2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)最新文献_第2页

Detection of Fake News and Hoaxes on Information from Web Scraping using Classifier Methods 利用分类器方法检测网络抓取信息中的假新闻和骗局

2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) Pub Date : 2021-12-16 DOI: 10.1109/ISRITI54043.2021.9702824

F. W. Wibowo, Akhmad Dahlan, Wihayati

{"title":"Detection of Fake News and Hoaxes on Information from Web Scraping using Classifier Methods","authors":"F. W. Wibowo, Akhmad Dahlan, Wihayati","doi":"10.1109/ISRITI54043.2021.9702824","DOIUrl":"https://doi.org/10.1109/ISRITI54043.2021.9702824","url":null,"abstract":"Current technological developments can make humans get information from the hand through gadget media. However, bad and good impacts are indeed a problem that arises in implementing this technology media. Fake news and hoaxes have developed along with social media applications obtained from these technological media. This paper aims to detect fake news and hoaxes using classification modeling. The classification models implemented in this paper are support vector machine (SVM), random forest, nearest centroid, stochastic gradient descent (SGD) method, decision tree (Tree), bagging, AdaBoost, gradient boosting, multi-layer perceptron artificial neural network (MLP ANN), and K-nearest neighbors (K-NN). The data obtained through web scraping amounted to 1116 data from Indonesian language news, with the distribution of training data and test data for modeling of 70% and 30%. The testing data are 335 data consisting of 205 fake news and hoax data and 130 real news data. Web data content processing using the principle of natural language processing (NLP) methods. The random forest model is the best model for classifying fake news and hoaxes with an accuracy value of 89%. The following models with the next high scores are SVM, Gradient Boosting, AdaBoost, SGD, and Decision Tree, respectively, with the highest scores above 80%. In comparison, other methods have accuracy scores below 80%.","PeriodicalId":156265,"journal":{"name":"2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122003524","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

An XGBoost Model for Age Prediction from COVID-19 Blood Test 基于XGBoost模型的COVID-19血液检测年龄预测

2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) Pub Date : 2021-12-16 DOI: 10.1109/ISRITI54043.2021.9702867

N. N. Qomariyah, A. A. Purwita, M. S. Astriani, S. Asri, D. Kazakov

{"title":"An XGBoost Model for Age Prediction from COVID-19 Blood Test","authors":"N. N. Qomariyah, A. A. Purwita, M. S. Astriani, S. Asri, D. Kazakov","doi":"10.1109/ISRITI54043.2021.9702867","DOIUrl":"https://doi.org/10.1109/ISRITI54043.2021.9702867","url":null,"abstract":"COVID-19 was declared a pandemic by the World Health Organization (WHO) in January 2020. Many studies found that some specific age groups of people have a higher risk of contracting the disease. The gold standard test for the disease is a condition-specific test based on Reverse-Transcriptase Polymerase Chain Reaction (RT-PCR). We have previously shown that the results of a standard suite of non-specific blood tests can be used to indicate the presence of a COVID-19 infection with a high likelihood. We continue our research in this area with a study of the connection between the patients' routine blood test results and their age. Predicting a person's age from blood chemistry is not new in health science. Most often, such results are used to detect the signs of diseases associated with aging and develop new medications. The experiment described here shows that the XGBoost algorithm can be used to predict the patients' age from their routine blood tests. The performance evaluation is very satisfactory, with $R^{2} > 0.80$ and a normalized RMSE below 0.1.","PeriodicalId":156265,"journal":{"name":"2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125806223","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

Efficient Scaling of Convolutional Neural Network for Detecting and Classifying Pneumonia Disease 卷积神经网络在肺炎疾病检测与分类中的高效缩放

2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) Pub Date : 2021-12-16 DOI: 10.1109/ISRITI54043.2021.9702779

Sofia Sa’idah, I. P. Y. N. Suparta, Syifa Rezki Fauziah

引用次数: 0

Indonesian Clickbait Detection Using Improved Backpropagation Neural Network 印度尼西亚使用改进的反向传播神经网络检测标题党

2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) Pub Date : 2021-12-16 DOI: 10.1109/ISRITI54043.2021.9702872

Bellatasya Unrica Nadia, Irene Anindaputri Iswanto

{"title":"Indonesian Clickbait Detection Using Improved Backpropagation Neural Network","authors":"Bellatasya Unrica Nadia, Irene Anindaputri Iswanto","doi":"10.1109/ISRITI54043.2021.9702872","DOIUrl":"https://doi.org/10.1109/ISRITI54043.2021.9702872","url":null,"abstract":"Clickbait has been considered a problem in the modern age of technology, especially in Indonesia. Various attempts have been made to research clickbait detection, however, researches which use Indonesian data are relatively scarce compared to other languages such as English because the availability of Indonesian datasets are lacking. Backpropagation Neural Network was used in clickbait detection on article's title and has achieved quite good accuracy result, however there is still a chance to improve the accuracy. This paper shows the results of using a modified backpropagation neural network algorithm to detect clickbait using article titles when compared to the standard algorithm. The research compares the results of standard stochastic gradient descent algorithm, mini-batch gradient descent algorithm, and a version of stochastic gradient descent with Adam optimizer and three hidden layers. The results show that using Adam optimizer and three hidden layers in stochastic gradient descent algorithm significantly improves the results compared to the standard architecture. The modified algorithm shows a precision score of 78% and a recall and F1 score of 76%, where the standard algorithm has a precision score of 67% and a recall and F1 score of 66%. The resulting algorithm is then implemented to a desktop application, which is considered easy to use.","PeriodicalId":156265,"journal":{"name":"2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114180193","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

Design of Microcontroller-Based Cardiopulmonary Resuscitation (CPR) Practice Tool 基于单片机的心肺复苏术练习工具的设计

2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) Pub Date : 2021-12-16 DOI: 10.1109/ISRITI54043.2021.9702854

Ratna Aisuwarya, M. H. Hersyah, Pandu C. Darmawan

{"title":"Design of Microcontroller-Based Cardiopulmonary Resuscitation (CPR) Practice Tool","authors":"Ratna Aisuwarya, M. H. Hersyah, Pandu C. Darmawan","doi":"10.1109/ISRITI54043.2021.9702854","DOIUrl":"https://doi.org/10.1109/ISRITI54043.2021.9702854","url":null,"abstract":"Cardiac arrest is the leading cause of death in cardiovascular emergencies, both in prehospital and intrahospital events. This case is called out-of-hospital cardiac arrest (OHCA). Quality Cardiopulmonary Resuscitation (CPR) can optimize the return of spontaneous circulation in OHCA. However, many people are not confident in carrying out this procedure, so they need CPR training to respond quickly, responsively, and accurately in assisting OHCA victims. In this study, we will make a tool that resembles the torso and human head and monitor and calculate the parameters that are a factor in the success of the CPR process. The system consists of the compression process, airways process, and breathing process. A microcontroller-based CPR practice tool can function exactly with the CPR process in humans. The designed system can simulate the CPR process by measuring every parameter of CPR, namely compression 30 times in 15–18 seconds with the optimal pressure is ±50kg, 30° angle slope for airways, and two times in 5 seconds for breathing. The design of this tool will provide a more economical solution, making it easier for a relevant public organization to accommodate the tools needed to carry out CPR training so that more people can provide CPR assistance.","PeriodicalId":156265,"journal":{"name":"2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131394778","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

A New Approach for ARP Poisoning Attack Detection Based on Network Traffic Analysis 基于网络流量分析的ARP投毒攻击检测新方法

2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) Pub Date : 2021-12-16 DOI: 10.1109/ISRITI54043.2021.9702860

Yohanes Priyo Atmojo, I. M. D. Susila, Ida Bagus Suradarma, Lilis Yuningsih, Erma Sulistyo Rini, Dandy Pramana Hostiadi

{"title":"A New Approach for ARP Poisoning Attack Detection Based on Network Traffic Analysis","authors":"Yohanes Priyo Atmojo, I. M. D. Susila, Ida Bagus Suradarma, Lilis Yuningsih, Erma Sulistyo Rini, Dandy Pramana Hostiadi","doi":"10.1109/ISRITI54043.2021.9702860","DOIUrl":"https://doi.org/10.1109/ISRITI54043.2021.9702860","url":null,"abstract":"Address Resolution Protocol (ARP) is a communication protocol to map the computer's addresses to the Media Access Control (MAC) address. In its implementation, ARP is abused, known as ARP poisoning Attack. The impact of ARP poisoning attacks is a deadlock to communicate on the network, identity fraud from addressing a computer through illegal access to steal important and confidential information. Several ARP poisoning attack detection models have been introduced. Still, they depend on application tools requiring complex configuration and mostly state ARP poisoning attacks as normal activity. In this paper, a model for detecting ARP poisoning attacks is proposed using the K-NN classification. The proposed model has a contribution to the feature extraction process based on network traffic flows analysis. The results show that the proposed model can detect ARP poisoning attacks more accurately than some classification algorithms with a TPR value of 97.67% and a detection accuracy of 98.7%.","PeriodicalId":156265,"journal":{"name":"2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121797461","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

High Detection of Hydroponic Plant Pak Choy Using Morphological Image Processing 利用形态图像处理技术对水培植物柏菜进行高效检测

2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) Pub Date : 2021-12-16 DOI: 10.1109/ISRITI54043.2021.9702765

Yusuf Ramatullah, Budhi Irawan, C. Setianingsih

{"title":"High Detection of Hydroponic Plant Pak Choy Using Morphological Image Processing","authors":"Yusuf Ramatullah, Budhi Irawan, C. Setianingsih","doi":"10.1109/ISRITI54043.2021.9702765","DOIUrl":"https://doi.org/10.1109/ISRITI54043.2021.9702765","url":null,"abstract":"Hydroponics is a cultivation technique that uses water without using soil by emphasizing nutrients for plants. But in monitoring the height of the plant, people who want to plant hydroponics or who are doing it at home still estimate without knowing exactly, so there are plants whose height is not well monitored. These problems created an idea to create a detection system for plant growth and development to detect height more accurately. Image Processing is a branch of knowledge about image processing processed digitally. The development of technology is speedy in computer vision that makes image processing not only to improve the image alone but also to detect or track an object, read barcodes, and others. The stages of image processing are acquiring images from images, preprocessing, and recognition. The method used in this system is the Morphological Image Processing method. The parameter used is to calculate the height of the Pak Choy hydroponic plant. Using this method, we obtained an accuracy of the system of 93.81% with a light intensity of 15.7 lux. During the 6 weeks of Pak Choy plant growth, the best accuracy was in the 3rd week with an accuracy of 97.24% with an average of 13.65 lux light intensity. The worst accuracy was found in the 2nd week, with an average accuracy of 86.25% at 15 lux light intensity.","PeriodicalId":156265,"journal":{"name":"2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132579943","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

Multi Label Classification Of Retinal Disease On Fundus Images Using AlexNet And VGG16 Architectures 基于AlexNet和VGG16架构的眼底图像视网膜疾病多标签分类

2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) Pub Date : 2021-12-16 DOI: 10.1109/ISRITI54043.2021.9702817

Reyhansyah Prawira, A. Bustamam, P. Anki

引用次数: 0

Analysis of Color and Texture Features for Samarinda Sarong Classification Samarinda Sarong分类的颜色和纹理特征分析

2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) Pub Date : 2021-12-16 DOI: 10.1109/ISRITI54043.2021.9702797

Anindita Septiarini, Rizqi Saputra, Andi Tejawati, M. Wati, H. Hamdani, N. Puspitasari

{"title":"Analysis of Color and Texture Features for Samarinda Sarong Classification","authors":"Anindita Septiarini, Rizqi Saputra, Andi Tejawati, M. Wati, H. Hamdani, N. Puspitasari","doi":"10.1109/ISRITI54043.2021.9702797","DOIUrl":"https://doi.org/10.1109/ISRITI54043.2021.9702797","url":null,"abstract":"Samarinda sarong or Tajong Samarinda is a traditional woven fabric originating from Samarinda, East Borneo, Indonesia. It is made through a weaving process using a loom called a Gedokan (a traditional machine). Unfortunately, many Samarinda people still lack knowledge regarding the type of Samarinda sarong; hence they cannot recognize it. Therefore, an automatic method of image processing-based needed to recognizing and classifying the motif of Samarinda sarong. This method requires appropriate and discriminatory features to obtain the optimal classification results. This work aims to analyze color and texture features to produce discriminative features. The color features used are color moments applied on RGB and HSV color spaces, while texture features were extracted using Gray Level Co-occurrence Matrix (GLCM). Subsequently, those features were reduced using correlation-based feature selection (CFS) followed by applying the Support Vector Machine (SVM) classifier. The dataset used consists of 150 sarong images (50 Belang Hata, 50 Belang Negara, and 50 Kuningsau). The method performance successfully achieved the accuracy of 100% using only 10 color features from a total of 34 features.","PeriodicalId":156265,"journal":{"name":"2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133615222","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: 4

Prediction of Bontang City COVID-19 Data Time Series Using the Facebook Prophet Method 用Facebook先知法预测Bontang市COVID-19数据时间序列

2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) Pub Date : 2021-12-16 DOI: 10.1109/ISRITI54043.2021.9702874

Kurnia Kasturi, M. I. A. Putera, S. R. Natasia

{"title":"Prediction of Bontang City COVID-19 Data Time Series Using the Facebook Prophet Method","authors":"Kurnia Kasturi, M. I. A. Putera, S. R. Natasia","doi":"10.1109/ISRITI54043.2021.9702874","DOIUrl":"https://doi.org/10.1109/ISRITI54043.2021.9702874","url":null,"abstract":"The increasing trend of COVID-19 cases in Bontang makes it the first order of the highest incident rate in East Kalimantan, with a value of 1161.78 cases per 100 thousand inhabitants. The purpose of this study was to predict the increase in COVID-19 cases in Bontang City with a data set of positive confirmed cases, recovered and died of COVID-19 in Bontang city. The data set used starts from March 24, 2020 - March 1, 2021, using the Facebook Prophet method, the Jupyter Notebook application, and the Python programming language. The research process consists of the data collection stage, prediction implementation stage (data preprocessing, processing, performance evaluation, dashboard creation), and analysis of the result. The prediction was performed for up to 92 days until May 5, 2021. The result shows a trend of increasing cases of covid reaching the highest positive value, the highest recovery, and highest death, respectively, of 8695, 6099, and 156 people. According to the model, the average positive predictive error (MAE) and the average positive predictive accuracy value (MAPE) are 0.17 and 17.4%, indicating the positive prediction of contracting covid has good accuracy criteria. The next evaluation for the death prediction is accounted as reasonable accuracy criteria in which MAE and MAPE are 0.27 and 27%, respectively. Lastly, the recovery prediction has MAE of 0.17 and MAPE of 17.4%, implying good accuracy criteria. The study also provides recommendations to the COVID-19 Task Force to prepare the minimum number of PCR Tests by 870 tests and increase the hospitalization occupancy by 294 to control the spreading of the Coronavirus.","PeriodicalId":156265,"journal":{"name":"2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133296879","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