Pub Date : 2017-10-01DOI: 10.1109/ICSITECH.2017.8257131
Zu Zu Aung, Cho Me Me Maung
Optical Character Recognition (OCR) can be used in many applications such as machine translation, postal processing, script recognition, text-to-speech, reading aid for blind, etc. Myanmar OCR system is essential to convert numerous published books, newspapers and journals of Myanmar into editable computer text files. It is a challenge for recognizing Myanmar old printed document in case of bad quality, absence of standard alphabets, absence of known fonts, ink through page, uneven background, broken characters, overlapped scripts and mixed scripts. This paper presents a new proposed block definition method for isolation printed Myanmar historical text. The proposed Myanmar optical character recognition (MOCR) system consists of local adaptive thresholding method for binarization and skew-slant correction, thinning algorithm is applied to obtain separation lines and words. For isolation of characters, block definition method is applied and adaptive neuro-fuzzy inference system (ANFIS) is matched the features in the trained database as machine readable text. Myanmar alphabets include consonants, vowels, medials and digits. By using block definition method, consonants and vowels are isolated easily and we obtained more accuracy rate of the OCR. The efficient experimental results are presented by using different Myanmar old documents in our proposed algorithms.
{"title":"Myanmar optical character recognition using block definition and featured approach","authors":"Zu Zu Aung, Cho Me Me Maung","doi":"10.1109/ICSITECH.2017.8257131","DOIUrl":"https://doi.org/10.1109/ICSITECH.2017.8257131","url":null,"abstract":"Optical Character Recognition (OCR) can be used in many applications such as machine translation, postal processing, script recognition, text-to-speech, reading aid for blind, etc. Myanmar OCR system is essential to convert numerous published books, newspapers and journals of Myanmar into editable computer text files. It is a challenge for recognizing Myanmar old printed document in case of bad quality, absence of standard alphabets, absence of known fonts, ink through page, uneven background, broken characters, overlapped scripts and mixed scripts. This paper presents a new proposed block definition method for isolation printed Myanmar historical text. The proposed Myanmar optical character recognition (MOCR) system consists of local adaptive thresholding method for binarization and skew-slant correction, thinning algorithm is applied to obtain separation lines and words. For isolation of characters, block definition method is applied and adaptive neuro-fuzzy inference system (ANFIS) is matched the features in the trained database as machine readable text. Myanmar alphabets include consonants, vowels, medials and digits. By using block definition method, consonants and vowels are isolated easily and we obtained more accuracy rate of the OCR. The efficient experimental results are presented by using different Myanmar old documents in our proposed algorithms.","PeriodicalId":165045,"journal":{"name":"2017 3rd International Conference on Science in Information Technology (ICSITech)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115692922","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 : 2017-10-01DOI: 10.1109/ICSITECH.2017.8257092
Yutika Amelia Effendi, R. Sarno
This paper presents a bio-inspired hybrid method which concentrate on the optimal or a near-optimal business process model from an event log. The discovery of Hybrid Particle Swarm Optimization (Hybrid PSO) algorithm comes from the combination of Particle Swarm Optimization (PSO) algorithm and Simulated Annealing (SA) method. This paper presents a method which combines Rule discovery task and Hybrid PSO. The proposed method can discover not only classification rules that produce the most optimal business process model from event logs, but also can optimize the quality of process model. To be formulated into an optimization problem, we use rule discovery task to get the high accuracy, comprehensibility and generalization performance. After we get the results from rule discovery task, we use Hybrid PSO to resolve the problem. In this proposed method, we use continuous data as data set and fitness function as evaluation criteria of quality of discovered business process model. As final results, we prove that the proposed method has the best results in terms of average fitness and number of iterations, compared with classical PSO algorithm and original hybrid PSO algorithm.
{"title":"Discovering optimized process model using rule discovery hybrid particle swarm optimization","authors":"Yutika Amelia Effendi, R. Sarno","doi":"10.1109/ICSITECH.2017.8257092","DOIUrl":"https://doi.org/10.1109/ICSITECH.2017.8257092","url":null,"abstract":"This paper presents a bio-inspired hybrid method which concentrate on the optimal or a near-optimal business process model from an event log. The discovery of Hybrid Particle Swarm Optimization (Hybrid PSO) algorithm comes from the combination of Particle Swarm Optimization (PSO) algorithm and Simulated Annealing (SA) method. This paper presents a method which combines Rule discovery task and Hybrid PSO. The proposed method can discover not only classification rules that produce the most optimal business process model from event logs, but also can optimize the quality of process model. To be formulated into an optimization problem, we use rule discovery task to get the high accuracy, comprehensibility and generalization performance. After we get the results from rule discovery task, we use Hybrid PSO to resolve the problem. In this proposed method, we use continuous data as data set and fitness function as evaluation criteria of quality of discovered business process model. As final results, we prove that the proposed method has the best results in terms of average fitness and number of iterations, compared with classical PSO algorithm and original hybrid PSO algorithm.","PeriodicalId":165045,"journal":{"name":"2017 3rd International Conference on Science in Information Technology (ICSITech)","volume":"216 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124261275","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 : 2017-10-01DOI: 10.1109/ICSITECH.2017.8257180
Prasetyo Adi Wibowo Putro
Validation requirements documents electronically is not only needed for electronic documents. For the specific needs of the physical document validation also needs to be done electronically. existing problems, physical documents will always have a different hash values each time digitized. Through this research is reviewed whether perceptual hash can be used for electronic validation of the physical document. The resulting conclusion of this study, perceptual can hash to use and can detect all modifications that occur in the main information document.
{"title":"Physical document validation with perceptual hash","authors":"Prasetyo Adi Wibowo Putro","doi":"10.1109/ICSITECH.2017.8257180","DOIUrl":"https://doi.org/10.1109/ICSITECH.2017.8257180","url":null,"abstract":"Validation requirements documents electronically is not only needed for electronic documents. For the specific needs of the physical document validation also needs to be done electronically. existing problems, physical documents will always have a different hash values each time digitized. Through this research is reviewed whether perceptual hash can be used for electronic validation of the physical document. The resulting conclusion of this study, perceptual can hash to use and can detect all modifications that occur in the main information document.","PeriodicalId":165045,"journal":{"name":"2017 3rd International Conference on Science in Information Technology (ICSITech)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116534287","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 : 2017-10-01DOI: 10.1109/ICSITECH.2017.8257125
I. F. Akmaliah, D. I. Sensuse, I. A. Wulandari, Isnaeni Nurrohmah, Rahmi Imanda, Elin Cahyaningsih, Handrie Noprisson
This study was conducted to determine how the organizational culture conditions in a research laboratory in order to develop a strategy for the implementation of knowledge management system (KMS). We adopted a survey-based research approach was supported by an instrument of Organization Culture Assessment Instrument (OCAI). We collected data from the member of the research laboratory in Faculty of Computer Science, University of Indonesia. The questionnaire was given to 73 potential respondents with 51 valid responses. The results of this study are three of seven research laboratories have a distinction between the current conditions and the preferred conditions. We found that the preferred conditions of all research laboratories are organizational culture ‘Clan’.
{"title":"Analyzing knowledge management in research laboratories based on organizational culture","authors":"I. F. Akmaliah, D. I. Sensuse, I. A. Wulandari, Isnaeni Nurrohmah, Rahmi Imanda, Elin Cahyaningsih, Handrie Noprisson","doi":"10.1109/ICSITECH.2017.8257125","DOIUrl":"https://doi.org/10.1109/ICSITECH.2017.8257125","url":null,"abstract":"This study was conducted to determine how the organizational culture conditions in a research laboratory in order to develop a strategy for the implementation of knowledge management system (KMS). We adopted a survey-based research approach was supported by an instrument of Organization Culture Assessment Instrument (OCAI). We collected data from the member of the research laboratory in Faculty of Computer Science, University of Indonesia. The questionnaire was given to 73 potential respondents with 51 valid responses. The results of this study are three of seven research laboratories have a distinction between the current conditions and the preferred conditions. We found that the preferred conditions of all research laboratories are organizational culture ‘Clan’.","PeriodicalId":165045,"journal":{"name":"2017 3rd International Conference on Science in Information Technology (ICSITech)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122896602","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 : 2017-10-01DOI: 10.1109/ICSITECH.2017.8257205
Rahmaniansyah Dwi Putri, H. W. Prabawa, Y. Wihardi
The study on Content Based Image Retrieval (CBIR) has been a concern for many researchers. To conduct CBIR study, some essential things should be considered that are determining the image dataset, extraction method, and image measurement method. In this study, the dataset used is the Oxford Flower 17 dataset. The feature extraction employed is the feature extraction of the HSV color, the Gray Level Cooccurrence Matrix (GLCM) texture extraction feature, and the combination of both features. This study is purposely generates precision from CBIR test based on the proposed method. At first, digital image is segmented by applying thresholding. Moreover, the image is converted into vector to be subsequently processed using feature extraction. Further, the similarity level of the image is measured by Euclidean Distance. Tests on the system are based on segmented and unsegmented image. The system test with segmented image yields mean average precision of 83.35% for HSV feature extraction, 83.4% for GLCM feature extraction, and 80.94% for combined feature extraction. Meanwhile, the system test for unsegmented image generates mean average precision of 82.64% for HSV feature extraction, 87.32% for GLCM feature extraction, and 85.73% for extraction of combined features.
{"title":"Color and texture features extraction on content-based image retrieval","authors":"Rahmaniansyah Dwi Putri, H. W. Prabawa, Y. Wihardi","doi":"10.1109/ICSITECH.2017.8257205","DOIUrl":"https://doi.org/10.1109/ICSITECH.2017.8257205","url":null,"abstract":"The study on Content Based Image Retrieval (CBIR) has been a concern for many researchers. To conduct CBIR study, some essential things should be considered that are determining the image dataset, extraction method, and image measurement method. In this study, the dataset used is the Oxford Flower 17 dataset. The feature extraction employed is the feature extraction of the HSV color, the Gray Level Cooccurrence Matrix (GLCM) texture extraction feature, and the combination of both features. This study is purposely generates precision from CBIR test based on the proposed method. At first, digital image is segmented by applying thresholding. Moreover, the image is converted into vector to be subsequently processed using feature extraction. Further, the similarity level of the image is measured by Euclidean Distance. Tests on the system are based on segmented and unsegmented image. The system test with segmented image yields mean average precision of 83.35% for HSV feature extraction, 83.4% for GLCM feature extraction, and 80.94% for combined feature extraction. Meanwhile, the system test for unsegmented image generates mean average precision of 82.64% for HSV feature extraction, 87.32% for GLCM feature extraction, and 85.73% for extraction of combined features.","PeriodicalId":165045,"journal":{"name":"2017 3rd International Conference on Science in Information Technology (ICSITech)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122983963","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 : 2017-10-01DOI: 10.1109/ICSITECH.2017.8257123
Aris Prawisudatama, I. B. Nugraha
Field data collection is one of the main activities performed by national statistical agencies in every country. Data collection activities have a similar workflow with Multi-Depot Vehicle Routing Problem (MDVRP). The use of MDVRP to generate pre-calculated routes resulted in total route costs with high standard deviation. The real-time mechanism by utilizing the publish/subscribe paradigm combined with MDVRP based on Cooperative Coevolution Algorithms (CoEAs) is proposed to reduce the inequality (large variation) of the completion time. The test results show that routes produced by the combination of publish/subscribe paradigm and CoEAs are more prevalent in enumerator's total route times compared with the pre-calculated routes produced by MDVRP based on CoEAs only.
{"title":"Real-time location recommendation system for field data collection","authors":"Aris Prawisudatama, I. B. Nugraha","doi":"10.1109/ICSITECH.2017.8257123","DOIUrl":"https://doi.org/10.1109/ICSITECH.2017.8257123","url":null,"abstract":"Field data collection is one of the main activities performed by national statistical agencies in every country. Data collection activities have a similar workflow with Multi-Depot Vehicle Routing Problem (MDVRP). The use of MDVRP to generate pre-calculated routes resulted in total route costs with high standard deviation. The real-time mechanism by utilizing the publish/subscribe paradigm combined with MDVRP based on Cooperative Coevolution Algorithms (CoEAs) is proposed to reduce the inequality (large variation) of the completion time. The test results show that routes produced by the combination of publish/subscribe paradigm and CoEAs are more prevalent in enumerator's total route times compared with the pre-calculated routes produced by MDVRP based on CoEAs only.","PeriodicalId":165045,"journal":{"name":"2017 3rd International Conference on Science in Information Technology (ICSITech)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114213649","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 : 2017-10-01DOI: 10.1109/ICSITECH.2017.8257089
M. Untoro, R. Sarno
Reusability is generally used to determine the level of integration a program, one of them the procurement of goods and services. The objective of this paper to analyze the reusability of components at the business process of the procurement of goods and services using metrics. This component we're analyzed by calculating of frequency and percentages by involving components of the registration of document, the completeness of document, procurement procedures, tender, selection of suppliers, delivery time, the total of goods or services, quality, payment, as well as taxes and inspection. The analysis showed that 7 components that can reusability (more than 50%) are the registration of documents, tender, selection of suppliers, the total of goods or services, quality, payment, as well as taxes and inspection. The highest percentage from of all component is the registration of document (100%).
{"title":"Reusability metric on procurement of goods and services","authors":"M. Untoro, R. Sarno","doi":"10.1109/ICSITECH.2017.8257089","DOIUrl":"https://doi.org/10.1109/ICSITECH.2017.8257089","url":null,"abstract":"Reusability is generally used to determine the level of integration a program, one of them the procurement of goods and services. The objective of this paper to analyze the reusability of components at the business process of the procurement of goods and services using metrics. This component we're analyzed by calculating of frequency and percentages by involving components of the registration of document, the completeness of document, procurement procedures, tender, selection of suppliers, delivery time, the total of goods or services, quality, payment, as well as taxes and inspection. The analysis showed that 7 components that can reusability (more than 50%) are the registration of documents, tender, selection of suppliers, the total of goods or services, quality, payment, as well as taxes and inspection. The highest percentage from of all component is the registration of document (100%).","PeriodicalId":165045,"journal":{"name":"2017 3rd International Conference on Science in Information Technology (ICSITech)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124097120","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 : 2017-10-01DOI: 10.1109/ICSITECH.2017.8257121
Hobert Ho, V. C. Mawardi, Agus Budi Dharmawan
Question answering system is a system that can give an answer from the user. In general, question answering can generate answer to text questions. This paper reports the result of question answering system that can receive input questions from speech and text. Hidden Markov Model (HMM) used to recognize the voice provided by the user. The HMM speech recognition used the feature value obtained from Mel Frequency Cepstrum Coefficients method (MFCC). The question answering system used Vector Space Model from Lucene search engine to retrieve relevant documents. The result shows that HMM speech recognition system's success rate in recognizing words is 83.31% which obtained from 13 tested questions. The result also shows that question answering system can answer 4 out of 6 questions that correctly identified by speech recognition system.
{"title":"Question answering system with Hidden Markov Model speech recognition","authors":"Hobert Ho, V. C. Mawardi, Agus Budi Dharmawan","doi":"10.1109/ICSITECH.2017.8257121","DOIUrl":"https://doi.org/10.1109/ICSITECH.2017.8257121","url":null,"abstract":"Question answering system is a system that can give an answer from the user. In general, question answering can generate answer to text questions. This paper reports the result of question answering system that can receive input questions from speech and text. Hidden Markov Model (HMM) used to recognize the voice provided by the user. The HMM speech recognition used the feature value obtained from Mel Frequency Cepstrum Coefficients method (MFCC). The question answering system used Vector Space Model from Lucene search engine to retrieve relevant documents. The result shows that HMM speech recognition system's success rate in recognizing words is 83.31% which obtained from 13 tested questions. The result also shows that question answering system can answer 4 out of 6 questions that correctly identified by speech recognition system.","PeriodicalId":165045,"journal":{"name":"2017 3rd International Conference on Science in Information Technology (ICSITech)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131554684","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 : 2017-10-01DOI: 10.1109/ICSITECH.2017.8257144
Leonel Hernandez, Y. Calderón, Hugo E. Martinez, A. Pranolo, I. Riyanto
The information processing centers including Data Centers in the companies have evolved and the distributed processing of the technologies for servers and network devices elevates the demand of energy and cooling. Therefore, it is important to analyze the environment with more caution, taking into account that the increase in density and variations are aspects that cause changes in the monitoring methodology of the computer environment. Critical threats that can be detected are elevated temperatures, humidity and unauthorized access, or inappropriate actions by data center staff. In this project, a prototype will be designed and implemented to detect some basic environmental variables such as temperature, pressure, current and humidity, which are vital to controlling within a data center, based on the concepts provided by Internet of Things (IoT). It will also focus on reviewing the current status of the University's data centers to determine if they are energy efficient. It will show the process of the detection system implementation, the components used and network connection for sending the information. This project will serve as a starting point for future development of similar systems, allowing the definition of more variables and serve as a solution for the business sector in the region and the country. In our business environment, there are not many similar developments, at a good cost, that the various entities can execute. It is offering an idea of a system of detection of environmental variables in the data center that is competitive and that represents security and reliability.
{"title":"Design of a system for detection of environmental variables applied in data centers","authors":"Leonel Hernandez, Y. Calderón, Hugo E. Martinez, A. Pranolo, I. Riyanto","doi":"10.1109/ICSITECH.2017.8257144","DOIUrl":"https://doi.org/10.1109/ICSITECH.2017.8257144","url":null,"abstract":"The information processing centers including Data Centers in the companies have evolved and the distributed processing of the technologies for servers and network devices elevates the demand of energy and cooling. Therefore, it is important to analyze the environment with more caution, taking into account that the increase in density and variations are aspects that cause changes in the monitoring methodology of the computer environment. Critical threats that can be detected are elevated temperatures, humidity and unauthorized access, or inappropriate actions by data center staff. In this project, a prototype will be designed and implemented to detect some basic environmental variables such as temperature, pressure, current and humidity, which are vital to controlling within a data center, based on the concepts provided by Internet of Things (IoT). It will also focus on reviewing the current status of the University's data centers to determine if they are energy efficient. It will show the process of the detection system implementation, the components used and network connection for sending the information. This project will serve as a starting point for future development of similar systems, allowing the definition of more variables and serve as a solution for the business sector in the region and the country. In our business environment, there are not many similar developments, at a good cost, that the various entities can execute. It is offering an idea of a system of detection of environmental variables in the data center that is competitive and that represents security and reliability.","PeriodicalId":165045,"journal":{"name":"2017 3rd International Conference on Science in Information Technology (ICSITech)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127844875","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 : 2017-10-01DOI: 10.1109/ICSITECH.2017.8257163
Nanang Cahyana, R. Munir
Twitter has hundreds of millions of users around the world. Using the Twitter as a social network analysis material is very much in demand. Social network analysis can analyze groups and actors of a social network so that it can detect early behaviors that will be performed by groups and actors. But social network analysis in general has not shown strong groups and actors because it uses only one keyword. As a result, this method is quite difficult in detecting early events of a group and actors, especially those associated with cyberterrorist. For that, it needs a method of social network analysis so that the group and the actors produced are really strong and can be detected early behavior that will be done group and actors. The method in question is the use of several different keywords but have the same topic. With this method, it can be obtained a network pattern of groups and powerful actors related to the desired topic so that it can detect earlier behavior that will be done groups and actors. The results obtained are different keywords but have a high value of similarity topics can produce groups and actors are getting stronger. It can increase in the value of graph metric. So this method is feasible to search relationships between different keywords to find the powerfull community and important actor in social network.
{"title":"Community and important actors analysis with different keywords in social network","authors":"Nanang Cahyana, R. Munir","doi":"10.1109/ICSITECH.2017.8257163","DOIUrl":"https://doi.org/10.1109/ICSITECH.2017.8257163","url":null,"abstract":"Twitter has hundreds of millions of users around the world. Using the Twitter as a social network analysis material is very much in demand. Social network analysis can analyze groups and actors of a social network so that it can detect early behaviors that will be performed by groups and actors. But social network analysis in general has not shown strong groups and actors because it uses only one keyword. As a result, this method is quite difficult in detecting early events of a group and actors, especially those associated with cyberterrorist. For that, it needs a method of social network analysis so that the group and the actors produced are really strong and can be detected early behavior that will be done group and actors. The method in question is the use of several different keywords but have the same topic. With this method, it can be obtained a network pattern of groups and powerful actors related to the desired topic so that it can detect earlier behavior that will be done groups and actors. The results obtained are different keywords but have a high value of similarity topics can produce groups and actors are getting stronger. It can increase in the value of graph metric. So this method is feasible to search relationships between different keywords to find the powerfull community and important actor in social network.","PeriodicalId":165045,"journal":{"name":"2017 3rd International Conference on Science in Information Technology (ICSITech)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124332381","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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