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Survey management system using data visualization method ud / Mohammad Fadhlan Nuaim Bujang

机译:使用数据可视化方法的调查管理系统 ud / Mohammad Fadhlan Nuaim Single

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摘要

Surveys are a reliable method to gather numerous data quickly and effectively but the manual evaluation of data collected from surveys take a long time and a lot of effort. Processing huge amounts of data is tiring and huge amounts of raw data acquired from surveys are hard to interpret. The prototype developed in this project aims to overcome the problems stated by automating the survey evaluation process thus reducing time and effort wasted and visualizes the data to facilitate the interpretation of huge data at first glance. The Likert scale was chosen as the data collection method as it is deemed convenient and reliable in gathering quantitative data, the Diversity Map was chosen as the visualization method due to the fact that it is efficient in displaying quantitative data and is very effective in showing diversity in data thus aiding first glance interpretation. The framework used for development is the agile method due to its versatility, it consists of four phases which are requirement analysis, design, development and testing. The prototype consists of two modules which are the researcher and respondent module. The researcher module requires registration before becoming available for use and has the functionality to login, create surveys and view the visualized survey results while the respondent module answers the survey given by the researchers. Testing was conducted on the prototype both in functionality and in its ability to handle actual data. The functionality testing shows that the prototype meets the expected outcomes and the actual data testing also gives positive results and proves that the Diversity Map visualization can aid in first glance interpretation of big data. This shows that the prototype can be used by researchers to reduce the troubles of manual questionnaire surveys and improves the interpretation of data by using data visualization.
机译:调查是一种快速有效地收集大量数据的可靠方法,但是对从调查中收集的数据进行人工评估需要花费长时间和大量的精力。处理大量数据非常累人,并且难以解释从调查中获取的大量原始数据。此项目中开发的原型旨在克服通过使调查评估过程自动化而带来的问题,从而减少浪费的时间和精力,并使数据可视化,以方便乍看之下解释大型数据。选择李克特量表作为数据收集方法,是因为它可以方便,可靠地收集定量数据,而选择多样性图作为可视化方法是因为它可以有效显示定量数据,并且可以非常有效地显示多样性数据,从而有助于乍一看。由于其通用性,用于开发的框架是敏捷方法,它由需求分析,设计,开发和测试四个阶段组成。原型包含两个模块,分别是研究人员模块和受访者模块。研究者模块需要注册才能可用,并具有登录,创建调查和查看可视化调查结果的功能,而受访者模块则回答研究者给出的调查。对原型进行了功能性和处理实际数据能力的测试。功能测试表明原型可以达到预期的结果,而实际数据测试也给出了积极的结果,并证明了多样性图可视化可以帮助乍一看大数据的解释。这表明研究人员可以使用该原型来减少手动问卷调查的麻烦,并通过使用数据可视化来改善数据的解释。

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