Pub Date : 2020-09-19DOI: 10.1109/iSemantic50169.2020.9234239
Aries Findra Setiawan, A. Wibawa, M. Purnomo, W. Islamiyah
In the new normal, a period after Covid-19 outbreak, many things run in the new normal. Including stroke rehabilitation. During the Covid-19 and new normal era, stroke patients are not allowed to gather in a hospital in queue line for rehabilitation service. A new approach is needed to keep the rehabilitation running with a big caution to Covid-19. EEG is an alternative technology for supporting the self-monitoring stroke rehabilitation. In this study, EEG parameters such as mean, Standard deviation, mean absolute value were analyzed and tested to answer our hypotheses whether or not those parameters can be used for monitoring stroke rehabilitation progress. This study involved 3 stroke patients who underwent stroke rehabilitation using re-learning program. Each time stroke patient performed rehabilitation program EEG data was recorded. During two months measurement in total from 3 stroke patients, 12 set EEG data was obtained and analyzed. Two motions were recorded namely hand movements and elbow movements. C3 and C4 EEG channel are used to get the raw EEG data. Data processing such as filtering EEG band into alpha and beta band, noise artefact removal (ICA) and data calculation were done before obtaining the monitoring parameters. The result showed that during post stroke rehabilitation parameters such as Mean, Standard Deviation and Mean Absolute Value showed higher value in both EEG band, alpha and beta. In conclusion, EEG statistical parameters can be used as a monitoring parameter during stroke rehabilitation. In the era of new normal, this could be a solution for home care stroke rehabilitation program.
{"title":"Monitoring Stroke Rehabilitation Re-Learning Program using EEG Parameter: A preliminary study for developing self-monitoring system for stroke rehabilitation during new normal","authors":"Aries Findra Setiawan, A. Wibawa, M. Purnomo, W. Islamiyah","doi":"10.1109/iSemantic50169.2020.9234239","DOIUrl":"https://doi.org/10.1109/iSemantic50169.2020.9234239","url":null,"abstract":"In the new normal, a period after Covid-19 outbreak, many things run in the new normal. Including stroke rehabilitation. During the Covid-19 and new normal era, stroke patients are not allowed to gather in a hospital in queue line for rehabilitation service. A new approach is needed to keep the rehabilitation running with a big caution to Covid-19. EEG is an alternative technology for supporting the self-monitoring stroke rehabilitation. In this study, EEG parameters such as mean, Standard deviation, mean absolute value were analyzed and tested to answer our hypotheses whether or not those parameters can be used for monitoring stroke rehabilitation progress. This study involved 3 stroke patients who underwent stroke rehabilitation using re-learning program. Each time stroke patient performed rehabilitation program EEG data was recorded. During two months measurement in total from 3 stroke patients, 12 set EEG data was obtained and analyzed. Two motions were recorded namely hand movements and elbow movements. C3 and C4 EEG channel are used to get the raw EEG data. Data processing such as filtering EEG band into alpha and beta band, noise artefact removal (ICA) and data calculation were done before obtaining the monitoring parameters. The result showed that during post stroke rehabilitation parameters such as Mean, Standard Deviation and Mean Absolute Value showed higher value in both EEG band, alpha and beta. In conclusion, EEG statistical parameters can be used as a monitoring parameter during stroke rehabilitation. In the era of new normal, this could be a solution for home care stroke rehabilitation program.","PeriodicalId":345558,"journal":{"name":"2020 International Seminar on Application for Technology of Information and Communication (iSemantic)","volume":"03 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127341320","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 : 2020-09-19DOI: 10.1109/iSemantic50169.2020.9234221
Agastya Vitadhani, Fahdiaz Alief, B. Haryanto, R. Harwahyu, Riri Fitri Sari
LoRaWAN as a low cost and has a wide area coverage is an efficient technology to replace a lot of manual processes. This paper presents simulation results of the usage of LoRaWAN for flood early warning control system in Ciliwung River. Ciliwung River is one of the rivers that flow through Jakarta, the capital city of Indonesia. One of the main causes of floods in Jakarta is the increase in the Ciliwung River water discharge due to high rainfall in the upstream area and areas along the Ciliwung River. Flood early warning control system, is an important factor for the Jakarta provincial government to determine decisions on flood mitigation, for example the preparation of evacuation areas, water pumps and floodgate capacity. Based on water level measurement points on existing systems, we try to measure the exact distance and height to determine the gateway placement. The area of water measurement points is divided into 2 areas, namely area 1 that covers Bogor and area 2 that includes Depok and South Jakarta. The simulation shows that the use of 1 gateway with antenna height of 30 meters in area 1 and 1 gateway with antenna height of 108 meters in area 2 can cover all end devices. In area 2, using 2 gateways with a height of 30 meters each can cover all end devices with a much lower gateway height.
{"title":"Simulating LoRaWAN for Flood Early Warning System in Ciliwung River, Bogor-Jakarta","authors":"Agastya Vitadhani, Fahdiaz Alief, B. Haryanto, R. Harwahyu, Riri Fitri Sari","doi":"10.1109/iSemantic50169.2020.9234221","DOIUrl":"https://doi.org/10.1109/iSemantic50169.2020.9234221","url":null,"abstract":"LoRaWAN as a low cost and has a wide area coverage is an efficient technology to replace a lot of manual processes. This paper presents simulation results of the usage of LoRaWAN for flood early warning control system in Ciliwung River. Ciliwung River is one of the rivers that flow through Jakarta, the capital city of Indonesia. One of the main causes of floods in Jakarta is the increase in the Ciliwung River water discharge due to high rainfall in the upstream area and areas along the Ciliwung River. Flood early warning control system, is an important factor for the Jakarta provincial government to determine decisions on flood mitigation, for example the preparation of evacuation areas, water pumps and floodgate capacity. Based on water level measurement points on existing systems, we try to measure the exact distance and height to determine the gateway placement. The area of water measurement points is divided into 2 areas, namely area 1 that covers Bogor and area 2 that includes Depok and South Jakarta. The simulation shows that the use of 1 gateway with antenna height of 30 meters in area 1 and 1 gateway with antenna height of 108 meters in area 2 can cover all end devices. In area 2, using 2 gateways with a height of 30 meters each can cover all end devices with a much lower gateway height.","PeriodicalId":345558,"journal":{"name":"2020 International Seminar on Application for Technology of Information and Communication (iSemantic)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127461109","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 : 2020-09-19DOI: 10.1109/iSemantic50169.2020.9234257
Muhammad Khosyi'in, E. N. Budisusila, S. Prasetyowati, B. Suprapto, Z. Nawawi
This article provides a discussion of the testing and measurement of UHF RFID with distance and facing angle parameters on static and moving state conditions. This study is necessary for implementing RFID technology in the development of autonomous vehicle navigation systems. Navigation systems in autonomous vehicles generally never leave the global positioning system (GPS) as a navigation sensor. The use of GPS independently has weaknesses related to the accuracy, so a navigation system using GPS requires correction of the navigation route based on coordinates, this correction can be done by adding another sensor. The integration of GPS and RFID technology has several advantages besides being cost-effective. Studies that have been carried out enable an autonomous vehicle navigation system to be run by combining data between RFID Reader readings in retrieving location data points marked with RFID tags and coordinate vehicle position data on maps by the GPS which generates route and location information passed by vehicles using the GPS/RFID method localization. Tests and measurements are performed by reading on three types of RFID tags with varying distances and angles of view. The results showed that the best reading distance for RFID tags is at a distance of 4 meters with a reading angle of the RFID Reader at 90 degrees on the z-axis and y-axis. While the best RFID tag performance is the tag on the Passive UHF RFID metal, both for testing in static or moving state condition.
{"title":"Tests Measurement of UHF RFID for Autonomous Vehicle Navigation","authors":"Muhammad Khosyi'in, E. N. Budisusila, S. Prasetyowati, B. Suprapto, Z. Nawawi","doi":"10.1109/iSemantic50169.2020.9234257","DOIUrl":"https://doi.org/10.1109/iSemantic50169.2020.9234257","url":null,"abstract":"This article provides a discussion of the testing and measurement of UHF RFID with distance and facing angle parameters on static and moving state conditions. This study is necessary for implementing RFID technology in the development of autonomous vehicle navigation systems. Navigation systems in autonomous vehicles generally never leave the global positioning system (GPS) as a navigation sensor. The use of GPS independently has weaknesses related to the accuracy, so a navigation system using GPS requires correction of the navigation route based on coordinates, this correction can be done by adding another sensor. The integration of GPS and RFID technology has several advantages besides being cost-effective. Studies that have been carried out enable an autonomous vehicle navigation system to be run by combining data between RFID Reader readings in retrieving location data points marked with RFID tags and coordinate vehicle position data on maps by the GPS which generates route and location information passed by vehicles using the GPS/RFID method localization. Tests and measurements are performed by reading on three types of RFID tags with varying distances and angles of view. The results showed that the best reading distance for RFID tags is at a distance of 4 meters with a reading angle of the RFID Reader at 90 degrees on the z-axis and y-axis. While the best RFID tag performance is the tag on the Passive UHF RFID metal, both for testing in static or moving state condition.","PeriodicalId":345558,"journal":{"name":"2020 International Seminar on Application for Technology of Information and Communication (iSemantic)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126474319","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}
Linear Discriminant Analysis (LDA) is a method used for dimension reduction and classification. By reducing the dimensions of data interpretation it becomes easier. A new LDA-based coordinate transformation (LDA-CT) approach has been developed that does not depend on the statistical nature of data distribution so that it is more robust to the influence of outliers. This approach transforms data from the old coordinates to the new coordinates so that an optimal gradient is obtained which maximizes the separation distance of the two groups in the projection space. Synthetic data are used to test the performance of this new LDA approach compared to existing LDA performance. The experimental results using synthetic data without and with outliers show that compared to the existing LDA, this new approach is able to make generalizations better and more robustly against the influence of outliers. For data that can be separated linearly, the LDA-CT Optimal method is able to separate classes as far as 0.705390519 better than existing LDA which only separates as far as 0.33440611. For data with outliers, LDA-CT Optimal accuracy is better than existing LDA with 91.67% compared to 75%.
{"title":"A Novel Approach on Linear Discriminant Analysis (LDA)","authors":"Usman Sudibyo, Supriadi Rustad, Pulung Nurtantio Andono, A. Zainul Fanani, Purwanto Purwanto, Muljono Muljono","doi":"10.1109/iSemantic50169.2020.9234274","DOIUrl":"https://doi.org/10.1109/iSemantic50169.2020.9234274","url":null,"abstract":"Linear Discriminant Analysis (LDA) is a method used for dimension reduction and classification. By reducing the dimensions of data interpretation it becomes easier. A new LDA-based coordinate transformation (LDA-CT) approach has been developed that does not depend on the statistical nature of data distribution so that it is more robust to the influence of outliers. This approach transforms data from the old coordinates to the new coordinates so that an optimal gradient is obtained which maximizes the separation distance of the two groups in the projection space. Synthetic data are used to test the performance of this new LDA approach compared to existing LDA performance. The experimental results using synthetic data without and with outliers show that compared to the existing LDA, this new approach is able to make generalizations better and more robustly against the influence of outliers. For data that can be separated linearly, the LDA-CT Optimal method is able to separate classes as far as 0.705390519 better than existing LDA which only separates as far as 0.33440611. For data with outliers, LDA-CT Optimal accuracy is better than existing LDA with 91.67% compared to 75%.","PeriodicalId":345558,"journal":{"name":"2020 International Seminar on Application for Technology of Information and Communication (iSemantic)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127593872","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 : 2020-09-19DOI: 10.1109/iSemantic50169.2020.9234272
Qori Erfan Sahril, I. Sudiharto, Ony Asrarul Qudsi
Voltage sag is a phenomenon of a short time voltage reduction from the nominal value which often occurs in the industrial’s electricity. Certainly, it causes negative impact on industrial production. The solution to this problem is by installing AC-AC converter that is modified into Dynamic Voltage Restorer (DVR). AC-AC converter is used in this design to minimize battery usage and to reduce harmonic components. The method used is transformation of direct-quadrature (dq) synchronous reference frame for single phase systems. It transforms AC variables, from stationary frame to the dq rotating frame into DC variables. The circuit model and the result in Power SIM simulation where the AC-AC converter output voltage is controlled has been described. DVR in this paper is capable to mitigate line voltage up to the remaining 25%.
{"title":"A Single Phase Dynamic Voltage Restorer (DVR) With Direct AC-AC Converter Using dq Transform to Mitigate Voltage Sag","authors":"Qori Erfan Sahril, I. Sudiharto, Ony Asrarul Qudsi","doi":"10.1109/iSemantic50169.2020.9234272","DOIUrl":"https://doi.org/10.1109/iSemantic50169.2020.9234272","url":null,"abstract":"Voltage sag is a phenomenon of a short time voltage reduction from the nominal value which often occurs in the industrial’s electricity. Certainly, it causes negative impact on industrial production. The solution to this problem is by installing AC-AC converter that is modified into Dynamic Voltage Restorer (DVR). AC-AC converter is used in this design to minimize battery usage and to reduce harmonic components. The method used is transformation of direct-quadrature (dq) synchronous reference frame for single phase systems. It transforms AC variables, from stationary frame to the dq rotating frame into DC variables. The circuit model and the result in Power SIM simulation where the AC-AC converter output voltage is controlled has been described. DVR in this paper is capable to mitigate line voltage up to the remaining 25%.","PeriodicalId":345558,"journal":{"name":"2020 International Seminar on Application for Technology of Information and Communication (iSemantic)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132659568","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 : 2020-09-19DOI: 10.1109/iSemantic50169.2020.9234287
Danny Oka Ratmana, Guruh Fajar Shidik, A. Z. Fanani, Muljono, R. A. Pramunendar
In the Text classification task, feature selections are one of the methods to improve classifier performance. With dimension reduction of the original features, it usually used to get better performance of accuracy, precision, recall, or maybe to accelerate computation time. In this paper, we applied several feature selections method such as Kbest with Chi-Squared Selection, Linear SVC, and Tree-based Selection into five classifiers: Naive Bayes (NB), Decision Tree (DT), K-Nearest Neighbor (KNN), Support Vector Machines (SVM) dan Neural Network (NN). Datasets that we used are collected from Kaggle, Imdb Movie Review 5000 records, and the best F1-Score results are on Linear SVC that running on SVM Classifier 92,32%.
在文本分类任务中，特征选择是提高分类器性能的方法之一。通过对原始特征进行降维，通常可以获得更好的准确率、精密度、查全率等性能，或者加快计算速度。本文将Kbest与卡方选择、线性SVC和基于树的选择等几种特征选择方法应用于朴素贝叶斯(NB)、决策树(DT)、k近邻(KNN)、支持向量机(SVM)和神经网络(NN)五种分类器中。我们使用的数据集是从Kaggle, Imdb Movie Review 5000条记录中收集的，最好的F1-Score结果是在运行在支持向量机分类器92,32%上的线性SVC上。
{"title":"Evaluation of Feature Selections on Movie Reviews Sentiment","authors":"Danny Oka Ratmana, Guruh Fajar Shidik, A. Z. Fanani, Muljono, R. A. Pramunendar","doi":"10.1109/iSemantic50169.2020.9234287","DOIUrl":"https://doi.org/10.1109/iSemantic50169.2020.9234287","url":null,"abstract":"In the Text classification task, feature selections are one of the methods to improve classifier performance. With dimension reduction of the original features, it usually used to get better performance of accuracy, precision, recall, or maybe to accelerate computation time. In this paper, we applied several feature selections method such as Kbest with Chi-Squared Selection, Linear SVC, and Tree-based Selection into five classifiers: Naive Bayes (NB), Decision Tree (DT), K-Nearest Neighbor (KNN), Support Vector Machines (SVM) dan Neural Network (NN). Datasets that we used are collected from Kaggle, Imdb Movie Review 5000 records, and the best F1-Score results are on Linear SVC that running on SVM Classifier 92,32%.","PeriodicalId":345558,"journal":{"name":"2020 International Seminar on Application for Technology of Information and Communication (iSemantic)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132342253","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 : 2020-09-19DOI: 10.1109/iSemantic50169.2020.9234225
Muhammad Misdram, E. Noersasongko, A. Syukur, Purwanto Faculty, Muljono Muljono, Heru Agus Santoso, De Rosal Ignatius Moses Setiadi
The classification method in data mining requires a good learning process to get optimal accuracy. This can be done if the dataset used is ideal, balanced, and has a lot of records, but in reality, it is difficult to get such a dataset. The imputation method is one way to fill in missing values, in a dataset that is not ideal. A large number of missing values can reduce the number of records in the learning process and affect accuracy. This research aims to analyze the effects of zero and mean imputation methods on classification accuracy in small datasets using the Naïve Bayes classifier (NBC) and NBC which have been optimized with Particle Swarm Optimization (PSO). Tests were carried out on five types of datasets originating from the UCI database, where one of the datasets did not require an imputation method because it did not have a missing value. Based on the results of the PSO testing proven to be able to improve the accuracy of the NBC classification on all datasets. While the imputation method can improve classification accuracy up to 4.33% in Biomarker datasets.
{"title":"Analysis of Imputation Methods of Small and Unbalanced Datasets in Classifications using Naïve Bayes and Particle Swarm Optimization","authors":"Muhammad Misdram, E. Noersasongko, A. Syukur, Purwanto Faculty, Muljono Muljono, Heru Agus Santoso, De Rosal Ignatius Moses Setiadi","doi":"10.1109/iSemantic50169.2020.9234225","DOIUrl":"https://doi.org/10.1109/iSemantic50169.2020.9234225","url":null,"abstract":"The classification method in data mining requires a good learning process to get optimal accuracy. This can be done if the dataset used is ideal, balanced, and has a lot of records, but in reality, it is difficult to get such a dataset. The imputation method is one way to fill in missing values, in a dataset that is not ideal. A large number of missing values can reduce the number of records in the learning process and affect accuracy. This research aims to analyze the effects of zero and mean imputation methods on classification accuracy in small datasets using the Naïve Bayes classifier (NBC) and NBC which have been optimized with Particle Swarm Optimization (PSO). Tests were carried out on five types of datasets originating from the UCI database, where one of the datasets did not require an imputation method because it did not have a missing value. Based on the results of the PSO testing proven to be able to improve the accuracy of the NBC classification on all datasets. While the imputation method can improve classification accuracy up to 4.33% in Biomarker datasets.","PeriodicalId":345558,"journal":{"name":"2020 International Seminar on Application for Technology of Information and Communication (iSemantic)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121675513","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 : 2020-09-19DOI: 10.1109/iSemantic50169.2020.9234194
F. Gunawan, S. Yazid
DevOps is a relatively new methodology and culture in software development to deliver software faster and with higher quality. DevOps changes how an organization works by flattening structures, increasing collaboration, and also promotes automation. However, it might pose serious security problems if outsourcing, intellectual property, and data protection are not put into consideration. XYZ Company is a typical small software company that is transforming to embrace DevOps. Digital forensic is a post-mortem mechanism to analyze incidents to help organizations mitigate and doing lawsuits. Digital forensic readiness (DFR) is assessed using Elyas et al [3] DFR framework. DFR improvement is part of the company’s effort to maintain the security level. The method we took and the issues we faced in this transformation are shared in this report.
{"title":"Improving Digital Forensic Readiness in DevOps Context: Lessons Learned from XYZ Company","authors":"F. Gunawan, S. Yazid","doi":"10.1109/iSemantic50169.2020.9234194","DOIUrl":"https://doi.org/10.1109/iSemantic50169.2020.9234194","url":null,"abstract":"DevOps is a relatively new methodology and culture in software development to deliver software faster and with higher quality. DevOps changes how an organization works by flattening structures, increasing collaboration, and also promotes automation. However, it might pose serious security problems if outsourcing, intellectual property, and data protection are not put into consideration. XYZ Company is a typical small software company that is transforming to embrace DevOps. Digital forensic is a post-mortem mechanism to analyze incidents to help organizations mitigate and doing lawsuits. Digital forensic readiness (DFR) is assessed using Elyas et al [3] DFR framework. DFR improvement is part of the company’s effort to maintain the security level. The method we took and the issues we faced in this transformation are shared in this report.","PeriodicalId":345558,"journal":{"name":"2020 International Seminar on Application for Technology of Information and Communication (iSemantic)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126738212","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 : 2020-09-19DOI: 10.1109/iSemantic50169.2020.9234229
Mohammad Iqbal Saryuddin Assaqty, Ying Gao, Ahmad Musyafa, WeiSheng Wen, Quansi Wen, Noni Juliasari
Triggered by the necessity of social distancing due to the current pandemic situation, people increasingly need video conference technology for various activities such as study and work. Currently, there are several public video conference services, both free and paid, that can be utilized without having to set up complex devices and infrastructure. However, in addition to the problems caused by dependence on certain service providers, the public services are mostly run from several centralized places, while the users are from various regions. That causes increased network latency and bandwidth costs between regions. We propose a video conference network that can be openly participated by various service providers that can be optimally utilized based on the closest location and network quality.
{"title":"Independent Public Video Conference Network","authors":"Mohammad Iqbal Saryuddin Assaqty, Ying Gao, Ahmad Musyafa, WeiSheng Wen, Quansi Wen, Noni Juliasari","doi":"10.1109/iSemantic50169.2020.9234229","DOIUrl":"https://doi.org/10.1109/iSemantic50169.2020.9234229","url":null,"abstract":"Triggered by the necessity of social distancing due to the current pandemic situation, people increasingly need video conference technology for various activities such as study and work. Currently, there are several public video conference services, both free and paid, that can be utilized without having to set up complex devices and infrastructure. However, in addition to the problems caused by dependence on certain service providers, the public services are mostly run from several centralized places, while the users are from various regions. That causes increased network latency and bandwidth costs between regions. We propose a video conference network that can be openly participated by various service providers that can be optimally utilized based on the closest location and network quality.","PeriodicalId":345558,"journal":{"name":"2020 International Seminar on Application for Technology of Information and Communication (iSemantic)","volume":"4 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113937680","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 : 2020-09-19DOI: 10.1109/iSemantic50169.2020.9234211
Ari Hilda Mawaddah, Christy Atika Sari, De Rosal Ignatius Moses Setiadi, Eko Hari Rachmawanto
Hiragana is one of the basic types of letters used in Japanese writing. This research proposes the method of recognizing Hiragana's writing characters using the Convolutional Neural Network (CNN) method. At the preprocessing stage, the segmentation process is carried out using the thresholding method to segment, followed by the process of noise removal, resize, and cropping for image normalization. In the CNN training process, maxpooling methods and danse functions are used for the fully connected process. Whereas in the testing phase the accuracy of using the Adam Optimizer tool. By using 1000 image datasets consisting of 50 characters, each with 50 samples, and with a composition of 950 training data and 50 testing data, the accuracy is 95%. This proves that the CNN method has a good performance for Hiragana character recognition.
{"title":"Handwriting Recognition of Hiragana Characters using Convolutional Neural Network","authors":"Ari Hilda Mawaddah, Christy Atika Sari, De Rosal Ignatius Moses Setiadi, Eko Hari Rachmawanto","doi":"10.1109/iSemantic50169.2020.9234211","DOIUrl":"https://doi.org/10.1109/iSemantic50169.2020.9234211","url":null,"abstract":"Hiragana is one of the basic types of letters used in Japanese writing. This research proposes the method of recognizing Hiragana's writing characters using the Convolutional Neural Network (CNN) method. At the preprocessing stage, the segmentation process is carried out using the thresholding method to segment, followed by the process of noise removal, resize, and cropping for image normalization. In the CNN training process, maxpooling methods and danse functions are used for the fully connected process. Whereas in the testing phase the accuracy of using the Adam Optimizer tool. By using 1000 image datasets consisting of 50 characters, each with 50 samples, and with a composition of 950 training data and 50 testing data, the accuracy is 95%. This proves that the CNN method has a good performance for Hiragana character recognition.","PeriodicalId":345558,"journal":{"name":"2020 International Seminar on Application for Technology of Information and Communication (iSemantic)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114519117","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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