2021 4th International Conference of Computer and Informatics Engineering (IC2IE)最新文献

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Raspberry Pi-based Decubitus Reducing Mattress with Air Pressure Monitoring System and Air Leaks Detector 基于树莓派的减压床垫,配有气压监测系统和漏气检测器
2021 4th International Conference of Computer and Informatics Engineering (IC2IE) Pub Date : 2021-09-14 DOI: 10.1109/ic2ie53219.2021.9649373
H. Pranjoto, William Chandra Sarwono, Andrew Febrian Miyata, L. Agustine
{"title":"Raspberry Pi-based Decubitus Reducing Mattress with Air Pressure Monitoring System and Air Leaks Detector","authors":"H. Pranjoto, William Chandra Sarwono, Andrew Febrian Miyata, L. Agustine","doi":"10.1109/ic2ie53219.2021.9649373","DOIUrl":"https://doi.org/10.1109/ic2ie53219.2021.9649373","url":null,"abstract":"Decubitus ulcers appear when the skin receives intense pressure for a short time or mild pressure for a longer time. Currently, nurses assist immobilized patients to change their position every 2 hours to avoid decubitus ulcers. Another option is using the pressure-reducing mattress. This mattress has the feature to change the pressure strength, but the air pressure and leakage are unknown. Both of these problems will be overcome by the automatic mattress developed in this study. The developed mattress uses gas pressure sensors, a Raspberry Pi, solenoid valves, and an AC air pump. The mattress pumping process is controlled based on the air pressure from 0.7 to 2.1 PSI in 3.5 minutes for each airbag group. The airbags are controlled to form wavelike contours with the feedback from the gas pressure sensors. A prolonged period to reach maximum pressure indicates the air leaks. The testing result shows that the control system can maintain the pressure of the airbag from 0.7 to 2.1 PSI accurately during the pumping process, with or without load on the mat. The accuracy of the pumping duration for each airbag group is 96.31% from the 3.5 minutes goal and gives no meaningful effect to skin pressure.","PeriodicalId":178443,"journal":{"name":"2021 4th International Conference of Computer and Informatics Engineering (IC2IE)","volume":"46 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125678418","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}
引用次数: 2
VIRKOM as Augmented Reality Application for Visualization of Computer Maintenance Learning Material 增强现实技术在计算机维护学习材料可视化中的应用
2021 4th International Conference of Computer and Informatics Engineering (IC2IE) Pub Date : 2021-09-14 DOI: 10.1109/ic2ie53219.2021.9649391
W. Hidayat, Muchammad Ryan Pratama, Hanif Samsu Angga Risky, R. Wakhidah, T. A. Sutikno, Alfyananda Kurnia Putra
{"title":"VIRKOM as Augmented Reality Application for Visualization of Computer Maintenance Learning Material","authors":"W. Hidayat, Muchammad Ryan Pratama, Hanif Samsu Angga Risky, R. Wakhidah, T. A. Sutikno, Alfyananda Kurnia Putra","doi":"10.1109/ic2ie53219.2021.9649391","DOIUrl":"https://doi.org/10.1109/ic2ie53219.2021.9649391","url":null,"abstract":"Practical learning on computer maintenance for vocational students during the COVID-19 pandemic cannot be implemented optimally. Hardware access problems that are difficult to reach by students cause the learning barriers in this subject to be even greater. Therefore, through this research, a mobile-based learning media was developed to visualize computer component devices with AR technology and 3D animation. The research method used is the ADDIE model. The research begins by diagnosing the problem, describing needs, and finding appropriate solutions for computer maintenance learning. Next, the product design process and user journey are carried out and then develop applications with 3D animation assets and learning materials. Implementation activities go through an evaluation process to media and content experts to determine the validity of the application. The media and content validation instrument consists of 4 aspects with 46 items. This media is equipped with 3D objects that can be used to help students observe computer hardware. Media validation got a value of 79.49% and was included in the valid criteria so that it could be used in learning. Content validation is in the valid category with a value of 80.2%. Several improvements were made to increase the usability and attractiveness of the media so that students' interest in using the media increased. In the future this media can be applied in learning so that it can be seen the impact, both on learning outcomes, student interest and critical thinking on computer troubleshooting.","PeriodicalId":178443,"journal":{"name":"2021 4th International Conference of Computer and Informatics Engineering (IC2IE)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114343285","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}
引用次数: 1
StrokIndo: An Expert System to Prevent Stroke for Indonesian StrokIndo:印尼预防中风的专家系统
2021 4th International Conference of Computer and Informatics Engineering (IC2IE) Pub Date : 2021-09-14 DOI: 10.1109/ic2ie53219.2021.9649125
R. Vinarti, Riris Diana Rachmayanti, R. Tyasnurita, Faizal Mahananto, Edwin Riksakomara
{"title":"StrokIndo: An Expert System to Prevent Stroke for Indonesian","authors":"R. Vinarti, Riris Diana Rachmayanti, R. Tyasnurita, Faizal Mahananto, Edwin Riksakomara","doi":"10.1109/ic2ie53219.2021.9649125","DOIUrl":"https://doi.org/10.1109/ic2ie53219.2021.9649125","url":null,"abstract":"Stroke is the leading cause of death and long-term disability in Indonesia. However, our preliminary study found that Indonesian needed more information about their personal risks and knowledge on how to reduce their risks of stroke (if any). Even though information about stroke is available on many health websites and videos, those media lack readers’ engagement because of generalization in information they provide. One way to increase readers’ engagement is personalization. Stroke risk calculator is a media that capable to personalize risk calculation based on someone’s profile. Also, it can educate Indonesian about stroke risk awareness by understanding their profile more. In this paper, we listed all apps and websites which calculate risks of stroke and found that three crucial points to educate people were not available on the listed platforms. Those are (1) static ratio of risk factors, (2) the absence of reasons for the calculated results, (3) less personalized advice on how to reduce those risks. To fill these gaps, an updateable knowledge-base and specific inference engine are designed and developed to be an expert system, StrokIndo. For current version, StrokIndo contains nine stroke risk factors that found in Indonesian population studies. Using the knowledge-base and inference engine that were designed specifically for stroke, StrokIndo is able to calculate stroke risk and advise each user with relevant information on how to reduce stroke risk. Also, StrokIndo can preserve knowledge related to stroke and use them to calculate stroke risk. In the next version, some updates on stroke knowledge may be implemented. From the testing phase, more than half users reported that the personalized advice improved their knowledge to reduce the risks of stroke they might have. Moreover, almost all of them (94%) would follow the given advice. If users consistently act on the personalized advice in the long run, we believe that the numbers of stroke incidents in Indonesia will decrease.","PeriodicalId":178443,"journal":{"name":"2021 4th International Conference of Computer and Informatics Engineering (IC2IE)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133894335","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}
引用次数: 0
Analysis of Software Defined Network (SDN) using Opendaylight Controller with ANOVA Repeated Measures 使用Opendaylight控制器和ANOVA重复测量分析软件定义网络(SDN)
2021 4th International Conference of Computer and Informatics Engineering (IC2IE) Pub Date : 2021-09-14 DOI: 10.1109/ic2ie53219.2021.9649084
Rifki Izdihar Oktavian Abas Pullah, Dodon Turianto Nugrahadi, Muhammad Itqan Mazdadi, Andi Farmadi, Ahmad Rusadi
{"title":"Analysis of Software Defined Network (SDN) using Opendaylight Controller with ANOVA Repeated Measures","authors":"Rifki Izdihar Oktavian Abas Pullah, Dodon Turianto Nugrahadi, Muhammad Itqan Mazdadi, Andi Farmadi, Ahmad Rusadi","doi":"10.1109/ic2ie53219.2021.9649084","DOIUrl":"https://doi.org/10.1109/ic2ie53219.2021.9649084","url":null,"abstract":"The rapid development of technology today makes the technology around us also become more advanced and continues to grow, this has an impact on the development of the internet network. Technology such as Software Defined Network (SDN) is needed because it results in improved performance in network management, control and data handling that allows it to be managed centrally and more easily by network administrators by separating the control plane and data plane. In this study, an analysis of the SDN architecture was carried out using the Opendaylight controller based on the parameters of throughput, delay and jitter which then can be seen how the performance of the SDN architecture with Opendaylight controller in a different topology by increasing the number of nodes. The throughput test shows that the custom topology has a significant high throughput with a p-value of 1.382E-251 and has a better average throughput value among other topologies. The linear topology a better increase in delay value with a p-value of 1.07738E-62. The jitter value was significantly increase when there is an increase in the number of nodes is in the star topology with a p-value of 1.74483E-09.","PeriodicalId":178443,"journal":{"name":"2021 4th International Conference of Computer and Informatics Engineering (IC2IE)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116106123","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}
引用次数: 0
Determination of Sex and Race in Forensic Anthropology: A Comparison of Artificial Neural Network and Support Vector Machine 法医人类学中性别和种族的确定:人工神经网络与支持向量机的比较
2021 4th International Conference of Computer and Informatics Engineering (IC2IE) Pub Date : 2021-09-14 DOI: 10.1109/ic2ie53219.2021.9649182
D. Nasien, M. H. Adiya, Iis Afrianty, N. A. Ali, Azurah A. Samah, Y. Rahayu
{"title":"Determination of Sex and Race in Forensic Anthropology: A Comparison of Artificial Neural Network and Support Vector Machine","authors":"D. Nasien, M. H. Adiya, Iis Afrianty, N. A. Ali, Azurah A. Samah, Y. Rahayu","doi":"10.1109/ic2ie53219.2021.9649182","DOIUrl":"https://doi.org/10.1109/ic2ie53219.2021.9649182","url":null,"abstract":"One of the topics covered in forensic anthropology is an investigation of skeletal remains where various properties of the skeleton are to be determined. Typically, the sample found is incomplete, meaning some bone parts are missing or destroyed, and the analysis needs to depend on limited information obtained from what is available. This research focuses on arm, leg, clavicle, and scapula bones, with 8 bone parts in total. Each part is either used independently from the other or considered altogether (aggregate) to test its usability in finding out the owner’s identity when facing such a situation. Bone measurements obtained from the database were used as input data for two different classifiers, namely artificial neural networks and supporting vector machines, with two identification targets, namely sex and race. All of the input data came from publicly available Robert J. Terry Anatomical Skeletal Collection Postcranial Osteo-metric database. Accuracies of 86.67% and 70.78% are obtained for those targets using clavicle and aggregate, respectively, showing that using all information possible from the sample rather than focusing on a single bone part is sometimes useful in improving identification accuracy.","PeriodicalId":178443,"journal":{"name":"2021 4th International Conference of Computer and Informatics Engineering (IC2IE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126144936","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}
引用次数: 1
Development of Deep Learning-Based Mobile Application for Predicting Diabetes Mellitus 基于深度学习的糖尿病预测移动应用开发
2021 4th International Conference of Computer and Informatics Engineering (IC2IE) Pub Date : 2021-09-14 DOI: 10.1109/ic2ie53219.2021.9649235
Christopher G. Estonilo, E. Festijo
{"title":"Development of Deep Learning-Based Mobile Application for Predicting Diabetes Mellitus","authors":"Christopher G. Estonilo, E. Festijo","doi":"10.1109/ic2ie53219.2021.9649235","DOIUrl":"https://doi.org/10.1109/ic2ie53219.2021.9649235","url":null,"abstract":"With the growing demand for intelligent services on mobile devices, deep learning-based mobile applications are expected to progress even further in the coming year. In the advent of this technology, a deep learning model embedded in a mobile application can play a vital role in predicting a certain kind of disease like diabetes mellitus. Many studies have been performed in the past few years to predict diabetes mellitus using various algorithms of machine learning and deep learning. However, these researches are mostly focused on the development of the predicting model. This study aimed for developing a mobile application that is deep learning-based for predicting diabetes mellitus. Using the TensorFlow platform, the Sequential function was used in building the diabetes prediction model. The model was then transformed into a ‘tflite’ format which was deployed in the development of mobile application using the Android Studio integrated development environment (IDE) to predict if a person has diabetes mellitus. The deep learning model demonstrated considerable accuracy of 93%. Additionally, the application also provides some important instructions for the end-users and facts about diabetes mellitus. The developed deep learning-based mobile application is an important new technology for diabetes mellitus early detection. If the prediction is positive, the lifestyle could change, and a serious complication will be avoided.","PeriodicalId":178443,"journal":{"name":"2021 4th International Conference of Computer and Informatics Engineering (IC2IE)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126179778","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}
引用次数: 2
Diabetic Retinopathy Detection using Deep Convolutional Neural Network with Visualization of Guided Grad-CA 基于视觉引导的深度卷积神经网络检测糖尿病视网膜病变
2021 4th International Conference of Computer and Informatics Engineering (IC2IE) Pub Date : 2021-09-14 DOI: 10.1109/ic2ie53219.2021.9649326
R. H. Paradisa, A. Bustamam, A. Victor, A. Yudantha, Devvi Sarwinda
{"title":"Diabetic Retinopathy Detection using Deep Convolutional Neural Network with Visualization of Guided Grad-CA","authors":"R. H. Paradisa, A. Bustamam, A. Victor, A. Yudantha, Devvi Sarwinda","doi":"10.1109/ic2ie53219.2021.9649326","DOIUrl":"https://doi.org/10.1109/ic2ie53219.2021.9649326","url":null,"abstract":"One of the complications of diabetes that represents a serious threat to world health is Diabetic Retinopathy (DR). High blood sugar levels in people with diabetes can damage the blood vessels in the retina and causing blindness. DR can be detected by examining the fundus image by an ophthalmologist. However, the limited number of ophthalmologists who can analyze fundus image is an obstacle because the number of DR sufferers continues to increase. Therefore, an automated system is needed to help doctors diagnose the disease. Researchers have developed deep learning techniques as Artificial Intelligence (AI) approach to finding DR in fundus images. In this research, we use the Deep Convolutional Neural Networks method with InceptionV3 structure and various optimizers such as the Stochastic Gradient Descent with Momentum (SGDM), Root Mean Square Propagation (RMSprop), and Adaptive Moment Estimation (Adam). The fundus image dataset previously through the augmentation and preprocessing steps to make it easier for the model to recognize the image. The InceptionV3 model with the Adam optimizer gave the best results in detecting DR lesions from the Kaggle dataset with 96% accuracy. This paper also presents a Grad-CAM guided activation map that can describe the position of the suspicious lesion to explain the results of DR detection.","PeriodicalId":178443,"journal":{"name":"2021 4th International Conference of Computer and Informatics Engineering (IC2IE)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128987128","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}
引用次数: 2
Effect of Various Data Preprocessing in Sequence Embedding-Based Machine Learning for Human-Virus PPI Classification 基于序列嵌入的机器学习中各种数据预处理对人类病毒PPI分类的影响
2021 4th International Conference of Computer and Informatics Engineering (IC2IE) Pub Date : 2021-09-14 DOI: 10.1109/ic2ie53219.2021.9649426
Fatma Indriani, Kunti Rabiatul Mahmudah, K. Satou
{"title":"Effect of Various Data Preprocessing in Sequence Embedding-Based Machine Learning for Human-Virus PPI Classification","authors":"Fatma Indriani, Kunti Rabiatul Mahmudah, K. Satou","doi":"10.1109/ic2ie53219.2021.9649426","DOIUrl":"https://doi.org/10.1109/ic2ie53219.2021.9649426","url":null,"abstract":"Identifying human-virus protein-protein interactions (PPI) is an important task which is increasingly researched using computational methods. Previous research shows that using doc2vec encoding scheme for features combined with Random Forest classifier gives promising performance. However, human-virus PPI data are usually imbalanced, and additional preprocessing step has not been investigated in this task. In this work, we investigated various preprocessing methods and modifications to improve classification performance. The result shows that a modification in the feature formulation method, combined with random oversampling can improve the classification AUC result from 0.9414 to 0.9448.","PeriodicalId":178443,"journal":{"name":"2021 4th International Conference of Computer and Informatics Engineering (IC2IE)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114436727","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}
引用次数: 0
Message Digest 5 (MD-5) Decryption Application using Python-Based Dictionary Attack Technique 基于python字典攻击技术的消息摘要5 (MD-5)解密应用
2021 4th International Conference of Computer and Informatics Engineering (IC2IE) Pub Date : 2021-09-14 DOI: 10.1109/ic2ie53219.2021.9649020
I. Neforawati, Defiana Arnaldy
{"title":"Message Digest 5 (MD-5) Decryption Application using Python-Based Dictionary Attack Technique","authors":"I. Neforawati, Defiana Arnaldy","doi":"10.1109/ic2ie53219.2021.9649020","DOIUrl":"https://doi.org/10.1109/ic2ie53219.2021.9649020","url":null,"abstract":"The growth of information in this digital era is growing very rapidly throughout the world. All forms of information needed can be easily and quickly obtained, especially this is obtained by using a technology called the internet. Of its various types, the web has become one of the most widely used technologies known to everyone in the world. With all the functions provided, the web can accommodate and present various kinds of information needed by users anyone. A web contains a database that is used to store various data that can be seen by internet users as well as sensitive data, such as usernames and passwords. Therefore, the website really needs data security related to the database so that it cannot be accessed by the public other than the owner of the data. The popular technique used is message digest 5 (MD5) which can be applied to encrypt databases on a website, but message digest 5 (MD5) has a weakness. To test the weakness of MD5, in this research an application is made that can decrypt MD5 very quickly accompanied by a dictionary attack technique. The dictionary attack technique uses rockyou.txt which contains about 14,344,392 unique passwords, the application made will test how fast MD5 decryption is. The results of this study indicate that the application made can decrypt MD5 from the wordlist used very quickly. However, not all words can be decrypted because they are not in the word list and the dictionary attack technique is different from the brute force method which tests password decryption, i.e. word by word.","PeriodicalId":178443,"journal":{"name":"2021 4th International Conference of Computer and Informatics Engineering (IC2IE)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126559723","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}
引用次数: 3
Analysis of New Features on the Performance of the Support Vector Machine Algorithm in Classification of Natural Disaster Messages 支持向量机算法在自然灾害信息分类中的性能新特征分析
2021 4th International Conference of Computer and Informatics Engineering (IC2IE) Pub Date : 2021-09-14 DOI: 10.1109/ic2ie53219.2021.9649107
Khairisyah Yuliani Firlia, M. Reza Faisal, Dwi Kartini, Radityo Adi Nugroho, Friska Abadi
{"title":"Analysis of New Features on the Performance of the Support Vector Machine Algorithm in Classification of Natural Disaster Messages","authors":"Khairisyah Yuliani Firlia, M. Reza Faisal, Dwi Kartini, Radityo Adi Nugroho, Friska Abadi","doi":"10.1109/ic2ie53219.2021.9649107","DOIUrl":"https://doi.org/10.1109/ic2ie53219.2021.9649107","url":null,"abstract":"When a natural disaster occurs, Twitter is one social media people use to give their opinion. The classification of natural disaster messages on Twitter has been widely used in research to determine messages from direct eyewitnesses. This message is crucial because it can be used to determine the location and time of the incident. One of the essential parts in the classification of natural disaster messages is feature extraction. The feature extraction technique commonly used is n-gram with TF-IDF weighting. In the research, we use structured data generated by n-gram and TF-IDF with three additional new features: word count, the presence of images, and URLs in tweets. The classification method used is the Support Vector Machine method multiclass with Kernel Gaussian Radial Basis Function. The results of this research are: the accuracy of the features generated by n-gram and TFIDF is 75.43%. The accuracy of the added features of the three new features is 77.50%. These results conclude that the three new features that we use can improve natural disaster message classification performance.","PeriodicalId":178443,"journal":{"name":"2021 4th International Conference of Computer and Informatics Engineering (IC2IE)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130381509","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}
引用次数: 2
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