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Implementation of Data Science in an Era and After Pandemic

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Implementation of Data Science in an Era and After Pandemic PROPOSAL OF COMMUNITY SERVICES IMPLEMENTATION OF DATA SCIENCE IN AN ERA AND AFTER PANDEMIC TEAM MEMBERS : Leader : Yaya Sudarya Triana, M.Kom., Ph.D. NIDN : 00160164 Member : 1. Dr. Puji Rahayu NIDN : 0319087701 2. Yunita Sartika Sari, S.Kom, M.Kom. NIDN : 0309068903 FIELD OF INFORMATION SYSTEM UNIVERSITAS MERCU BUANA 2020 i VALIDITY SHEET 1. a. Title of Proposal of Community : Implementation of Data Science in an Era Services and After Pandemic b. Previous Research Title : Fuzzy Decision Support Model for Determining Top Marketer 2. Team Leader a. Name (with salutation) : Yaya Sudarya Triana, M.Kom., Ph.D. b. NIDN : 0016016404 c. Functional Position : Lektor d. Faculty/Study Program : Computer Science/Information System e. Mobile Number : 085810527731 f. E-mail address : [email protected] 3. Team Members (lecturer) a. Number of Member : Lecturer 2 persons b. Name of Member I (with salutation) : Dr. Puji Rahayu b. Name of Member II (with salutation) : Yunita Sartika Sari, S.Kom, M.Kom. 4. Team Members (student) a. Number of Member : Student 2 persons b. Name of Student I : Yuni Safitri NIM: 41817010047 c. Name of Student II : Amalia Putri Efelina NIM: 41817110041 5. Location of Activity a. Location/Activity Area : Universitas Mercu Buana b. City/Province : Jakarta 6. Project Partner : Prof. Anton Abdul Basah K. (Turki) 7. Output Produced : Draft of Journal 8. Duration : 6 months 9. Source of Expenditure : Rp. ..... a. Source from UMB : Rp. 7.500.000,- b. Source from Partner (In Kind) : Rp. 2.500.000,- Grand Total : Rp. 10.000.000, Jakarta, 15 November 2019 Signed by: Leader of Community Services Group Team Leader (Wawan Gunawan, S.Kom, MT) (Yaya Sudarya Triana, M.Kom., Ph.D. ) NIP/NIK 120810677 NIP/NIK 114640402 Approved by: Dean of Computer Science Head of Community Services (Dr. Mujiono, MT) (Dr. Inge Hutagalung, M.Si) NIP/NIK 110700306 NIP/NIK : 1 1359 0380 i TABLE OF CONTENTS VALIDITY SHEET i TABLE OF CONTENTS ii CHAPTER 1 INTRODUCTION 1 CHAPTER 2 SOLUTION AND OUTPUT TARGETS 5 CHAPTER 3 METHOD OF IMPLEMENTATION 7 CHAPTER 4 COST AND SCHEDULE OF ACTIVITIES 8 REFERENCES 9 APPENDIX 10 ii SUMMARY To meet the current and future needs of society, Data Science seeks to encourage the creation of technology solutions that are useful for users in everyday life. Many scientific disciplines are united behind this goal, with health sciences at the fore, especially given the context of the current battle against the Covid-19 pandemic. These technology-enabled digital tools address problems which, if approached in a conventional manner, would take more time and effort to solve. Data Science is a complex process that can help us as a society achieve our goal of helping people deal with complex problems. Nonetheless, with this ambitious scenario, new challenges emerge that must be overcome to make room for this technique. The challenge becomes complicated when we need to do this learning quickly, observing daily how regrettable situations affect society while scientists in various fields struggle to acquire this knowledge that in theory no one else has. In addressing these challenges, Data Science emerged as a key factor in making the learning process more agile. The various techniques that underlie these technologies compete to ascertain how they can be used to better describe the current situation, predict what may happen tomorrow and, ultimately, help us as a society determine how best to proceed and act. iii CHAPTER I INTRODUCTION 1.1. Situation Analysis The novel coronavirus disease (COVID-19) was first identified in Wuhan, China in early December 2019, but has since spread to other parts of the world. The disease for which at the time of writing this paper has been declared a pandemic by the World Health Organization (WHO). In the following weeks, the virus spread within China then spread widely in other countries and infected more than 1,996,681 people and claimed more than 127,590 lives in the second week of April, 2020.2 Estimating trends in the spread of infection over time can provide information. and insight into the epidemiology of the situation and ascertaining whether outbreak control strategies are having a significant effect. COVID-19 is a respiratory disease caused by the corona virus which is very contagious, especially transmitted through the respiratory tract. This corona virus is a new coronavirus known as SARS-CoV-2 (severe acute respiratory syndrome-coronavirus-2). SARS-CoV-2 differs from the common coronavirus which causes mild illness such as the common cold among humans. It is imperative to understand the impact and outcome of this pandemic. Coronavirus 2019 is different from SARS-CoV but has the same host receptor: the human angiotensin 2 converting enzyme (ACE2). SARS-CoV-2 was first discovered in 2019 in Wuhan, China, unfortunately spreading globally, resulting in a 2019-2020 pandemic, as declared by the World Health Organization (WHO) and Public Health Emergency Concern International (PHEIC). In a situation like this it is necessary to consider strategies for handling the outbreak, so that it can provide consideration for decision making in terms of future progress that can measure risk and for direct mitigation strategies. The spread of infected over time can be traced, so that patterns can be studied. Forecasting methods will be considered based on patterns and time periods. The following is a graph showing the addition of daily data cases in DKI Jakarta from 4 March 2020 to 11 November 2020, as shown in Figure 1.1: 1 Figure 1.1 Additional Covid-19 Daily Cases in DKI Jakarta 4 March 2020 - 11 November 2020 For Suspect Mapping, Close Contact Mapping and Positive Mapping in DKI Jakarta can be shown in Figure 1.2 which is displayed in different colors for each city in DKI Jakarta as follows: Figure 1.2 Suspect Mapping, Close Contact Mapping and Positive Mapping in DKI Jakarta until November 14, 2020 Covid 19 or commonly known as the corona virus, is a virus that attacks the human respiratory system. This virus has claimed tens of thousands of victims in Indonesia and millions of victims in the world. Victims who are positive for the corona virus themselves have common characteristics: fever, dry cough, and fatigue. There are many ways to prevent the spread of the Covid-19 virus, one of which is by using data to determine the distribution and prediction of the number of corona positive victims. One of the ways to stop the spread of the Covid-19 virus is to implement Large-Scale Social Restrictions (PSBB). With the help and role of data science, the PSBB policy can be assessed for its optimality. One of them is the platform created by Lotadata. In collaboration with Citidash and CubeEye, this platform has managed to collect location tracking data from users of thousands of gaming, e-commerce, and social media applications via smartphones. By capturing data on the mobility of people in Indonesia, this platform focuses on seeing the 2 movement of people from Jakarta to 5 cities, namely: Surabaya, Bandung, Semarang, Yogyakarta, and Solo. As a result, the number of movements to several cities continued to increase during the PSBB era in line with the increase in positive cases of corona in those cities . 1.2.Partner Issues Identification and formulation of problems in community service include: 1. How do you provide an understanding to the public to avoid the Covid-19 outbreak? 2. How do you present information about Covid-19 to the public through data science? 1.3.Purpose of Activity The objectives to be achieved in community service this time are: 1. Provide knowledge about the development of the Covid-19 outbreak. 2. Provide knowledge about the benefits of understanding the information presented through data science. 3. Providing knowledge about the creation of information through data science 1.4 Program Activity Objectives 1. Describe the information displayed through data science. 2. Explain how to create information through data science 1.5 Target Program Activities The trainees in this training are Universitas Mercu Buana students who have registered and in accordance with the requirements set by the organizer. 1.6. Benefits of Activities The benefits of this training are: 1. For the Target Group: a. Students gain knowledge about data science b. Students gain knowledge about how to implement Data Science. 2. For Community Service Groups Provide an understanding to the community about the problems faced in interpreting data science. 3 3. To Mercu Buana University as input for Mercu Buana University, introducing UMB to all levels of society and international partners 1. Untuk Kelompok Sasaran: a. Students gain knowledge about modern transactions b. Students get knowledge and benefits from data science c. Students gain knowledge about how to implement data science. 2. For Community Service Groups Provide insight to the community about the problems faced in dealing with the Covid-19 outbreak. 3. To Universitas Mercu Buana University as input for Universitas Mercu Buana, introducing UMB to all levels of society and international partners 4 CHAPTER II SOLUTIONS AND OUTPUT TARGETS 2.1 Solution The next role of data science is to create a dashboard for the spread of the Covid-19 virus. Starting with the dashboard pioneered by John Hopkins University, many other dashboards have emerged which are useful for seeing the number of positive corona victims every day. Maybe after seeing how they visualize and predict, you can get some new information related to the Covid-19 virus. Here are some examples of data science visualization related to the Covid-19 virus. Using Artificial Intelligence, start-up company Landing AI created a workplace monitoring tool that can give a signal if someone is not doing social distancing.
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