2021 1st International Conference on Computer Science and Artificial Intelligence (ICCSAI)最新文献_第9页

A Systematic Literature Review: Database Optimization Techniques 系统文献综述:数据库优化技术

2021 1st International Conference on Computer Science and Artificial Intelligence (ICCSAI) Pub Date : 2021-10-28 DOI: 10.1109/ICCSAI53272.2021.9609766

Rizki Ashari, M. Akbar, Winata Dharmawan Thamrin, Novita Hanafiah

{"title":"A Systematic Literature Review: Database Optimization Techniques","authors":"Rizki Ashari, M. Akbar, Winata Dharmawan Thamrin, Novita Hanafiah","doi":"10.1109/ICCSAI53272.2021.9609766","DOIUrl":"https://doi.org/10.1109/ICCSAI53272.2021.9609766","url":null,"abstract":"Big data optimization is the main thing in getting accurate and fast data. The condition of the data at this time is very much, therefore optimization must be done. As technology develops, more and more data is generated, some data optimization techniques still take a long time to get optimal results. This research paper aims to find out several ways of optimizing the database with several existing techniques. The design used is a literature review. The criteria for the papers used are those published in 2005–2020. In the paper that we have researched, there are several ways to optimize a database, the methods used, and the challenges that will exist during database optimization. Based on the collected papers, it was found that there are indeed many ways to optimize the database. Then there are many methods in database optimization that use the Map Reduce Algorithm, and it is proven that the algorithm can reduce the amount of work time when transferring data, and there are several challenges in database optimization. This research paper shows how to optimize the database from several sources. Then there is an explanation of the methods or algorithms used in database optimization.","PeriodicalId":426993,"journal":{"name":"2021 1st International Conference on Computer Science and Artificial Intelligence (ICCSAI)","volume":"65 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":"122404761","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

Modelling personality prediction from user's posting on social media 根据用户在社交媒体上的帖子进行个性预测建模

2021 1st International Conference on Computer Science and Artificial Intelligence (ICCSAI) Pub Date : 2021-10-28 DOI: 10.1109/iccsai53272.2021.9609711

Derwin Suhartono

引用次数: 0

Comparison of Gaussian Hidden Markov Model and Convolutional Neural Network in Sign Language Recognition System 高斯隐马尔可夫模型与卷积神经网络在手语识别中的比较

2021 1st International Conference on Computer Science and Artificial Intelligence (ICCSAI) Pub Date : 2021-10-28 DOI: 10.1109/ICCSAI53272.2021.9609718

Herman Gunawan, Suharjito, Devriady Pratama

{"title":"Comparison of Gaussian Hidden Markov Model and Convolutional Neural Network in Sign Language Recognition System","authors":"Herman Gunawan, Suharjito, Devriady Pratama","doi":"10.1109/ICCSAI53272.2021.9609718","DOIUrl":"https://doi.org/10.1109/ICCSAI53272.2021.9609718","url":null,"abstract":"Sign language Recognition is the study to help bridging communication of deaf-mute people. Sign Language Recognition uses techniques to convert gestures of sign language into words or alphabet. In Indonesia, there are two types of sign languages which are used, Bahasa Isyarat Indonesia (BISINDO) and Sistem Isyarat Bahasa Indonesia (SIBI). The purpose of this research is comparing sign language recognition methods between Gaussian Hidden Markov Model and Convolutional Neural Network using indonesian sign language SIBI as a dataset. The dataset comes from 200 videos from 2 signers. Each signer performs 10 signs with 10 repetitions. To improve the recognition accuracy, modified histogram equalization is used as an image enhancement. Skin detection was used to track the movement of the gesture as input features in the Gaussian Hidden Markov Model and fine tuning was used in Convolutional Neural Network using transfer learning, freeze layer, and dropout. The results of the research are the Gaussian Hidden Markov Model provides accuracy value of 84.6% and Convolutional Neural Network provides accuracy value of 82%.","PeriodicalId":426993,"journal":{"name":"2021 1st International Conference on Computer Science and Artificial Intelligence (ICCSAI)","volume":"51 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":"130288851","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

Performance Analysis Between Cloud Storage and NAS to Improve Company's Performance: A Literature Review 云存储与NAS提升企业绩效的绩效分析:文献综述

2021 1st International Conference on Computer Science and Artificial Intelligence (ICCSAI) Pub Date : 2021-10-28 DOI: 10.1109/iccsai53272.2021.9609792

Dimas Sekti Adji, Gabriel Eduardus, Michael, Minawati, W. Budiharto

{"title":"Performance Analysis Between Cloud Storage and NAS to Improve Company's Performance: A Literature Review","authors":"Dimas Sekti Adji, Gabriel Eduardus, Michael, Minawati, W. Budiharto","doi":"10.1109/iccsai53272.2021.9609792","DOIUrl":"https://doi.org/10.1109/iccsai53272.2021.9609792","url":null,"abstract":"Storage systems are becoming increasingly important in framework for storing and accessing information with less retrieval time and a low budget. It is common for every small organization or large company to use storage for storing their data. The data that they store later will boost their value as an organization or company. The problem is that many companies do not know the best option for their storage system. Most companies pick one storage type without knowing the best type for their companies. This paper aims to know and compare what kinds of storage a company uses nowadays and what kind of storage suits its needs. In this paper, we proposed to look for and compare two storages, namely Cloud Storage and Network Attached Storage (NAS) because these two systems are the most commonly used. Based on our research, both storages are good depending on their needs. Even so, for the small companies, Cloud Storage is the best choice as it cost lower, has easier configuration and data back-up, takes up a little space, scalability, and many more.","PeriodicalId":426993,"journal":{"name":"2021 1st International Conference on Computer Science and Artificial Intelligence (ICCSAI)","volume":"18 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":"125387902","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

Sentiment Analysis using SVM and Naïve Bayes Classifiers on Restaurant Review Dataset 基于支持向量机和Naïve贝叶斯分类器的餐厅评论数据集情感分析

2021 1st International Conference on Computer Science and Artificial Intelligence (ICCSAI) Pub Date : 2021-10-28 DOI: 10.1109/iccsai53272.2021.9609776

Jason Cornelius Sugitomo, Nathaniel Kevin, Nayra Jannatri, Derwin Suhartono

引用次数: 0