Pub Date : 2019-12-01DOI: 10.1109/ISRITI48646.2019.9034658
Wayan Dadang, Hera Hikmarika, Herma Hermawati, B. Suprapto, Suci Dwijayanti
This study describes a security system using a humanoid robot by utilizing speech recognition. The robot has two main parts, namely, Raspberry Pi 3 and two Arduino UNO R3 as a slave. This robot is designed as a combination of speech recognition and voice biometric. The instruction given by a speaker must be obeyed by the robot using servo motor. Meanwhile, for voice biometric, robot may give access to an authorized person using speech recognition. Mel Frequency Cepstral Coefficients (MFCCs), their delta, and delta-delta are used as feature extraction which is fed to a classifier, Gaussian Mixture Model (GMM). Results of this study show that the robot may recognize the speaker with an accuracy of 99.4% and 99% for 50% of testing data and 20% of testing data, respectively. Thus, this suggests that the combination of MFCC and GMM can be implemented in speech recognition for security system performed by the robot.
本研究描述一种利用语音识别的人形机器人安全系统。该机器人有两个主要部分，即树莓派3和两个Arduino UNO R3作为从机。这个机器人被设计成语音识别和语音生物识别的结合。使用伺服电机的机器人必须服从扬声器发出的指令。同时，对于语音生物识别，机器人可以使用语音识别来访问授权人员。Mel频率倒谱系数(MFCCs)，它们的δ和δ - δ被用作特征提取，并被馈送到分类器高斯混合模型(GMM)中。本研究结果表明，在50%的测试数据和20%的测试数据下，机器人识别说话人的准确率分别为99.4%和99%。因此，这表明MFCC和GMM的结合可以在机器人执行的安防系统语音识别中实现。
{"title":"Security System Using A Robot Based On Speech Recognition","authors":"Wayan Dadang, Hera Hikmarika, Herma Hermawati, B. Suprapto, Suci Dwijayanti","doi":"10.1109/ISRITI48646.2019.9034658","DOIUrl":"https://doi.org/10.1109/ISRITI48646.2019.9034658","url":null,"abstract":"This study describes a security system using a humanoid robot by utilizing speech recognition. The robot has two main parts, namely, Raspberry Pi 3 and two Arduino UNO R3 as a slave. This robot is designed as a combination of speech recognition and voice biometric. The instruction given by a speaker must be obeyed by the robot using servo motor. Meanwhile, for voice biometric, robot may give access to an authorized person using speech recognition. Mel Frequency Cepstral Coefficients (MFCCs), their delta, and delta-delta are used as feature extraction which is fed to a classifier, Gaussian Mixture Model (GMM). Results of this study show that the robot may recognize the speaker with an accuracy of 99.4% and 99% for 50% of testing data and 20% of testing data, respectively. Thus, this suggests that the combination of MFCC and GMM can be implemented in speech recognition for security system performed by the robot.","PeriodicalId":367363,"journal":{"name":"2019 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129804858","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 : 2019-12-01DOI: 10.1109/isriti48646.2019.9034584
{"title":"ISRITI 2019 Preface","authors":"","doi":"10.1109/isriti48646.2019.9034584","DOIUrl":"https://doi.org/10.1109/isriti48646.2019.9034584","url":null,"abstract":"","PeriodicalId":367363,"journal":{"name":"2019 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129011929","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 : 2019-12-01DOI: 10.1109/ISRITI48646.2019.9034643
Dyah Ayu Yuli Murniyati, Lesnanto Multa Putranto, F. D. Wijaya, N. Setiawan, I. Adiyasa
The location of the plant depends on the potential of renewable energy sources. This microgrid power source is a renewable energy generator that will be optimized. The mobile power plant in which implemented is a synchronous generator coupled with a diesel engine, and two power plants based on an induction generator which is implemented as a wind power plant and a micro hydropower plant. Generator will be operated in stand-alone and parallel in the system when the load increases, the load decreases. The increase in load and decrease in the burden can be influenced in terms of the location of these renewable energy plants and can cause a decrease in voltage and frequency. To support the benefits of the scattered power plant, good planning is needed, including determining the location of placement and the power of the scattered power plant that is used so that by optimizing the location of the power plant system in order to achieve optimal operating patterns, when the system voltage stability can reach the voltage parameter 380 V (+ 5% and -10%) and 50 Hz (± 1%) frequency when the generator is working in parallel with variations in loading. Voltage reduction can be minimized by choosing the cable type and generator distance.
{"title":"Effect of Placement of Scattering Generator Locations on Microgrid Testbed Systems","authors":"Dyah Ayu Yuli Murniyati, Lesnanto Multa Putranto, F. D. Wijaya, N. Setiawan, I. Adiyasa","doi":"10.1109/ISRITI48646.2019.9034643","DOIUrl":"https://doi.org/10.1109/ISRITI48646.2019.9034643","url":null,"abstract":"The location of the plant depends on the potential of renewable energy sources. This microgrid power source is a renewable energy generator that will be optimized. The mobile power plant in which implemented is a synchronous generator coupled with a diesel engine, and two power plants based on an induction generator which is implemented as a wind power plant and a micro hydropower plant. Generator will be operated in stand-alone and parallel in the system when the load increases, the load decreases. The increase in load and decrease in the burden can be influenced in terms of the location of these renewable energy plants and can cause a decrease in voltage and frequency. To support the benefits of the scattered power plant, good planning is needed, including determining the location of placement and the power of the scattered power plant that is used so that by optimizing the location of the power plant system in order to achieve optimal operating patterns, when the system voltage stability can reach the voltage parameter 380 V (+ 5% and -10%) and 50 Hz (± 1%) frequency when the generator is working in parallel with variations in loading. Voltage reduction can be minimized by choosing the cable type and generator distance.","PeriodicalId":367363,"journal":{"name":"2019 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126708025","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 : 2019-12-01DOI: 10.1109/ISRITI48646.2019.9034631
Poorni Wickramarathne, M. De Silva, Chathurangi Weerasinghe, Heshani Nanayakkara, P. Abeygunawardhana, S. Silva
In a highly changing technical era, Intelligent Fashion Designing systems play a key role to bridge the gap between fashion designers and the customers. Most of the people specially females, are fond of fashion. Currently, fashion has become a way of defining a person’s preferences and personality. Analyzing through a large number of fashion trends and selecting a one among them will be a highly time-consuming task. Even though most of the people are keen on fashion, with their busy schedules, spending time on selecting a cloth for an occasion among numerous numbers of designs available is a hard task. Therefore, it would be exhausting to select a proper design for an occasion for them. Prevailing the difficulty in finding the clothes up to the user’s expectation, we propose a user-friendly fashion designing mobile application and a web application called "TrendiTex". Extracting user preference details, user’s body shape predicting and recommending trending fashion designs according to their shape, generating the unique 2D new fashionable design for a specific event and the augmented fit-on facility are implemented in TrendiTex. This system represents an efficient approach to design new unique products according to user’s preferences and gives augmented fit-on facility.
{"title":"TrendiTex: An Intelligent Fashion Designer","authors":"Poorni Wickramarathne, M. De Silva, Chathurangi Weerasinghe, Heshani Nanayakkara, P. Abeygunawardhana, S. Silva","doi":"10.1109/ISRITI48646.2019.9034631","DOIUrl":"https://doi.org/10.1109/ISRITI48646.2019.9034631","url":null,"abstract":"In a highly changing technical era, Intelligent Fashion Designing systems play a key role to bridge the gap between fashion designers and the customers. Most of the people specially females, are fond of fashion. Currently, fashion has become a way of defining a person’s preferences and personality. Analyzing through a large number of fashion trends and selecting a one among them will be a highly time-consuming task. Even though most of the people are keen on fashion, with their busy schedules, spending time on selecting a cloth for an occasion among numerous numbers of designs available is a hard task. Therefore, it would be exhausting to select a proper design for an occasion for them. Prevailing the difficulty in finding the clothes up to the user’s expectation, we propose a user-friendly fashion designing mobile application and a web application called \"TrendiTex\". Extracting user preference details, user’s body shape predicting and recommending trending fashion designs according to their shape, generating the unique 2D new fashionable design for a specific event and the augmented fit-on facility are implemented in TrendiTex. This system represents an efficient approach to design new unique products according to user’s preferences and gives augmented fit-on facility.","PeriodicalId":367363,"journal":{"name":"2019 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114242624","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 : 2019-12-01DOI: 10.1109/ISRITI48646.2019.9034618
Maximillian Sheldy Ferdinand Erwianda, S. Kusumawardani, P. Santosa, Meizar Raka Rimadana
Detecting confusion has been considered as a critical issue in online education platforms. Confusion emerged as an effect of the limited interaction between lecturers and learners. The confusion detection machine learning model can be used to overcome the problem. Such a model can provide the ability for online education systems to detect confusion, thus it can react accordingly. Encouraged by the need, several studies have been done to develop confusion-state classifier models. The best previous model has an average accuracy of 75%. Despite having a promising result, the model still contains several gaps that can be improved. The gaps lie in the selection of the machine learning algorithm and the absence of any hyper-parameter optimization technique. This study aims to overcome them using two approaches: replacing the machine learning algorithm with XGBoost and applying the Tree-structured Parzen Estimator (TPE) as a hyper-parameter optimization technique. The TPE was also combined with the Recursive Feature Elimination (RFE) technique. The proposed model had outperformed the previous ones by achieving an average accuracy of 87%. This study also brought out the most optimal configuration of features and hyper-parameters to build such a model. This study had presented the current confusion-state classifier model.
{"title":"Improving Confusion-State Classifier Model Using XGBoost and Tree-Structured Parzen Estimator","authors":"Maximillian Sheldy Ferdinand Erwianda, S. Kusumawardani, P. Santosa, Meizar Raka Rimadana","doi":"10.1109/ISRITI48646.2019.9034618","DOIUrl":"https://doi.org/10.1109/ISRITI48646.2019.9034618","url":null,"abstract":"Detecting confusion has been considered as a critical issue in online education platforms. Confusion emerged as an effect of the limited interaction between lecturers and learners. The confusion detection machine learning model can be used to overcome the problem. Such a model can provide the ability for online education systems to detect confusion, thus it can react accordingly. Encouraged by the need, several studies have been done to develop confusion-state classifier models. The best previous model has an average accuracy of 75%. Despite having a promising result, the model still contains several gaps that can be improved. The gaps lie in the selection of the machine learning algorithm and the absence of any hyper-parameter optimization technique. This study aims to overcome them using two approaches: replacing the machine learning algorithm with XGBoost and applying the Tree-structured Parzen Estimator (TPE) as a hyper-parameter optimization technique. The TPE was also combined with the Recursive Feature Elimination (RFE) technique. The proposed model had outperformed the previous ones by achieving an average accuracy of 87%. This study also brought out the most optimal configuration of features and hyper-parameters to build such a model. This study had presented the current confusion-state classifier model.","PeriodicalId":367363,"journal":{"name":"2019 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123834173","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 : 2019-12-01DOI: 10.1109/ISRITI48646.2019.9034650
Yohanes Yohanie Fridelin Panduman, S. Sukaridhoto, A. Tjahjono
Increased Internet of Things (IoT) technology has increased the number of IoT platform technology developments that are used to facilitate the development of IoT. But in the industrial era 4.0, the application of IoT to Smart Factory has evolved into a new paradigm, namely the Cyber-Physical System (CPS). Therefore, this paper aims to do a survey to determine the parameters and criteria to build a system and architecture of the CPS platform. Additionally, it surveys and analyzes using several parameters or criteria to compare several IoT platforms such as thing management, connectivity, data storage, data abstraction, interface, analytical, feedback & collaboration, security, scalability, microservices, plug, and play. The result shows that these parameters and criteria can be used as references to develop the CPS platform system. In the next step, we expected that the creation of a CPS platform can be based on references from the results of this research survey and analysis.
{"title":"A Survey of IoT Platform Comparison for Building Cyber-Physical System Architecture","authors":"Yohanes Yohanie Fridelin Panduman, S. Sukaridhoto, A. Tjahjono","doi":"10.1109/ISRITI48646.2019.9034650","DOIUrl":"https://doi.org/10.1109/ISRITI48646.2019.9034650","url":null,"abstract":"Increased Internet of Things (IoT) technology has increased the number of IoT platform technology developments that are used to facilitate the development of IoT. But in the industrial era 4.0, the application of IoT to Smart Factory has evolved into a new paradigm, namely the Cyber-Physical System (CPS). Therefore, this paper aims to do a survey to determine the parameters and criteria to build a system and architecture of the CPS platform. Additionally, it surveys and analyzes using several parameters or criteria to compare several IoT platforms such as thing management, connectivity, data storage, data abstraction, interface, analytical, feedback & collaboration, security, scalability, microservices, plug, and play. The result shows that these parameters and criteria can be used as references to develop the CPS platform system. In the next step, we expected that the creation of a CPS platform can be based on references from the results of this research survey and analysis.","PeriodicalId":367363,"journal":{"name":"2019 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122690397","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 : 2019-12-01DOI: 10.1109/ISRITI48646.2019.9034667
R. S. Yuwana, Endang Suryawati, A. Heryana, Vicky Zilvan, D. Rohdiana, Heri Syahrian K
As each tea clone may produce different quality of tea, it is important to have them identified in the field. Tea Clones identification is one application of ICT technologies in agriculture. Tea clones may have very similar characteristics between them, required to have a good amount of data to train a machine learning-based classifiers to have good performances. However, we may have to deal with a small amount of data in many cases. To overcome this, we propose to use an encoder-based feature reduction to produce RGB-based bottleneck features. The output features are then fed into an SVM classifier. We evaluate our features on the classification of two tea clones of the Gambung Assamica (GMB) series. Our experimental results show that our proposed features achieve better performance than using full dimensions RGB.
{"title":"Bottleneck RGB Features for Tea Clones Identification","authors":"R. S. Yuwana, Endang Suryawati, A. Heryana, Vicky Zilvan, D. Rohdiana, Heri Syahrian K","doi":"10.1109/ISRITI48646.2019.9034667","DOIUrl":"https://doi.org/10.1109/ISRITI48646.2019.9034667","url":null,"abstract":"As each tea clone may produce different quality of tea, it is important to have them identified in the field. Tea Clones identification is one application of ICT technologies in agriculture. Tea clones may have very similar characteristics between them, required to have a good amount of data to train a machine learning-based classifiers to have good performances. However, we may have to deal with a small amount of data in many cases. To overcome this, we propose to use an encoder-based feature reduction to produce RGB-based bottleneck features. The output features are then fed into an SVM classifier. We evaluate our features on the classification of two tea clones of the Gambung Assamica (GMB) series. Our experimental results show that our proposed features achieve better performance than using full dimensions RGB.","PeriodicalId":367363,"journal":{"name":"2019 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121870401","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 : 2019-12-01DOI: 10.1109/ISRITI48646.2019.9034669
Vebby Clarissa, S. Suyanto
Nurse Rostering Problem (NRP) is a crucial problem in hospital industry with combinatorial complex problem. NRP is one of the NP-Hard problems, which means that today there is no definite algorithm that is capable of solving the problem. In this paper, a metaheuristic approach called Reward-Based Movement for Bee Colony Optimization (RBMBCO) is proposed to solve the NRP. It is evaluated using an NRP instance of 30 nurses for 4 weeks of assignment from The Second International Nurse Rostering Competition (INRC-II) dataset. The experimental results show that RBMBCO is capable of generating a better solution than the standard Globally-Evolved Bee Colony Optimization.
{"title":"New Reward-Based Movement to Improve Globally-Evolved BCO in Nurse Rostering Problem","authors":"Vebby Clarissa, S. Suyanto","doi":"10.1109/ISRITI48646.2019.9034669","DOIUrl":"https://doi.org/10.1109/ISRITI48646.2019.9034669","url":null,"abstract":"Nurse Rostering Problem (NRP) is a crucial problem in hospital industry with combinatorial complex problem. NRP is one of the NP-Hard problems, which means that today there is no definite algorithm that is capable of solving the problem. In this paper, a metaheuristic approach called Reward-Based Movement for Bee Colony Optimization (RBMBCO) is proposed to solve the NRP. It is evaluated using an NRP instance of 30 nurses for 4 weeks of assignment from The Second International Nurse Rostering Competition (INRC-II) dataset. The experimental results show that RBMBCO is capable of generating a better solution than the standard Globally-Evolved Bee Colony Optimization.","PeriodicalId":367363,"journal":{"name":"2019 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"332 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134019242","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 : 2019-12-01DOI: 10.1109/ISRITI48646.2019.9034567
Muhammad Husain Toding Bunga, S. Suyanto
As technologies of natural language understanding and generation improve, the human interest towards human-computer interaction increases. The technologies can be applied for various applications of customer services. Most works related to this field are emphasizing on single sentence and speaker turn. Meanwhile, a conversation sometimes has its own context according to the previous one. Designing this kind of conversational system is challenging. Most conversational agents are built based on knowledge-based and rule based systems. This paper discusses a development of a complete dialogue system to understand the intent of a text and give response based on the dialogue state. The dialogue model is implemented using the combination of rule-based and data-driven approach by utilizing a long short-term memory (LSTM). Some experiments show that the developed system give a high performance. A detail observation informs that some errors come from the intent classifier that fails to classify some sentences not in the corpus. This system can be improved by increasing the performance of the intent classifier and incorporating an additional named entity recognition module.
{"title":"Developing a Complete Dialogue System Using Long Short-Term Memory","authors":"Muhammad Husain Toding Bunga, S. Suyanto","doi":"10.1109/ISRITI48646.2019.9034567","DOIUrl":"https://doi.org/10.1109/ISRITI48646.2019.9034567","url":null,"abstract":"As technologies of natural language understanding and generation improve, the human interest towards human-computer interaction increases. The technologies can be applied for various applications of customer services. Most works related to this field are emphasizing on single sentence and speaker turn. Meanwhile, a conversation sometimes has its own context according to the previous one. Designing this kind of conversational system is challenging. Most conversational agents are built based on knowledge-based and rule based systems. This paper discusses a development of a complete dialogue system to understand the intent of a text and give response based on the dialogue state. The dialogue model is implemented using the combination of rule-based and data-driven approach by utilizing a long short-term memory (LSTM). Some experiments show that the developed system give a high performance. A detail observation informs that some errors come from the intent classifier that fails to classify some sentences not in the corpus. This system can be improved by increasing the performance of the intent classifier and incorporating an additional named entity recognition module.","PeriodicalId":367363,"journal":{"name":"2019 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126232968","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 : 2019-12-01DOI: 10.1109/isriti48646.2019.9034623
{"title":"ISRITI 2019 Technical Program Committee","authors":"","doi":"10.1109/isriti48646.2019.9034623","DOIUrl":"https://doi.org/10.1109/isriti48646.2019.9034623","url":null,"abstract":"","PeriodicalId":367363,"journal":{"name":"2019 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122574005","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}
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