressive moving average exogenous (ARMAX). The models were designed using m-file of the parametric model. The best result models Four Wheel Mobile Robot are ARX model with first-order structure (FIT= 98,11% and ARMAX model with second order structure (FIT= 95,30%. The ARX model shows the best model for Four Wheel Mobile Robot (FWMR) system.
{"title":"Identification of Four Wheel Mobile Robot based on Parametric Modelling","authors":"Brian Raafiu, P. A. Darwito","doi":"10.1109/ISITIA.2018.8710761","DOIUrl":"https://doi.org/10.1109/ISITIA.2018.8710761","url":null,"abstract":"Technology Four Wheel Mobile Robotic is a choice with a variety of the functions in the industry and the application of the other, reliability and intelligence system of wheeled mobile robot become an option on a 4.0 generation industry. Stabilization of four-wheel mobile robot is an important case for the system control of the mobile robot. This paper presents system identification process of Four Wheel Mobile Robot (FWMR). In the first phase, it is investigating a part of the system as multi-input single output (MISO) system. The current and duty cycle of motors as input, and speed of rotation wheel as outputs. Model of Four Wheel Mobile Robot is constructed by parametric models in system identification. There are two parametric models used in this study, those are autoregressive exogenous (ARX) and autoregressive moving average exogenous (ARMAX). The models were designed using m-file of the parametric model. The best result models Four Wheel Mobile Robot are ARX model with first-order structure (FIT= 98,11% and ARMAX model with second order structure (FIT= 95,30%. The ARX model shows the best model for Four Wheel Mobile Robot (FWMR) system.","PeriodicalId":388463,"journal":{"name":"2018 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"369 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116539043","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 : 2018-08-01DOI: 10.1109/isitia.2018.8711237
Nazmia Kurniawati, A. Affandi, I. Pratomo, K. Gyoda
More than half of Indonesia area haven't covered by the mobile network. Therefore an ad-hoc network delivering VoIP technology can be the solution for this problem. This paper presents the research using Raspberry Pi with Kamailio SIP server and OLSR routing protocol. From the experiment, the network performance shows a satisfying result when compared to the standard made by Indonesian Ministry of Communication and Informatics. Considering Raspberry Pi capability and experiment result, it is possible to use Raspberry Pi for VoIP system in the rural area.
{"title":"Raspberry Pi-Based VoIP System For Rural Area","authors":"Nazmia Kurniawati, A. Affandi, I. Pratomo, K. Gyoda","doi":"10.1109/isitia.2018.8711237","DOIUrl":"https://doi.org/10.1109/isitia.2018.8711237","url":null,"abstract":"More than half of Indonesia area haven't covered by the mobile network. Therefore an ad-hoc network delivering VoIP technology can be the solution for this problem. This paper presents the research using Raspberry Pi with Kamailio SIP server and OLSR routing protocol. From the experiment, the network performance shows a satisfying result when compared to the standard made by Indonesian Ministry of Communication and Informatics. Considering Raspberry Pi capability and experiment result, it is possible to use Raspberry Pi for VoIP system in the rural area.","PeriodicalId":388463,"journal":{"name":"2018 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122044038","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}
D. Adzkiya, J. Al-Jaroodi, R. Morris, Insook Kim, N. Mohamed, Mohan Patel, D. Patel
{"title":"Technical Program Committee & Reviewers","authors":"D. Adzkiya, J. Al-Jaroodi, R. Morris, Insook Kim, N. Mohamed, Mohan Patel, D. Patel","doi":"10.1109/icetet.2010.178","DOIUrl":"https://doi.org/10.1109/icetet.2010.178","url":null,"abstract":"","PeriodicalId":388463,"journal":{"name":"2018 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127940670","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：