Usability analysis of smart Covid-19 diagnose application for Android devices

Wahyu Alfandi, I. S. Wijaya, Fitri Bimantoro, Triana Diyah Cahyawati, Ramaditya Dwiyansaputra
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Abstract

An unreported disease cluster occurred in Wuhan, Hubei Province, China in December 2019. The disease was named Coronavirus Disease 2019 (Covid-19) by the World Health Organization (WHO). The transmission of Covid-19 from human to human occurs through coughing/sneezing (drops). Indonesia has Covid-19 cases that are increasing every day. By July 14, 2021, it is counting up to 2,670,046 cases of Covid-19â in Indonesia. This causes Indonesia to become the country with the highest number of Covid-19 cases in Southeast Asia. In dealing with this case, the government has provided various methods to detect the Covid-19 virus in humans, but it has not been able to provide satisfactory results. This is caused by the delay in the detection of the diagnosis given. The delay was due to the limited testing capacity provided. Thus, to help improve patient test results, a CT scan tool is used. The Covid-19 Diagnose System University of Mataram is a system designed to facilitate the process of identifying Covid-19 patients through chest X-rays by applying the CNN model for classification. To find out the system is suitable for the use by end-users, it is necessary to test the usability of the application using the System Usability Scale (SUS) method. The System Usability Scale is used because this method focuses on the end-user. Therefore, this research was made to find out whether the application that has been made (the Covid-19 Diagnose System University of Mataram) can be accepted by users or not. To test the feasibility of this application, it needs to test its usability with the SUS instrument. Testing with SUS has been done using 10 statements of SUS. The test shows the score of SUS is 71.38. It means that the application is acceptable to be used by end users and classified into grade C with a good rating © 2023 Author(s).
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Android设备新型冠状病毒智能诊断应用的可用性分析
2019年12月,中国湖北省武汉市发生了一起未报告的聚集性病例。世界卫生组织将这种疾病命名为2019冠状病毒病(Covid-19)。Covid-19在人与人之间的传播通过咳嗽/打喷嚏(滴)发生。印度尼西亚的Covid-19病例每天都在增加。到2021年7月14日,印度尼西亚的covid - 19病例已达2,670,046例。这使得印度尼西亚成为东南亚新冠肺炎病例最多的国家。政府在处理这一事件的过程中,虽然提供了多种人体检测新冠病毒的方法,但并没有取得令人满意的结果。这是由于诊断的检测延迟造成的。延迟的原因是所提供的测试能力有限。因此,为了帮助改善患者的测试结果,使用了CT扫描工具。马塔兰姆大学的新冠肺炎诊断系统是为了利用CNN模型进行分类,方便通过胸部x光片识别新冠肺炎患者而设计的系统。为了找出系统是否适合最终用户使用,有必要使用系统可用性量表(SUS)方法测试应用程序的可用性。之所以使用系统可用性量表,是因为该方法关注的是最终用户。因此,本次研究的目的是了解已经提出的申请(新冠肺炎诊断系统马塔兰大学)是否能被用户接受。要测试此应用程序的可行性,需要使用SUS仪器测试其可用性。使用SUS的10条语句完成了对SUS的测试。测试显示SUS的分数是71.38。这意味着该应用程序可以被最终用户使用,并被分类为C级,评级良好©2023 Author(s)。
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