2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)最新文献_第10页

Channel Characteristics for 5G Systems in Urban Rail Viaduct Based on Ray-Tracing 基于光线追踪的城市轨道高架桥5G系统信道特性

2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) Pub Date : 2021-12-16 DOI: 10.1109/ISRITI54043.2021.9702771

Pei Tang

引用次数: 1

Mechanical vibration control and second-order LTI system analysis of an SDOF with harmonic motion 含谐运动的单自由度机械振动控制及二阶LTI系统分析

2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) Pub Date : 2021-12-16 DOI: 10.1109/ISRITI54043.2021.9702778

Ömer Ayvaci, P. Szulczyński

引用次数: 0

Estimate the Survival and Hazard functions by using the Simulation Technique for Modified Weibull Extension Distribution 利用改进威布尔扩展分布的模拟技术估计生存函数和危险函数

2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) Pub Date : 2021-12-16 DOI: 10.1109/ISRITI54043.2021.9702787

Shaima’a B. Yass, Iden H. Al Kanani

{"title":"Estimate the Survival and Hazard functions by using the Simulation Technique for Modified Weibull Extension Distribution","authors":"Shaima’a B. Yass, Iden H. Al Kanani","doi":"10.1109/ISRITI54043.2021.9702787","DOIUrl":"https://doi.org/10.1109/ISRITI54043.2021.9702787","url":null,"abstract":"In this paper, we study the modified Weibull extension distribution by utilizing the Monte Carlo method in the simulation procedure to generate various sample sizes with various replicates of the sample size and using this simulation to compare two estimation methods, the maximum likelihood estimator method and the rank set sampling estimator method, to get the best estimate for the unknown parameters of the modified Weibull extension distribution. It is noted that mean square error values for the maximum likelihood estimator method are better than mean square error values for the rank set sampling estimator method, which means that the maximum likelihood estimator method is the best for estimating the parameters of the modified Weibull extension distribution. Accordingly, we obtain an initial value from the best estimation for starting the process of applying this study in our lives on real data about patients who suffer from acute lymphocytic leukemia disease, and estimate the Survival and hazard functions of this state of patients.","PeriodicalId":156265,"journal":{"name":"2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"657 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":"116429213","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

Supervised Machine Learning Algorithms to Detect Instagram Fake Accounts 监督机器学习算法检测Instagram虚假账户

2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) Pub Date : 2021-12-16 DOI: 10.1109/ISRITI54043.2021.9702833

Michael Jonathan Ekosputra, Angela Susanto, Ferdiana Haryanto, Derwin Suhartono

{"title":"Supervised Machine Learning Algorithms to Detect Instagram Fake Accounts","authors":"Michael Jonathan Ekosputra, Angela Susanto, Ferdiana Haryanto, Derwin Suhartono","doi":"10.1109/ISRITI54043.2021.9702833","DOIUrl":"https://doi.org/10.1109/ISRITI54043.2021.9702833","url":null,"abstract":"Instagram is extremely popular because many celebrities and their fan pages use Instagram as the platform for them to communicate. Instagram offers many media sharing features and has proven to be the most popular social media platform for promoting many brands. As the most popular platform, Instagram also has fake users. Regrettably, some people do malicious activities using fake accounts such as impersonating artists or influencers, hate comments and spread rumors to become viral. Hence, this research aims to detect Instagram fake users based on the user's profile. There are several stages before account authenticity detection is successful, starting from data pre-processing, selecting a classification model, and classification evaluation. The algorithms that are used to create the supervised machine learning model are Logistic Regression, Bernoulli Naive Bayes, Random Forest, Support Vector Machine, and Artificial Neural Network (ANN). This paper tried two experiments. The first is that the default state of the model has no parameters, and no features are added. Second, to improve the accuracy, new features and tuning parameters were added in the experiment. Models that perform better than other models based on the second experiment with new features and parameters are Logistic Regression and Random Forest, with an accuracy of 0.93.","PeriodicalId":156265,"journal":{"name":"2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"24 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":"125118168","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

Design of Transformer Oil Purification Equipment 变压器油净化设备的设计

2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) Pub Date : 2021-12-16 DOI: 10.1109/ISRITI54043.2021.9702769

Y. Siregar, Hendra Zulkarnain, Ayumi Fadhillah

引用次数: 0

Peatland Data Fusion for Forest Fire Susceptibility Prediction Using Machine Learning 基于机器学习的泥炭地数据融合森林火灾易感性预测

2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) Pub Date : 2021-12-16 DOI: 10.1109/ISRITI54043.2021.9702762

N. Hidayanto, A. H. Saputro, D. Nuryanto

{"title":"Peatland Data Fusion for Forest Fire Susceptibility Prediction Using Machine Learning","authors":"N. Hidayanto, A. H. Saputro, D. Nuryanto","doi":"10.1109/ISRITI54043.2021.9702762","DOIUrl":"https://doi.org/10.1109/ISRITI54043.2021.9702762","url":null,"abstract":"Forest fires have been a severe hydrometeorological hazard during the dry season in Indonesia. Pulang Pisau Regency in Central Kalimantan has become one of the most forest fires affected areas during the 2015 El Nino event. Based on MODIS data, more than 120.000 hotspots have been recorded between 2014 and 2019. Previous studies concluded that peatlands act as contributing factor to forest fires in this country. This study proposed the peat-effect on the development of machine learning models for forest fire susceptibility (FFS), which can be alternative tool to support forest fire disaster management. In addition to the peat effect, such as elevation, slope, Normalized Difference Vegetation Index (NDVI), rainfall, distance from the road network, and distance from the residents also analyzed. Those variables were divided into training (2014 – 2018) and testing (2019). Random Forest (RF), Support Vector Classifications (SVC), and Gradient Boosting Classification (GBC) models were used to build the FFS map. The experiment results showed an increase in Area Under Curve (AUC) from 0.84 – 0.87 to 0.87 – 0.88 with the addition of the peat depth variable. The complete test resulted in the highest accuracy of 0.80 in the RF and SVC.","PeriodicalId":156265,"journal":{"name":"2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"35 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":"117201093","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

Detection of Covid-19 Based on Lung Ultrasound Image Using Convolutional Neural Network Architectures 基于卷积神经网络结构的肺部超声图像检测Covid-19

2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) Pub Date : 2021-12-16 DOI: 10.1109/ISRITI54043.2021.9702780

C. Fatichah, Muhammad Fadhlan Min Robby, S. Hidayati, T. Mustaqim

引用次数: 0

A Customized DeepICF+a with BiLSTM for Better Recommendation 一个带有BiLSTM的定制DeepICF+ A，用于更好的推荐

2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) Pub Date : 2021-12-16 DOI: 10.1109/ISRITI54043.2021.9702863

Maria Anastasia Br. Simanullang, Christina Clara, Reza Oktovian Siregar, M. E. Simaremare, T. Panggabean

{"title":"A Customized DeepICF+a with BiLSTM for Better Recommendation","authors":"Maria Anastasia Br. Simanullang, Christina Clara, Reza Oktovian Siregar, M. E. Simaremare, T. Panggabean","doi":"10.1109/ISRITI54043.2021.9702863","DOIUrl":"https://doi.org/10.1109/ISRITI54043.2021.9702863","url":null,"abstract":"Recommendations are expected to help users make decisions when users are faced with a large amount of information. One technique for developing a recommendation system is item-based collaborative filtering (ICF), where this approach recommends items based on their similarity to the items with which users already interacted and comparable decisions made by other users. In recent years, many ICF approaches have made significant progress by using deep neural networks to learn similarities from data. Developing a recommender system based on ICF+attention approach has shown a significant output. In this research, we conducted experiments on MovieLens 1M dataset to build movie recommendation. A recent study demonstrates a good result by HR= 0.7084 and NDCG = 0.4380 of its performance. Previous work implemented MLP to predict the next watched movies. MLP performs poorly for prediction compared to BiLSTM performs better for prediction if the data in a historical model. In this work, we modify the architecture of the previous study (DeepICF+a with MLP) by replacing MLP model with BiLSTM Our work shows that the performance have a better result by 0.7121 and 0.4399 for HR and NDCG, respectively with configuration embedding size = 32, layers BiLSTM [64, 32, 16] and number negative = 8. The DeepICF+a with BiLSTM recommendation model provides a better optimization model for Train Loss with a score of 0.2064 and a Test Loss with a score of 0.1263 compared to MLP for train loss with a score of 0.2127 and a Test Loss with a score of 0.3167.","PeriodicalId":156265,"journal":{"name":"2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"44 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":"121753302","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

Discrete Cosine Transform-Based Key Generation Scheme for Indoor Environment 基于离散余弦变换的室内环境密钥生成方案

2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) Pub Date : 2021-12-16 DOI: 10.1109/ISRITI54043.2021.9702786

Suwadi, Mike Yuliana, Wirawan

引用次数: 0

The Intention to Use Online Groceries Shopping during the COVID19 Pandemic 在covid - 19大流行期间使用在线杂货购物的意图

2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) Pub Date : 2021-12-16 DOI: 10.1109/ISRITI54043.2021.9702827

L. Wijaya, H. Helen, S. Pramudya, Andina Sulistiowati

引用次数: 0