scholarly journals Test-Driven Development pada Pengembangan Aplikasi Android untuk Memantau COVID-19

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Federick Jonathan ◽  
Magdalena Ariance Ineke Pakereng
Keyword(s):  
Mobile Application ◽  
Systems Science ◽  
Test Case ◽  
Android Application ◽  
Science And Engineering ◽  
Test Driven Development ◽  
Writing Test ◽  
Johns Hopkins University ◽  
Reliable Software

Dalam pengembangan perangkat lunak, terdapat banyak teknik dan pendekatan yang digunakan untuk menghasilkan perangkat lunak yang handal. Kualitas perangkat lunak sangat bergantung pada pengujian perangkat lunak. Namun tidak semua pengembang peduli dengan tahapan pengujian pada sebuah perangkat lunak. Penelitian ini bertujuan untuk mengetahui pengaruh dari menerapkan proses pengujian dalam mengembangkan perangkat lunak dengan menggunakan metode TDD. Pada Metode TDD, pengembangan perangkat lunak dimulai dengan menulis test case terlebih dahulu lalu kemudian menulis kode. Pada artikel ini, dikembangkan aplikasi mobile dengan menerapkan metode TDD. Perangkat lunak yang dikembangkan adalah berupa sistem informasi mengenai data laporan kasus COVID-19. Data diambil dari Johns Hopkins University The Center of Systems Science and Engineering (JHU CSSE). Hasil penerapan metode TDD menunjukkan bahwa fungsi dan fitur dari perangkat lunak yang dibangun dapat bekerja dan terintegrasi dengan baik antar satu sama lain. Kode yang dihasilkan dari penerapan TDD juga menjadi rapih karena dilakukannya proses refactoring. In Software Engineering, there are many techniques and approaches that can be used to build a reliable software. The quality of a software relies mostly on the software testing process. However, not many developers are bothered with the testing step of a software. The purpose of this article is to learn the results from implementing a testing process on software developmenty. In TDD, the development is started by writing test case first and then writing code. This article developed a mobile application by applying TDD in the process. The android application that had been developed is an information system about report cases on COVID-19. The cases are coming from Johns Hopkins University The Center of Systems Science and Engineering (JHU CSSE). The result of using TDD in development proves that all functions and features of the developed application are working and integrated well.

scholarly journals Country transition index based on hierarchical clustering to predict next COVID-19 waves

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ricardo A. Rios ◽  
Tatiane Nogueira ◽  
Danilo B. Coimbra ◽  
Tiago J. S. Lopes ◽  
Ajith Abraham ◽  
...  
Keyword(s):  
Hierarchical Clustering ◽  
Temporal Analysis ◽  
Systems Science ◽  
Collateral Damage ◽  
Science And Engineering ◽  
University Center ◽  
Main Challenge ◽  
Johns Hopkins University ◽  
The World ◽  
Transition Index

AbstractCOVID-19 has widely spread around the world, impacting the health systems of several countries in addition to the collateral damage that societies will face in the next years. Although the comparison between countries is essential for controlling this disease, the main challenge is the fact of countries are not simultaneously affected by the virus. Therefore, from the COVID-19 dataset by the Johns Hopkins University Center for Systems Science and Engineering, we present a temporal analysis on the number of new cases and deaths among countries using artificial intelligence. Our approach incrementally models the cases using a hierarchical clustering that emphasizes country transitions between infection groups over time. Then, one can compare the current situation of a country against others that have already faced previous waves. By using our approach, we designed a transition index to estimate the most probable countries’ movements between infectious groups to predict next wave trends. We draw two important conclusions: (1) we show the historical infection path taken by specific countries and emphasize changing points that occur when countries move between clusters with small, medium, or large number of cases; (2) we estimate new waves for specific countries using the transition index.

scholarly journals Interim Analysis of Pandemic Coronavirus Disease 2019 (COVID-19) and the SARS-CoV-2 virus in Latin America and the Caribbean: Morbidity, Mortality and Molecular Testing Trends in the Region

2020 ◽  
Author(s):  
Katherine Simbaña-Rivera ◽  
Lenin Gómez-Barreno ◽  
Jhon Guerrero ◽  
Fernanda Simbaña-Guaycha ◽  
Raúl Fernández ◽  
...  
Keyword(s):  
Latin American ◽  
Case Fatality ◽  
Incidence Rates ◽  
Systems Science ◽  
Molecular Testing ◽  
Science And Engineering ◽  
Johns Hopkins University ◽  
Significant Burden ◽  
Similar Disease ◽  
Novel Coronavirus

AbstractBackgroundThe relentless advance of the SARS-CoV-2 virus pandemic has resulted in a significant burden on countries, regardless of their socio-economic conditions. The virus has infected more than 2.5 million people worldwide, causing to date more than 150,000 deaths in over 210 countries.ObjectiveThe aim of this study was to describe the trends in cases, tests and deaths related to novel coronavirus disease (COVID-19) in Latin American and Caribbean (LAC) countries.MethodologyData were retrieved from the WHO-Coronavirus Disease (COVID-2019) situation reports and the Center for Systems Science and Engineering (CSSE) databases from Johns Hopkins University. Descriptive statistics including death rates, cumulative mortality and incidence rates, as well as testing rates per population at risk were performed. A comparison analysis among countries with ≥50 confirmed cases was performed from February 26th, 2020 to April 8th, 2020.ResultsBrazil had the greatest number of cases and deaths in the region. Panama experienced a rapid increase in the number of confirmed cases with Trinidad and Tobago, Bolivia and Honduras having the highest case fatality rates. Panama and Chile conducted more tests per million inhabitants and more tests per day per million inhabitants, followed by Uruguay and El Salvador. Dominican Republic, Bolivia, Ecuador and Brazil had the highest positive test rates.ConclusionsThe COVID-19 disease pandemic caused by the SARS-CoV-2 virus has progressed rapidly in LAC countries. Some countries have been affected more severely than others, with some adopting similar disease control methods to help slow down the spread of the virus. With limited testing and other resources, social distancing is needed to help alleviate the strain on already stretched health systems.

2019 Novel Coronavirus COVID-19 (2019-nCoV) Data Repository

2020 ◽  
pp. 47-51
Author(s):  
Meg Miller
Keyword(s):  
Academic Library ◽  
Systems Science ◽  
Data Repository ◽  
Science And Engineering ◽  
University Center ◽  
Johns Hopkins University ◽  
Novel Coronavirus

This review provides an overview of 2019 Novel Coronavirus COVID-19 (2019-nCoV) Data Repository compiled by the Johns Hopkins University Center for Systems Science and Engineering. It provides a background of how the repository was compiled, the data included and how the repo is being made use of in a Canadian academic library context.

scholarly journals SIR Model Parameters Estimation with COVID-19 Data

2021 ◽  
pp. 97-117
Author(s):  
Nilson C. Roberty ◽  
Lucas S. F. de Araujo
Keyword(s):  
Removal Rate ◽  
Sir Model ◽  
Parameters Estimation ◽  
Systems Science ◽  
Model Parameters ◽  
Science And Engineering ◽  
University Center ◽  
Johns Hopkins University ◽  
System Solution ◽  
Rate Of Decay

Based on the SIR model that divides the population into susceptible, infected and removed individuals, data about the evolution of the pandemic compiled by the Johns Hopkins University Center for Systems Science and Engineering (JHUCSSE) are integrated into the numerical system solution. The system parameters Rate of Contact β, Basic Reproduction Number R0 and Removal Rate γ, also named Rate of Decay, are determined according to a ridge regression approach and a mobile statistical scheme with different averages. Data is automatically downloaded from https://raw.githubusercontent.com/CSSEGISandData/COVID-19. The main Python libraries used are Numpy, Pandas, Skit-Learn, Requests and Urllib.

scholarly journals Measuring Time-Varying Effective Reproduction (Rt) Numbers for COVID-19 and Their Relationship with Movement Control Order (MCO) in Malaysia

2021 ◽  
Author(s):  
Musa Kamarul Imran ◽  
Wan Nor Ariffin ◽  
Mohd Mohd Hafiz ◽  
Subhi Jamiluddin ◽  
Noor Atinah Ahmad ◽  
...  
Keyword(s):  
Reproduction Number ◽  
Movement Control ◽  
Systems Science ◽  
Time Varying ◽  
Science And Engineering ◽  
University Center ◽  
Incidence Data ◽  
Johns Hopkins University ◽  
Control Order ◽  
Local Transmission

To quantify the time-varying reproduction number (Rt) for Malaysia using the COVID-19 incidence data., we used data the from the Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE) Coronavirus repository. Day 1 was taken from the first assumed local transmission of COVID-19. Data was split into four intervals: a) Interval 1: from Day 1 to Day 10 MCO 1, b) Interval 2: from Day 1 to Day 10 MCO 2, c) Interval 3: from Day 1 to Day 10 MCO 3 and d) Interval 4: from Day 1 to Day 10 MCO 4. We estimated the Rt using the EpiEstim package. The means for Rt at Day 1, Day 5 and Day 10 for all MCOs ranged between 0.665 to 1.147. The average Rt gradually decreased in MCO 1 and MCO 2. However, Rt increased in MCO 3 before stabilized around 0.8 in MCO 4. MCO 1 and MCO 2 which were stricter coincide with the gradual reduction of Rt. However, the more relaxed MCO 3 and MCO 4 correspond to a slight increase in the Rt before it stabilized.

scholarly journals Epidemiology of COVID-19 in Africa - daily cumulative index and mortality rate

2020 ◽  
Vol 16 (2) ◽  
Author(s):  
Kenneth Bitrus David ◽  
Naomi Thomas ◽  
Joan Kuyet Solomon
Keyword(s):  
Mortality Rate ◽  
Human Life ◽  
Epidemiological Data ◽  
Systems Science ◽  
Science And Engineering ◽  
Cumulative Index ◽  
Johns Hopkins University ◽  
The World

COVID-19 outbreak which originated from Wuhan, a city in China has spread to over 180 countries in the world, disrupting several sectors of the human life, and causing deaths. This unprecedented event has affected 55 countries in Africa in different ways. This study aims to outline the current epidemiological data of COVID-19 in Africa. The number of confirmed cases and deaths in Africa was obtained from COVID-19 Dashboard by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University. Mortality rate and daily cumulative index were calculated for each country. The mortality rate in Africa is low compared to other Continents regardless of the high Daily Cumulative Index recorded.

Students’ Understanding of Generic Structure of the Text and the Quality of Writing: A Correlational Study

2019 ◽  
Vol 2 (1) ◽  
pp. 37-45
Author(s):  
Atikah Wati
Keyword(s):  
High School ◽  
Research Design ◽  
Senior High School ◽  
Second Grade ◽  
Statistical Calculation ◽  
Writing Quality ◽  
Generic Structure ◽  
Writing Test ◽  
Correlational Research

Indriyani et al, (2013) stated that many students had dificulty in understanding the generic structure of analytical exposition text. Therefore, the present study tried to investigate the correlation between students understanding in writing generic structure of analytical exposition and the quality of students’ writing in second grade of senior hight school. Grounded in explanatory correlational research design by Creswell (2011), this study conducted over two weeks in one of senior high school in Indramayu. Close-ended questionnaire and writing test were instruments to collect the data and it was analyzed  by using SPSS 22. The statistical calculation from students understanding in writing generic stucture of the text and writing test indicated that the value of tcount was 3.23 and the value of ttable was 0.361. It can be concluded that the hypothesis was accepted because tcount 3.23 > ttable 0.361. The finding reveal that there was middle correlation or middle prediction in students understanding of generic structure of analytical exposition and students writing quality with the score 0,52.

Psychometric evaluation of the Mobile Application Rating Scale (MARS) (Preprint)

2020 ◽  
Author(s):  
Yannik Terhorst ◽  
Paula Philippi ◽  
Lasse Sander ◽  
Dana Schultchen ◽  
Sarah Paganini ◽  
...  
Keyword(s):  
Health Care ◽  
Construct Validity ◽  
Mobile Application ◽  
Concurrent Validity ◽  
Rating Scale ◽  
Psychometric Evaluation ◽  
Confirmatory Factor ◽  
Health Domains ◽  
Psychometric Quality

BACKGROUND Mobile health apps (MHA) have the potential to improve health care. The commercial MHA market is rapidly growing, but the content and quality of available MHA are unknown. Consequently, instruments of high psychometric quality for the assessment of the quality and content of MHA are highly needed. The Mobile Application Rating Scale (MARS) is one of the most widely used tools to evaluate the quality of MHA in various health domains. Only few validation studies investigating its psychometric quality exist with selected samples of MHAs. No study has evaluated the construct validity of the MARS and concurrent validity to other instruments. OBJECTIVE This study evaluates the construct validity, concurrent validity, reliability, and objectivity, of the MARS. METHODS MARS scoring data was pooled from 15 international app quality reviews to evaluate the psychometric properties of the MARS. The MARS measures app quality across four dimensions: engagement, functionality, aesthetics and information quality. App quality is determined for each dimension and overall. Construct validity was evaluated by assessing related competing confirmatory models that were explored by confirmatory factor analysis (CFA). A combination of non-centrality (RMSEA), incremental (CFI, TLI) and residual (SRMR) fit indices was used to evaluate the goodness of fit. As a measure of concurrent validity, the correlations between the MARS and 1) another quality assessment tool called ENLIGHT, and 2) user star-rating extracted from app stores were investigated. Reliability was determined using Omega. Objectivity was assessed in terms of intra-class correlation. RESULTS In total, MARS ratings from 1,299 MHA covering 15 different health domains were pooled for the analysis. Confirmatory factor analysis confirmed a bifactor model with a general quality factor and an additional factor for each subdimension (RMSEA=0.074, TLI=0.922, CFI=0.940, SRMR=0.059). Reliability was good to excellent (Omega 0.79 to 0.93). Objectivity was high (ICC=0.82). The overall MARS rating was positively associated with ENLIGHT (r=0.91, P<0.01) and user-ratings (r=0.14, P<0.01). CONCLUSIONS he psychometric evaluation of the MARS demonstrated its suitability for the quality assessment of MHAs. As such, the MARS could be used to make the quality of MHA transparent to health care stakeholders and patients. Future studies could extend the present findings by investigating the re-test reliability and predictive validity of the MARS.

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