Pub Date : 2020-10-21DOI: 10.1109/ICSITech49800.2020.9392077
Dewandari Adi Antika Putri, Akhmad Hambali, Erna S. Sugesti, Brian Pamukti
Visible Light Communication (VLC) is the one of technologies used for 6th generation of telecommunications (6G), because it has a wide frequency spectrum, higher speed and safety. We have conducted an experiment using a prototype to transmit sound. Measurements were made by changing the receiving distance from 30 cm up to 300 cm in increments of 30 cm. We also shift the receiving device, so that it forms an angle 0° up to 30°. This study analyzes the extent of changes in distance and angle to the measurement results. We use a Lux meter measurement of the light intensity received by the receiver. In addition, we also measure the ratio of the sound sent to the received by measuring dB meter. From the results of extensive testing, we got the result that the farther distance, then the sound quality is getting lower. For the 0° angle obtained a propagation distance limit of up to 250 cm, 15° angle 200 cm away and 30° angle up to 150 cm. In addition, we also found that the magnitude of the angle shift decreased the intensity of the received light.
{"title":"Voice Delivery using The Visible Light Communication (VLC) Prototype on Line of Sight (LOS) Channels","authors":"Dewandari Adi Antika Putri, Akhmad Hambali, Erna S. Sugesti, Brian Pamukti","doi":"10.1109/ICSITech49800.2020.9392077","DOIUrl":"https://doi.org/10.1109/ICSITech49800.2020.9392077","url":null,"abstract":"Visible Light Communication (VLC) is the one of technologies used for 6th generation of telecommunications (6G), because it has a wide frequency spectrum, higher speed and safety. We have conducted an experiment using a prototype to transmit sound. Measurements were made by changing the receiving distance from 30 cm up to 300 cm in increments of 30 cm. We also shift the receiving device, so that it forms an angle 0° up to 30°. This study analyzes the extent of changes in distance and angle to the measurement results. We use a Lux meter measurement of the light intensity received by the receiver. In addition, we also measure the ratio of the sound sent to the received by measuring dB meter. From the results of extensive testing, we got the result that the farther distance, then the sound quality is getting lower. For the 0° angle obtained a propagation distance limit of up to 250 cm, 15° angle 200 cm away and 30° angle up to 150 cm. In addition, we also found that the magnitude of the angle shift decreased the intensity of the received light.","PeriodicalId":408532,"journal":{"name":"2020 6th International Conference on Science in Information Technology (ICSITech)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126770755","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 : 2020-10-21DOI: 10.1109/ICSITech49800.2020.9392051
R. Surya, Elliana Gautama
Cassava is a plant that is widely found in Indonesia with various benefits. One of the benefits of cassava is as a substitute for rice. According to data from the Indonesian Central Statistics Agency in 2015, cassava production in Indonesia was 21,801,415 tons a year. Lampung Province is the largest producer of cassava in Indonesia. In 2016, its production decreased due to disease attacking the cassava plant. One of the deep learning methods currently being developed is Convolutional Neural Network (CNN). This network is built with the assumption that the input used is an image. This technique can make the image learning function more efficient to implement. Therefore, this study will take advantage of the advantages of CNN, namely being able to classify an object intended for image data so that the CNN model will be used as an introduction to the four types of healthy cassava leaf and cassava leaf diseases that can be found in Indonesia. By using the Tensorflow library, the results of model trials and evaluations of cassava leaf images show an accuracy of 0.8538 for training and 0.7496 for data validation. So it can be concluded that the implementation of Deep Learning with the Convolutional Neural Network (CNN) method can detect cassava leaf disease images.
{"title":"Cassava Leaf Disease Detection Using Convolutional Neural Networks","authors":"R. Surya, Elliana Gautama","doi":"10.1109/ICSITech49800.2020.9392051","DOIUrl":"https://doi.org/10.1109/ICSITech49800.2020.9392051","url":null,"abstract":"Cassava is a plant that is widely found in Indonesia with various benefits. One of the benefits of cassava is as a substitute for rice. According to data from the Indonesian Central Statistics Agency in 2015, cassava production in Indonesia was 21,801,415 tons a year. Lampung Province is the largest producer of cassava in Indonesia. In 2016, its production decreased due to disease attacking the cassava plant. One of the deep learning methods currently being developed is Convolutional Neural Network (CNN). This network is built with the assumption that the input used is an image. This technique can make the image learning function more efficient to implement. Therefore, this study will take advantage of the advantages of CNN, namely being able to classify an object intended for image data so that the CNN model will be used as an introduction to the four types of healthy cassava leaf and cassava leaf diseases that can be found in Indonesia. By using the Tensorflow library, the results of model trials and evaluations of cassava leaf images show an accuracy of 0.8538 for training and 0.7496 for data validation. So it can be concluded that the implementation of Deep Learning with the Convolutional Neural Network (CNN) method can detect cassava leaf disease images.","PeriodicalId":408532,"journal":{"name":"2020 6th International Conference on Science in Information Technology (ICSITech)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128399937","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 : 2020-10-21DOI: 10.1109/ICSITech49800.2020.9392072
S. Núñez, Jesus Mendoza Padilla
Now more than ever, Industry 4.0 and the suite of new technologies are enabling a digital transformation in the education sector. Dream to Succeed Foundation performed research on distance learning during the Covid-19 pandemic and this white paper presents a review on the current state of reality and proposes an integrated distance learning solution with three intertwined domains: people, processes, and technology. Many companies, schools, research centers, universities, local government, or department of education acknowledge that artificial intelligence, machine learning, Internet of things, virtual reality, cloud computing, and other Industry 4.0 technologies are key components for an integrated distance learning solution. A well-defined teaching and learning process and a new mindset and skills from all personals involved will be required to improve the education system in a sustainable environment with continuous improvements to adapt to new norms. This white paper will serve as a framework for the future development of similar integrated solutions with a partnership with great companies to collaborate and implement a great and global solution.
{"title":"Industry 4.0: An Integrated Distance Learning Solution","authors":"S. Núñez, Jesus Mendoza Padilla","doi":"10.1109/ICSITech49800.2020.9392072","DOIUrl":"https://doi.org/10.1109/ICSITech49800.2020.9392072","url":null,"abstract":"Now more than ever, Industry 4.0 and the suite of new technologies are enabling a digital transformation in the education sector. Dream to Succeed Foundation performed research on distance learning during the Covid-19 pandemic and this white paper presents a review on the current state of reality and proposes an integrated distance learning solution with three intertwined domains: people, processes, and technology. Many companies, schools, research centers, universities, local government, or department of education acknowledge that artificial intelligence, machine learning, Internet of things, virtual reality, cloud computing, and other Industry 4.0 technologies are key components for an integrated distance learning solution. A well-defined teaching and learning process and a new mindset and skills from all personals involved will be required to improve the education system in a sustainable environment with continuous improvements to adapt to new norms. This white paper will serve as a framework for the future development of similar integrated solutions with a partnership with great companies to collaborate and implement a great and global solution.","PeriodicalId":408532,"journal":{"name":"2020 6th International Conference on Science in Information Technology (ICSITech)","volume":"153 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130926185","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 : 2020-10-21DOI: 10.1109/ICSITech49800.2020.9392044
R. A. Sukamto, Yudi Wibisono, De Gitgit Agitya
Many of the activities are done online nowadays. The portal website is one of the websites that the users need to visit. This makes the portal website need to meet user satisfaction. The user satisfaction can be reached by increasing the User Experience (UX) value. User-Centered Design (UCD) is a method used to develop a product by involving users in its development. Products developed using the UCD method will have a better user experience so that the users will be more comfortable using the product. The purpose of this research is to improve UX on an portal website using the UCD method. The initial value and final product value will be assessed using the User Experience Questionnaire (UEQ). The results of the study show there is an increase in the UEQ scale, attractiveness from 1.16 to 1.60, perspicuity from 1.10 to 1.54, efficiency from 1.11 to 1.42, dependability from 1.02 to 1.32, stimulation from 0.87 to 1.61 and novelty from 0.59 to 1.14 and overall are in above average or even good in one criteria. The results represent the feedback from the respondents about the portal website improvement is going better.
{"title":"Enhancing The User Experience of Portal Website using User-Centered Design Method","authors":"R. A. Sukamto, Yudi Wibisono, De Gitgit Agitya","doi":"10.1109/ICSITech49800.2020.9392044","DOIUrl":"https://doi.org/10.1109/ICSITech49800.2020.9392044","url":null,"abstract":"Many of the activities are done online nowadays. The portal website is one of the websites that the users need to visit. This makes the portal website need to meet user satisfaction. The user satisfaction can be reached by increasing the User Experience (UX) value. User-Centered Design (UCD) is a method used to develop a product by involving users in its development. Products developed using the UCD method will have a better user experience so that the users will be more comfortable using the product. The purpose of this research is to improve UX on an portal website using the UCD method. The initial value and final product value will be assessed using the User Experience Questionnaire (UEQ). The results of the study show there is an increase in the UEQ scale, attractiveness from 1.16 to 1.60, perspicuity from 1.10 to 1.54, efficiency from 1.11 to 1.42, dependability from 1.02 to 1.32, stimulation from 0.87 to 1.61 and novelty from 0.59 to 1.14 and overall are in above average or even good in one criteria. The results represent the feedback from the respondents about the portal website improvement is going better.","PeriodicalId":408532,"journal":{"name":"2020 6th International Conference on Science in Information Technology (ICSITech)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117304326","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 : 2020-10-21DOI: 10.1109/icsitech49800.2020.9392058
{"title":"ICSITech 2020 Schedule","authors":"","doi":"10.1109/icsitech49800.2020.9392058","DOIUrl":"https://doi.org/10.1109/icsitech49800.2020.9392058","url":null,"abstract":"","PeriodicalId":408532,"journal":{"name":"2020 6th International Conference on Science in Information Technology (ICSITech)","volume":"644 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122957417","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 : 2020-10-21DOI: 10.1109/ICSITech49800.2020.9392075
E. Nugroho, Taufik Djatna, I. S. Sitanggang, A. Buono, I. Hermadi
Internet of Things (IoT) devices with their network services are often vulnerable to attacks because they are not designed for security. Especially with the rapid technological advances that make data increase exponentially. This is targeted by malicious users to exploit vulnerabilities or interfere with many vulnerability attacks. Therefore, deal with this vulnerability, an intrusion detection system that involves machine learning techniques is needed. Intrusion Detection System (IDS) is targeted to get intrusion in a communication system by looking at the IDS types and methods. This is influenced by the characteristics of the IoT network involved and the reference dataset used in the detection system. This dataset determines the categories or classes of attacks upon which the IDS decides whether or not to intrusion. Reference databases that already exist and are often used, such as KDD Cup 99, NSL KDD, and attack datasets obtained from conditions. In developing IDS in IoT Device, the Machine Learning approach can be used to solve the type of algorithm used consisting of supervised learning, unsupervised learning, or Reinforcement learning. These algorithm methods can be used include SVM, Decision Tree, K-NN, ANN, RNN, and others. From the review analysis of dominant research conducted in 2015–2020, the largest percentage was obtained using the artificial neural network and deep learning algorithm for the intrusion classification process, with details of 16% ANN, 12% RNN, and DNN.
物联网(IoT)设备及其网络服务往往容易受到攻击，因为它们不是为安全而设计的。特别是随着技术的快速发展，数据呈指数级增长。这是恶意用户利用漏洞或干扰许多漏洞攻击的目标。因此，针对这一漏洞，需要一个涉及机器学习技术的入侵检测系统。通过分析入侵检测系统的类型和方法，对通信系统进行入侵检测。这受到所涉及的物联网网络特性和检测系统中使用的参考数据集的影响。该数据集确定IDS决定是否入侵的攻击类别或类别。已经存在并且经常使用的参考数据库，如KDD Cup 99、NSL KDD、从条件中获得的攻击数据集。在物联网设备中开发IDS时，机器学习方法可用于解决由监督学习、无监督学习或强化学习组成的算法类型。这些算法方法可用于支持向量机，决策树，K-NN, ANN, RNN等。从2015-2020年的主流研究综述分析来看，人工神经网络和深度学习算法在入侵分类过程中所占的比例最大，ANN占16%，RNN占12%，DNN占12%。
{"title":"A Review of Intrusion Detection System in IoT with Machine Learning Approach: Current and Future Research","authors":"E. Nugroho, Taufik Djatna, I. S. Sitanggang, A. Buono, I. Hermadi","doi":"10.1109/ICSITech49800.2020.9392075","DOIUrl":"https://doi.org/10.1109/ICSITech49800.2020.9392075","url":null,"abstract":"Internet of Things (IoT) devices with their network services are often vulnerable to attacks because they are not designed for security. Especially with the rapid technological advances that make data increase exponentially. This is targeted by malicious users to exploit vulnerabilities or interfere with many vulnerability attacks. Therefore, deal with this vulnerability, an intrusion detection system that involves machine learning techniques is needed. Intrusion Detection System (IDS) is targeted to get intrusion in a communication system by looking at the IDS types and methods. This is influenced by the characteristics of the IoT network involved and the reference dataset used in the detection system. This dataset determines the categories or classes of attacks upon which the IDS decides whether or not to intrusion. Reference databases that already exist and are often used, such as KDD Cup 99, NSL KDD, and attack datasets obtained from conditions. In developing IDS in IoT Device, the Machine Learning approach can be used to solve the type of algorithm used consisting of supervised learning, unsupervised learning, or Reinforcement learning. These algorithm methods can be used include SVM, Decision Tree, K-NN, ANN, RNN, and others. From the review analysis of dominant research conducted in 2015–2020, the largest percentage was obtained using the artificial neural network and deep learning algorithm for the intrusion classification process, with details of 16% ANN, 12% RNN, and DNN.","PeriodicalId":408532,"journal":{"name":"2020 6th International Conference on Science in Information Technology (ICSITech)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115527635","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 : 2020-10-21DOI: 10.1109/ICSITech49800.2020.9392047
A. Wahyudin, Herbert Siregar, S. Balqis
One of the intentions of using information systems for organizations is to improve business performance. The information system strategic planning is endeavored to be in line with the business strategy. Information system strategic planning refers to the active and continuous use of information systems and technology to achieve alignment of business and technology strategies. However, planning in this era of technological advancement cannot last long and requires continuous adjustments. Therefore, as part of organizational resources, information systems require operational supervision to ensure investment effectiveness and monitor the influence of business performance growth. The IT balanced scorecard with critical success factors in this study was combined to produce a monitoring and evaluation instrument. Business strategists and linguists are involved in the design validation of monitoring and evaluation instruments. The level of maturity of information systems on business performance is the resulting output. The resulting system software is intended as a model to make it more straightforward for organizations to find out the performance of their information systems. Following the objectives, this study produces monitoring and evaluating instruments for an existing information system based on a combination of an IT balanced scorecard with critical success factors. The result can be an alternative for continuous monitoring and evaluation for existing information systems to be dynamic against changing demands and stay in line with business strategies collaboratively.
{"title":"Collaborative Information System Monitoring and Evaluation Tools Model","authors":"A. Wahyudin, Herbert Siregar, S. Balqis","doi":"10.1109/ICSITech49800.2020.9392047","DOIUrl":"https://doi.org/10.1109/ICSITech49800.2020.9392047","url":null,"abstract":"One of the intentions of using information systems for organizations is to improve business performance. The information system strategic planning is endeavored to be in line with the business strategy. Information system strategic planning refers to the active and continuous use of information systems and technology to achieve alignment of business and technology strategies. However, planning in this era of technological advancement cannot last long and requires continuous adjustments. Therefore, as part of organizational resources, information systems require operational supervision to ensure investment effectiveness and monitor the influence of business performance growth. The IT balanced scorecard with critical success factors in this study was combined to produce a monitoring and evaluation instrument. Business strategists and linguists are involved in the design validation of monitoring and evaluation instruments. The level of maturity of information systems on business performance is the resulting output. The resulting system software is intended as a model to make it more straightforward for organizations to find out the performance of their information systems. Following the objectives, this study produces monitoring and evaluating instruments for an existing information system based on a combination of an IT balanced scorecard with critical success factors. The result can be an alternative for continuous monitoring and evaluation for existing information systems to be dynamic against changing demands and stay in line with business strategies collaboratively.","PeriodicalId":408532,"journal":{"name":"2020 6th International Conference on Science in Information Technology (ICSITech)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116841040","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 : 2020-10-21DOI: 10.1109/ICSITech49800.2020.9392071
K. F. Hashim, N. Hashim, Solahudin Ismail, S. Miniaoui, Shadi Atalla
The objective of this paper is to examine the level of readiness among Dubai citizens to adopt Dubai Smart Government services using the new emerging technologies. This study adopts the Technology Readiness theory as the underlying factor predicting the citizen’s intention to adopt the e-government services. An online survey was conducted and 225 respondents replied to it. The data were analyzed using a structural equation modeling technique. The results show that a citizen’s intention to adopt e-government services using the new technologies are strongly influenced by their level of the service’s innovativeness and security. Meanwhile, the feeling of discomfort negatively influenced their intention to adopt e-government services. This paper ends by discussing the theoretical and practical contributions of this study.
{"title":"Citizen Readiness to Adopt the New Emerging Technologies in Dubai Smart Government Services","authors":"K. F. Hashim, N. Hashim, Solahudin Ismail, S. Miniaoui, Shadi Atalla","doi":"10.1109/ICSITech49800.2020.9392071","DOIUrl":"https://doi.org/10.1109/ICSITech49800.2020.9392071","url":null,"abstract":"The objective of this paper is to examine the level of readiness among Dubai citizens to adopt Dubai Smart Government services using the new emerging technologies. This study adopts the Technology Readiness theory as the underlying factor predicting the citizen’s intention to adopt the e-government services. An online survey was conducted and 225 respondents replied to it. The data were analyzed using a structural equation modeling technique. The results show that a citizen’s intention to adopt e-government services using the new technologies are strongly influenced by their level of the service’s innovativeness and security. Meanwhile, the feeling of discomfort negatively influenced their intention to adopt e-government services. This paper ends by discussing the theoretical and practical contributions of this study.","PeriodicalId":408532,"journal":{"name":"2020 6th International Conference on Science in Information Technology (ICSITech)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126617436","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 : 2020-10-21DOI: 10.1109/ICSITech49800.2020.9392059
U. Pujianto, A. Wibawa, Raditha Ulfah
Damerau-Levenshtein Distance is an algorithm that can solve word correction problems. This algorithm changes one word into another word using a specified set of edit operations. In word correction using Damerau-Levenshtein Distance, edit operations that can be performed are: substitution, insertion, deletion and transposition. However, the Damerau-Levenshtein Distance algorithm also has a weakness, which is a long processing time. In order for the system to be able to display word suggestions on the wrong string, the system must calculate the word with each word in the dictionary. The processing time will be longer if the dictionary used is very large, for example, the Indonesian Dictionary has more than 30,000 basic words. So that in this study, a dictionary distribution based on the number of characters to shorten the processing time. The use of a distributed dictionary speeds up the Damerau-Levenshtein Distance algorithm by 29.04 seconds.
{"title":"Dictionary Distribution Based on Number of Characters for Damerau-Levenshtein Distance Spell Checker Optimization","authors":"U. Pujianto, A. Wibawa, Raditha Ulfah","doi":"10.1109/ICSITech49800.2020.9392059","DOIUrl":"https://doi.org/10.1109/ICSITech49800.2020.9392059","url":null,"abstract":"Damerau-Levenshtein Distance is an algorithm that can solve word correction problems. This algorithm changes one word into another word using a specified set of edit operations. In word correction using Damerau-Levenshtein Distance, edit operations that can be performed are: substitution, insertion, deletion and transposition. However, the Damerau-Levenshtein Distance algorithm also has a weakness, which is a long processing time. In order for the system to be able to display word suggestions on the wrong string, the system must calculate the word with each word in the dictionary. The processing time will be longer if the dictionary used is very large, for example, the Indonesian Dictionary has more than 30,000 basic words. So that in this study, a dictionary distribution based on the number of characters to shorten the processing time. The use of a distributed dictionary speeds up the Damerau-Levenshtein Distance algorithm by 29.04 seconds.","PeriodicalId":408532,"journal":{"name":"2020 6th International Conference on Science in Information Technology (ICSITech)","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134012078","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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