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2020 3rd International Conference on Computer and Informatics Engineering (IC2IE)最新文献

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Face Recognition Login Authentication for Digital Payment Solution at COVID-19 Pandemic 新冠肺炎疫情下数字支付解决方案的人脸识别登录认证
Pub Date : 2020-09-15 DOI: 10.1109/IC2IE50715.2020.9274654
Muhammad Irwan Padli Nasution, N. Nurbaiti, N. Nurlaila, Tri Inda Fadhila Rahma, Kamilah Kamilah
On March 11, 2020 the World Health Organization has announced the status of a global pandemic of corona virus disease 2019 or also called corona virus disease 2019 (COVID-19). The World Health Organization defines this disease as a pandemic because all citizens of the world are potentially exposed to COVID-19 infection. With the establishment of the global pandemic status, WHO also confirmed that COVID-19 was an international emergency. The trend of digitalization is becoming a new business trend to develop and survive in the midst of a crisis due to this pandemic. The online buying and selling market, digital payments and electronic health services, from online training classes to consulting with doctors via the internet, continue to increase. Some companies in the offline market also continue to operate by implementing health protocols. The form of digital payments continues increasing, this is because according to WHO the surface of objects can be a medium in the spread of the covid-19 virus. However, some digital payment media still require a card and enter a Personal Identification Number (PIN) in the Electronic Data Capture machine. For a solution so that the buyer does not need to bring a card and touch the Electronic Data Capture machine, face recognition authentication can be developed instead of PIN.
2020年3月11日,世界卫生组织宣布了2019年冠状病毒病全球大流行的状况,也称为2019年冠状病毒病(COVID-19)。世界卫生组织将这种疾病定义为大流行,因为世界上所有公民都有可能感染COVID-19。随着全球大流行地位的确立,世卫组织也确认新冠肺炎为国际紧急事件。数字化趋势正在成为在疫情危机中发展和生存的新商业趋势。在线买卖市场、数字支付和电子医疗服务(从在线培训课程到通过互联网向医生咨询)继续增加。线下市场的一些公司也继续通过执行卫生协议来运营。数字支付的形式不断增加,这是因为根据世卫组织的说法,物体的表面可能成为covid-19病毒传播的媒介。然而,一些数字支付媒体仍然需要一张卡,并在电子数据采集机上输入个人识别号码(PIN)。为了解决买方不需要带卡和触摸电子数据采集机的问题,可以开发人脸识别认证来代替PIN。
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引用次数: 18
IT Infrastructure Security Risk Assessment using the Center for Internet Security Critical Security Control Framework: A Case Study at Insurance Company 使用互联网安全中心关键安全控制框架的IT基础设施安全风险评估:一个保险公司的案例研究
Pub Date : 2020-09-15 DOI: 10.1109/IC2IE50715.2020.9274594
H. Winarno, Fatah Yasin, Muhamad Aries Prasetyo, Fathur Rohman, M. R. Shihab, B. Ranti
PT. XYZ is an insurance company that currently provides a variety of services using electronic systems in 80 service offices throughout Indonesia. At the end of 2019, the company experienced an IT security incident. The core application was hit by a malware attack that caused slow system performance and disruption of insurance operational services. These events have a negative impact on the company both operationally and to customers, so that it becomes a serious concern of management. Therefore, this research aims to see how companies develop infrastructure to ensure the reliability and improvement of IT security. The research methodology used is a qualitative approach by collecting data through documentation and interview studies. Based on the results of the assessment, there were 16 out of 20 controls that exceeded the threshold value. These results illustrate that the security of the IT infrastructure of PT. XYZ is very weak. Therefore, the company must carry out 13 recommendations for improvement that will be carried out in stages. This research is expected to be a lesson for other organizations especially insurance companies to improve the reliability and security of IT infrastructure.
PT. XYZ是一家保险公司,目前在印度尼西亚的80个服务办事处使用电子系统提供各种服务。2019年底,该公司经历了一次IT安全事件。核心应用程序受到恶意软件攻击,导致系统性能下降,保险业务服务中断。这些事件对公司的运营和客户都有负面影响,因此成为管理层严重关注的问题。因此,本研究旨在了解公司如何开发基础设施以确保IT安全的可靠性和改进。使用的研究方法是通过文献和访谈研究收集数据的定性方法。根据评估结果,20个控制组中有16个超过了阈值。这些结果表明,PT. XYZ的IT基础设施的安全性非常薄弱。因此,公司必须实施13项改进建议,并分阶段实施。这项研究有望为其他组织,特别是保险公司,提高IT基础设施的可靠性和安全性提供借鉴。
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引用次数: 2
An Attention-based Approach to Detect Emotion from Tweets 一种基于注意力的推文情感检测方法
Pub Date : 2020-09-15 DOI: 10.1109/IC2IE50715.2020.9274600
Sifat Ahmed, Abdus Sayef Reyadh, Fatima Tabsun Sithil, F. Shah, Asif Imtiaz Shaafi
In today’s world, social networks are the place where user share their views, emotions in their way. Social media, such as Twitter, Instagram, Facebook, etc. where millions of people express their views in their daily day-to-day life, which can be their sentiments and opinions or expressing emotions about a particular thing or their own. This gave researchers an outstanding opportunity to analyze the emotions of users’ activities on social networks. These massive digital data contain people’s day to day life sentiments, opinions, and showing emotions. Over the years there have been different research on emotion analysis of the social platform. As people tend to have different thoughts, analyzing the right emotion from social data is becoming a challenge. This clearly states that there is a need for an attempt to work towards these problems and it has opened up several opportunities for future research for hidden emotion identification, users’ emotions about a particular topic, etc. Detecting emotion from text is one of the toughest challenges in natural language processing. Developing a system that can detect emotion from social media is a crying need as people are sharing more of their thoughts here. In this research work, to learn the representation of the tweets, we propose an attention-based model. The proposed model has been divided into different components and subcomponents consisting of ID Convolution, Bidirectional LSTM, and Attention mechanism. We create a new dataset from SemEval Affect in Tweets dataset and then conduct experiments for the best outcomes. Our model achieves up to 79% accuracy in this task.
在当今世界,社交网络是用户以自己的方式分享观点和情感的地方。社交媒体,如Twitter, Instagram, Facebook等,数百万人在日常生活中表达自己的观点,可以是他们的情绪和观点,也可以是对特定事物或自己的情感表达。这给研究人员提供了一个绝佳的机会来分析用户在社交网络上活动的情绪。这些海量的数字数据包含了人们的日常生活情绪、观点和情感表现。多年来,对社交平台的情感分析有不同的研究。由于人们的想法往往不同,从社交数据中分析正确的情绪成为一项挑战。这清楚地表明,有必要尝试解决这些问题,并为未来的隐藏情感识别、用户对特定主题的情感等研究开辟了几个机会。从文本中检测情感是自然语言处理中最棘手的挑战之一。随着人们越来越多地在社交媒体上分享自己的想法,开发一种可以从社交媒体上检测情绪的系统是迫切需要的。在本研究中,为了学习推文的表征,我们提出了一个基于注意力的模型。该模型分为ID卷积、双向LSTM和注意机制组成的不同组件和子组件。我们从SemEval影响Tweets数据集中创建一个新的数据集,然后进行实验以获得最佳结果。我们的模型在这项任务中达到了79%的准确率。
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引用次数: 1
Investigation of Job Satisfaction and Worker Performance on Digital Business Company 数字化商务公司工作满意度与员工绩效的调查研究
Pub Date : 2020-09-15 DOI: 10.1109/IC2IE50715.2020.9274648
Atika Uyun, Dwinanda Kinanti Suci Sekarhati, Mohamad Yusup Dias Ibrahim, Sofian Lusa, D. I. Sensuse, Nadya Safitri, Damayanti Elisabeth
Nowadays, digital marketing strategy has made major improvement in business and industry within more than two decades. In the era of rapid information technology development, business competition is also getting stricter through the transformation of digital business. This is also happening in one of Indonesia’s digital business company known as PT XYZ Indonesia. For its sustainability, knowledge management has been adopted. But, there are some issues in its implementation because of high turnover rate and incorrect implementation process. In addition, there is a complaint rating of approximately 20% of 1049 projects. This paper aims to investigate KM implementation process on job satisfaction and worker performance for XYZ and give recommendation based on the measurement result to KM process implementation. The result of this paper is organizational culture has significant relationship with job satisfaction and knowledge sharing has significant relationship with worker performance. Based on the result, we recommend to create reward, KM policy, allocate budget, and organize special division of KM to optimal the KM implementation.
如今,在二十多年的时间里,数字营销策略在商业和工业领域取得了重大进展。在信息技术快速发展的时代,通过数字化业务的转型,商业竞争也越来越激烈。这也发生在印尼的一家名为PT XYZ Indonesia的数字商业公司。为了其可持续性,采用了知识管理。但由于员工流动率高,实施过程不正确,在实施过程中存在一些问题。此外,在1049个项目中,投诉率约为20%。本文旨在调查XYZ公司实施知识管理过程对工作满意度和员工绩效的影响,并根据测量结果对实施知识管理过程提出建议。研究结果表明,组织文化对工作满意度有显著影响,知识共享对员工绩效有显著影响。在此基础上,提出了建立奖励机制、制定知识管理政策、分配预算、组织知识管理专项分工等措施来优化知识管理的实施。
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引用次数: 0
Factors Affecting Student’s Perceived Readiness on Abrupt Distance Learning Adoption: Indonesian Higher-Education Perspectives 影响学生对突然接受远程教育的感知准备的因素:印尼高等教育的视角
Pub Date : 2020-09-15 DOI: 10.1109/IC2IE50715.2020.9274640
L. M. Hasani, Hafizh Rafizal Adnan, D. I. Sensuse, Kautsarina, Ryan Randy Suryono
Widespread lockdowns across the globe during Covid-19 outbreak forced the universities to abruptly adopt full-online distance learning. Such unprecedented abrupt adoption requires a degree of student readiness to ensure the success of distance learning delivery. However, prior research about student readiness of e-Learning adoption is still limited to discussing proactive adoption in normal conditions. To address this issue, this study investigated the factors that affect the student’s perceived readiness for abrupt distance learning adoption. By applying Structural Equation Modelling (SEM) using the Partial Least Square algorithm, this study found that self-competence, comfort with e-Learning, uncertainty avoidance, financial ability, and technological facilitating conditions are factors that significantly affect student’s perceived readiness. Based on this finding, faculties are recommended to be an early adopter of e-Learning, to provide an e-Learning platform with excellent usability and effective instructional design for the students, to provide clear instructions for both students and instructors, and to provide needed resources (e.g. internet connection) to the students. Moreover, future studies could be focused on lecturers’ or faculties’ readiness for abrupt distance learning adoption.
在2019冠状病毒病爆发期间,全球范围内的广泛封锁迫使大学突然采用全在线远程学习。这种前所未有的突然采用要求学生有一定程度的准备,以确保远程教育交付的成功。然而,以往关于学生采用e-Learning准备度的研究仍然局限于讨论正常情况下的主动采用。为了解决这一问题,本研究调查了影响学生对突然采用远程学习的感知准备程度的因素。本研究运用偏最小二乘法的结构方程模型(SEM),发现自我能力、网络学习舒适度、不确定性规避、经济能力和技术便利条件是影响学生感知准备程度的显著因素。基于此,我们建议各学院尽早采用电子学习,为学生提供一个可用性良好、教学设计有效的电子学习平台,为学生和教师提供明确的指导,并为学生提供所需的资源(如互联网连接)。此外,未来的研究可以集中在讲师或院系对突然采用远程学习的准备情况上。
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引用次数: 13
Performance Analysis of Reverse Proxy and Web Application Firewall with Telegram Bot as Attack Notification On Web Server 以Telegram Bot作为攻击通知的Web服务器上反向代理和Web应用防火墙的性能分析
Pub Date : 2020-09-15 DOI: 10.1109/IC2IE50715.2020.9274592
Defiana Arnaldy, Tio Setia Hati
Sophisticated technology in the world has been developing very rapidly, especially in terms of accessing all the information that is on the web. Website is one of technological sophistication that presents various kinds of information needed, from children to adults easily accessing websites on the internet. Unwittingly the number of accesses made by users around the world causes a web server or a place that provides a website will be weak and can occur down. When a web server becomes weak, hackers will use it to attack the web server, retrieve data, important information, and even more fatal is when user data is stolen and misused by hackers. The web developers only focus on a website appearance but do not focus on access and security of the website. Therefore, we need an optimal web server that can accommodate the many accesses caused by users and the security of the web server to safeguard data and information stored. This research applies a package namely Reverse Proxy which is used to optimize a web server and Web Application Firewall which is used to maintain the security of a web server.
世界上的尖端技术发展非常迅速,特别是在访问网络上的所有信息方面。网站是一种复杂的技术,它提供了各种各样的信息,从儿童到成人都可以轻松地访问互联网上的网站。不知不觉中,世界各地用户的访问数量会导致网络服务器或提供网站的地方变弱并可能发生故障。当web服务器变得脆弱时,黑客就会利用它来攻击web服务器,检索数据、重要信息,更致命的是用户数据被黑客窃取和滥用。web开发人员只关注网站的外观,而不关注网站的访问和安全性。因此,我们需要一个最优的web服务器,既能容纳用户的大量访问,又能保证web服务器的安全性,以保护存储的数据和信息。本研究应用了一个软件包,即反向代理,用于优化web服务器和web应用防火墙,用于维护web服务器的安全。
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引用次数: 3
Disaster Impact Analysis Uses Land Cover Classification, Case study: Petobo Liquefaction 灾害影响分析使用土地覆盖分类,案例研究:石油液化
Pub Date : 2020-09-15 DOI: 10.1109/IC2IE50715.2020.9274573
R. Hidayat, A. M. Arymurthy, Dimas Sony Dewantara
Analysis of changes in the conditions of an area can be done through satellite image analysis. This study utilizes the classification of satellite imagery to determine the impact of disasters and liquefaction disaster recovery efforts in the Petobo region, Palu, Central Sulawesi. The deep learning approach, namely Convolutional Neural Network (CNN) and CNN combined with ResNet as the Transfer Learning model, were selected as classification methods that would be compared in determining the approach with the best performance. The classification of satellite imagery is mapped into two main classes, namely natural land cover and artificial land cover. This research subsequently succeeded in mapping land cover changes that occurred as a result of liquefaction disasters and recovery efforts that have been carried out with promising performance
分析一个地区的条件变化可以通过卫星图像分析来完成。本研究利用卫星图像分类来确定灾害的影响和液化灾害恢复工作在佩托博地区,帕卢,苏拉威西岛中部。选择深度学习方法,即卷积神经网络(CNN)和CNN结合ResNet作为迁移学习模型,作为分类方法进行比较,以确定性能最佳的方法。卫星图像的分类主要分为两类,即自然土地覆盖和人工土地覆盖。这项研究后来成功地绘制了由于液化灾害和恢复工作而发生的土地覆盖变化的地图,这些工作已经取得了良好的成绩
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引用次数: 1
Template Pattern for Simple Question Transformation 简单问题转换模板模式
Pub Date : 2020-09-15 DOI: 10.1109/IC2IE50715.2020.9274666
Rakhmayudhi, W. Suwarningsih
The classification of question types in the Indonesian medical domain is the important component of the medical question answering system. The strategy proposed in this paper is to build the template pattern and rule-based parser for extracting some important words using the generated feature to automatically query the classification of question. Classification aims to prove that the system is capable of classifying queries only by using the available language resources. The proposed method has been evaluated using datasets collected from various Indonesian health consultation websites. Test results from the proposed method indicated that the classification process is very effective with an accuracy of 84.33%.
印尼语医学领域问题类型分类是医学问答系统的重要组成部分。本文提出的策略是构建模板模式和基于规则的解析器,利用生成的特征提取重要词,实现问题分类的自动查询。分类旨在证明系统能够仅通过使用可用的语言资源对查询进行分类。使用从印度尼西亚各健康咨询网站收集的数据集对拟议的方法进行了评估。实验结果表明,该方法具有良好的分类效果,准确率达到84.33%。
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引用次数: 1
Product Cognition, Platform Emotion, Behavior Intention, and Actual Behavior Stage in Cross Border E-commerce (Case Study: Shopee as The Biggest Cross Border E-Commerce in Indonesia) 跨境电商中的产品认知、平台情感、行为意向与实际行为阶段(以印尼最大的跨境电商Shopee为例)
Pub Date : 2020-09-15 DOI: 10.1109/IC2IE50715.2020.9274563
Diyang Risma Gabriella, A. Agus
Cross-border e-commerce (CBEC) is growing rapidly, it provides a new shopping experience for customers where they can involve in a global transaction. Each year, CBEC receives a significant total number of transactions, recorded in 2018, CBEC transactions have increased by 27.5% globally. Shopee as the biggest of Indonesia CBEC has dominated the market with a monthly average of 200.2 million visits. Competition between CBEC in Indonesia continues, they are competing to provide the best quality of products and platform experience to gain trust and purchase from the customers. Building a trust and customer intention to purchase in CBEC platform is a challenge, while customers’ awareness of products is the first step in creating optimal product cognition. Perceived trust can be improved by the involvement of customers in the CBEC platform, the provision of convincing product information, as well as the awareness of good product quality, thus it will influence purchase intention of customers. Therefore, this study was conducted to analyze the relationship between product cognition stage, platform emotion stage, behavior intention stage, and actual behavior stage at the biggest CBEC in Indonesia. The research is based on the Hierarchy of Effect (HOE) model which consists of customers stages of journey. The survey began in January to March, 2020 and 1.281 respondents were processed through a structured questionnaire, and data were analyzed using the Structural Equation Method (SEM).
跨境电子商务(CBEC)正在迅速发展,它为客户提供了一种新的购物体验,他们可以参与全球交易。每年,CBEC都会收到大量的交易,2018年,CBEC交易在全球范围内增长了27.5%。Shopee是印尼最大的CBEC,月平均访问量为2.002亿。CBEC在印尼的竞争仍在继续,他们正在竞争提供最优质的产品和平台体验,以获得客户的信任和购买。在CBEC平台上建立信任和客户购买意愿是一个挑战,而客户对产品的认知是创造最佳产品认知的第一步。感知信任可以通过客户参与CBEC平台,提供令人信服的产品信息,以及对良好产品质量的认识来提高,从而影响客户的购买意愿。因此,本研究以印尼最大的CBEC为研究对象,分析产品认知阶段、平台情感阶段、行为意向阶段和实际行为阶段之间的关系。本研究基于效应层次模型(Hierarchy of Effect, HOE),该模型包含了顾客旅程的各个阶段。调查于2020年1月至3月展开,通过结构化问卷对1281名受访者进行了处理,并使用结构方程法(SEM)对数据进行了分析。
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引用次数: 2
Forecasting Model of Amount of Water Production Using Double Moving Average Method 双移动平均法预测出水量模型
Pub Date : 2020-09-15 DOI: 10.1109/IC2IE50715.2020.9274603
D. M. Khairina, S. Maharani, P. P. Widagdo, Ramlawati, H. R. Hatta
The population continues to increase causing high water consumption. This causes the need for clean water to continue to increase while the supply of clean water is uncertain every year. Uncontrolled use of water is a challenge for the organization in meeting clean water needs. A forecasting system is needed that is able to predict the use of water for several periods in order to minimize the problem of uneven water distribution. Water demand predictions can also be utilized by companies to allocate water distribution to customers so that they do not experience shortages or waste. Forecasting the amount of water production is carried out using actual data within the period of 2 (two) previous years ie from 2017 to 2018 using the Double Moving Average (DMA) method. Forecasting trials are carried out by comparing the actual data of 2018 with the estimated data of 2018 by using the movement value of 3 periods and 4 periods. The forecasting accuracy method is used the Mean Absolute Percentage Error (MAPE) method to calculate the percentage of errors at each method movement value DMA every month. Based on the tests conducted, the best forecast of the amount of water production is shown in the movement value with 3 periods which results in a smaller accuracy or error rate of MAPE so that it can be said the accuracy value is better and more recommended than the movement value with 4 periods in the DMA method so determining the value of movement can affect the value of forecasting accuracy.
人口持续增长导致高用水量。这导致对清洁水的需求继续增加,而清洁水的供应每年都不确定。不受控制的用水是该组织在满足清洁用水需求方面面临的挑战。需要一种能够预测几个时期的用水情况的预报系统,以便尽量减少水分配不均匀的问题。水需求预测也可以被公司用来分配给客户的水,这样他们就不会遇到短缺或浪费。使用双移动平均线(DMA)方法,使用前2(2)年(即2017年至2018年)的实际数据进行产水量预测。采用3期和4期的移动值,将2018年的实际数据与2018年的估计数据进行对比,进行预测试验。预测精度方法采用平均绝对误差百分比法(MAPE)计算每个月各方法移动值DMA的误差百分比。通过试验发现,3周期的运动值对产水量的预测效果最好,MAPE的精度或错误率较小,可以说该精度值比DMA法中4周期的运动值更好,更值得推荐,因此运动值的确定会影响预测精度值。
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引用次数: 3
期刊
2020 3rd International Conference on Computer and Informatics Engineering (IC2IE)
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