2021 1st International Conference on Computer Science and Artificial Intelligence (ICCSAI)最新文献_第4页

Exploration of React Native Framework in designing a Rule-Based Application for healthy lifestyle education React Native框架在健康生活方式教育基于规则应用设计中的探索

2021 1st International Conference on Computer Science and Artificial Intelligence (ICCSAI) Pub Date : 2021-10-28 DOI: 10.1109/iccsai53272.2021.9609763

Anik Hanifatul Azizah, Siti Zuliatul Faidah, Muhammad Bahrul Ulum, Putri Handayani

{"title":"Exploration of React Native Framework in designing a Rule-Based Application for healthy lifestyle education","authors":"Anik Hanifatul Azizah, Siti Zuliatul Faidah, Muhammad Bahrul Ulum, Putri Handayani","doi":"10.1109/iccsai53272.2021.9609763","DOIUrl":"https://doi.org/10.1109/iccsai53272.2021.9609763","url":null,"abstract":"Researches indicates the implementation of hybrid applications is more profitable for mobile application development solutions. Hybrid application combine the advantages of web and native application. React Native is a hybrid framework for developing mobile applications. React Native framework can create within two platform applications by compiling the code written in React. The utilization of React Native in a rule-based application can build a solution for healthy lifestyle education. The aim of this study is to build a rule-based application for healthy reminder in daily activities. By developing an application in React Native, the study will design a comprehensive mobile application that make users easy to use. Moreover, this study will explore and construct an application that guide the user to maintain their daily health. To develop the application, author uses waterfall methodology. Before building the application, a systematic survey was conducted to gain relevant data from the users and also to invent a rule-based that will be the way of thinking of the application design. The results indicate that React Native framework can be utilized in building a reminder application about healthy lifestyle education. This study built a mobile application product that has good performance and helps users change the lifestyle in order to improve the quality of a healthy lifestyle.","PeriodicalId":426993,"journal":{"name":"2021 1st International Conference on Computer Science and Artificial Intelligence (ICCSAI)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121071343","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

Towards Classification of Personality Prediction Model: A Combination of BERT Word Embedding and MLSMOTE 面向分类的人格预测模型:BERT词嵌入与MLSMOTE的结合

2021 1st International Conference on Computer Science and Artificial Intelligence (ICCSAI) Pub Date : 2021-10-28 DOI: 10.1109/iccsai53272.2021.9609750

Henry Lucky, Roslynlia, Derwin Suhartono

{"title":"Towards Classification of Personality Prediction Model: A Combination of BERT Word Embedding and MLSMOTE","authors":"Henry Lucky, Roslynlia, Derwin Suhartono","doi":"10.1109/iccsai53272.2021.9609750","DOIUrl":"https://doi.org/10.1109/iccsai53272.2021.9609750","url":null,"abstract":"The rise in internet usage improved digital communication and an increase in user data, particularly on social media. The information supplied from social media, including Twitter, can be used to retrieve user personality. In this paper, we experiment to predict user's personality based on Big Five Personality Trait on Twitter, particularly Indonesian users. We focus on using XGBoost classifier as it gives promising result in the previous study. We experiment on using multiple Bidirectional Encoder Representations from Transformer (BERT) models for extracting contextual word embeddings from tweets data to see the best model. We also address the imbalanced dataset problem with Multilabel Synthetic Minority Oversampling Technique (MLSMOTE). Our research found that the IndoBERT model, which is pre-trained with general data including Indonesian Twitter tweets, has the best overall performance on our dataset. We also found that using MLSMOTE could increase the accuracy up to 19,91% and the F1 up to 19,38%, which is a huge increment and shows that MLSMOTE works well with our dataset.","PeriodicalId":426993,"journal":{"name":"2021 1st International Conference on Computer Science and Artificial Intelligence (ICCSAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130811236","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: 5

Indonesian Banking Stock Price Prediction with LSTM and Random Walk Method 基于LSTM和随机漫步法的印尼银行股价格预测

2021 1st International Conference on Computer Science and Artificial Intelligence (ICCSAI) Pub Date : 2021-10-28 DOI: 10.1109/iccsai53272.2021.9609752

Mike Christ Heru, R. N. Rachmawati, Derwin Suhartono

{"title":"Indonesian Banking Stock Price Prediction with LSTM and Random Walk Method","authors":"Mike Christ Heru, R. N. Rachmawati, Derwin Suhartono","doi":"10.1109/iccsai53272.2021.9609752","DOIUrl":"https://doi.org/10.1109/iccsai53272.2021.9609752","url":null,"abstract":"Investing in stock market is the challenging for every new investor, as the stock market always move in dynamic way. When using technical or fundamental analysis approach, investor can reduce the loss probability and increase the profit probability. When one tries to analyze the stock market data, any techniques can be used. For example, the LSTM as the part of Neural Network and Machine Learning, which need past data to train the model and try to give the best prediction result based on the model generated by the data. The other example of techniques used in this paper is the Random Walk which come from Integrated Nested Laplace Approximation (INLA) library of R language which approximate the Bayesian Inference. Both methods are used to get the best prediction result. To get some comparison, the data can be split to several period and from several choices, the best result can be generated. As a result, the LSTM always predict the best result (comparison using the RMSEP / Root Mean Square Error for Prediction value) and the more data fed to the model will produce lower rate of RMSE, which is good for prediction result.","PeriodicalId":426993,"journal":{"name":"2021 1st International Conference on Computer Science and Artificial Intelligence (ICCSAI)","volume":"252 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134191970","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

Immersive Experience with Non-Player Characters Dynamic Dialogue 具有非玩家角色动态对话的沉浸式体验

2021 1st International Conference on Computer Science and Artificial Intelligence (ICCSAI) Pub Date : 2021-10-28 DOI: 10.1109/ICCSAI53272.2021.9609725

Muhammad Fikri Hasani, Y. Udjaja

引用次数: 0

Predicting Stock Market Prices using Time Series SARIMA 利用时间序列SARIMA预测股票市场价格

2021 1st International Conference on Computer Science and Artificial Intelligence (ICCSAI) Pub Date : 2021-10-28 DOI: 10.1109/ICCSAI53272.2021.9609720

Daryl, Aditya Winata, Sena Kumara, Derwin Suhartono

引用次数: 2

Building Natural Language Understanding System from User Manual to Execute Office Application Functions 从用户手册构建自然语言理解系统以执行办公应用程序功能

2021 1st International Conference on Computer Science and Artificial Intelligence (ICCSAI) Pub Date : 2021-10-28 DOI: 10.1109/iccsai53272.2021.9609755

Anis Cherid, E. Winarko, M. Sadikin, Afiyati Reno

{"title":"Building Natural Language Understanding System from User Manual to Execute Office Application Functions","authors":"Anis Cherid, E. Winarko, M. Sadikin, Afiyati Reno","doi":"10.1109/iccsai53272.2021.9609755","DOIUrl":"https://doi.org/10.1109/iccsai53272.2021.9609755","url":null,"abstract":"To improve the flexibility of using office applications, it takes a natural language interface that can execute the office application's functions. To achieve this, the office application must have an inference engine that can automatically detect the intents and the entities contained in an instruction, into an algorithm to execute the related functions in the application on the entities. Creating a natural language understanding system by manually listing various rules in a knowledge base, is very inefficient and makes the effort of using natural language to execute office application functions too expensive. The author proposes conducting research to build a natural language understanding system more efficient, by analyzing the text contained in the office application user manual, by means of natural language processing technology. We propose to build a variety of simple rules automatically, using the text in the user manual, which is specifically crafted to facilitate and support natural language processing technology. In future works, research will be conducted to automatically build various complicated rules, from analysis of the text from common and commercially available user manual. In this preliminary study, the necessary steps to execute the application functions, is executed on an office application prototype specifically built for this study.","PeriodicalId":426993,"journal":{"name":"2021 1st International Conference on Computer Science and Artificial Intelligence (ICCSAI)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122088112","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

Effectiveness of LMS in Online Learning by Analyzing Its Usability and Features 通过分析LMS的可用性和特点，分析LMS在在线学习中的有效性

2021 1st International Conference on Computer Science and Artificial Intelligence (ICCSAI) Pub Date : 2021-10-28 DOI: 10.1109/iccsai53272.2021.9609757

Iulia Duta, Rio, Mochamad Rizky Febriansyah, Maria Susan Anggreainy

{"title":"Effectiveness of LMS in Online Learning by Analyzing Its Usability and Features","authors":"Iulia Duta, Rio, Mochamad Rizky Febriansyah, Maria Susan Anggreainy","doi":"10.1109/iccsai53272.2021.9609757","DOIUrl":"https://doi.org/10.1109/iccsai53272.2021.9609757","url":null,"abstract":"With the advancement of technology, education and learning processes have evolved and accommodated by many forms of digital applications and services, one of which that is prevalent in most educational institutions is none other than LMS (Learning Management System). In this current digital era, the world is transitioning from offline to online activities including schools and universities due to certain circumstances. This transition affects LMS to fully support online learning as opposed to supplementary support for offline learning process. Therefore, we conduct this research to find out how effective are currently available LMS to support online learning. Our approach is by analyzing LMS features by conducting workflow testing to test the effectiveness of the LMS for online learning. We align our findings in comparison to user satisfaction survey to reach the conclusion. We will see how effective is our current technology to support education especially online learning. We will know what modules are done right, what needs to be improved, which one is important and not as important, and what addition can be made as a reference to enhance future LMS development. (Abstract)","PeriodicalId":426993,"journal":{"name":"2021 1st International Conference on Computer Science and Artificial Intelligence (ICCSAI)","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122333965","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

Proceedings of 2021 1st International Conference on Computer Science and Artificial Intelligence (ICCSAI) 2021第一届计算机科学与人工智能国际会议论文集(ICCSAI)

2021 1st International Conference on Computer Science and Artificial Intelligence (ICCSAI) Pub Date : 2021-10-28 DOI: 10.1109/iccsai53272.2021.9609785

引用次数: 0

Finetunning IndoBERT to Understand Indonesian Stock Trader Slang Language 微调IndoBERT理解印尼股票交易员俚语语言

2021 1st International Conference on Computer Science and Artificial Intelligence (ICCSAI) Pub Date : 2021-10-28 DOI: 10.1109/iccsai53272.2021.9609746

Anderies, R. Rahutomo, B. Pardamean

引用次数: 9

Spread of COVID-19 Deaths in Jakarta: Cluster and Regression Analysis COVID-19死亡在雅加达的传播:聚类和回归分析

2021 1st International Conference on Computer Science and Artificial Intelligence (ICCSAI) Pub Date : 2021-10-28 DOI: 10.1109/iccsai53272.2021.9609727

Intan Saskia, Ro'fah Nur Rachmawati, Derwin Suhartono

{"title":"Spread of COVID-19 Deaths in Jakarta: Cluster and Regression Analysis","authors":"Intan Saskia, Ro'fah Nur Rachmawati, Derwin Suhartono","doi":"10.1109/iccsai53272.2021.9609727","DOIUrl":"https://doi.org/10.1109/iccsai53272.2021.9609727","url":null,"abstract":"Jakarta as the center of the capital city of Indonesia has a very high mobility and population density. This has resulted in the spread of COVID-19 cases also have a very high increasing trend. Regional clustering and the detection of variables that affect COVID-19 deaths can be an early warning or the basis for government policies in handling the spread of disease outbreaks. This study aims to classify areas at the subdistrict level in Jakarta based on distribution of COVID-19 cases using the K-Means method. After the regional clusters were formed, Bayesian regression analysis was carried in each cluster and sub-district to identify variables that had an effect on COVID-19 deaths. The number of deaths is assumed to have Normal distribution, and statistical inference in Bayesian regression using the Integrated Nested Laplace Approximation (INLA) approach. This study produced several interesting results including: (1) there are 4 clusters that indicate areas prone to spread with a high case rate, fairly high risk, low risk to very low risk areas. (2) most of Jakarta's sub-districts, which is about 45%, are included in areas with a fairly high risk of spreading. (3) In general, the number of recovered cases is a significant variable on the majority decrease number of COVID-19 deaths in each cluster.","PeriodicalId":426993,"journal":{"name":"2021 1st International Conference on Computer Science and Artificial Intelligence (ICCSAI)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128776932","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