Analisa Tingkat Kecemasan Masyarakat Jabodetabek sebagai Prior Research terhadap Fenomena Wabah COVID-19

Research sangat diperlukan oleh pengambil kebijakan dalam membuat regulasi demi meminimalisir efek negatif akibat pandemi COVID-19. Meskipun pandemi sudah berlangsung kurang lebih selama enam bulan, prinsip kehati-hatian tetap diperlukan agar tidak mengambil keputusan secara tergesa-gesa, sehingga Indonesia dapat melakukan rebound agar terhindar kondisi yang lebih buruk. Dari mini research yang penulis dan tim lakukan, berikut masukan yang dapat penulis sampaikan: (1) Perlunya skala prioritas dalam menyusun kebijakan dalam menangani dampak pandemi COVID-19 harus dibuat. (2) Perlunya perlakukan khusus (specific treatment) untuk kelompok masyarakat tertentu pada beberapa regulasi dan kebijakan yang akan diterapkan pemerintah, karena dampak pandemi yang diterima masyarakat tidak semuanya sama.

Transcript

1. FINAL REPORT SOLVER SOCIETY ON COVID-19 Analisa Tingkat Kecemasan Masyarakat Jabodetabek terhadap Fenomena Wabah COVID-19
2. METHODOLOGY Cross Industry Standard Process for Data Mining : 1. Problem Understanding 2. Data Understanding 3. Data Preparation 4. Data Analysis
3. METHODOLOGY START Problem Understanding Is there any trend caused by COVID-19? In what aspect do people feel anxious the most? Data Collection Social Media (Twitter) External Data (Websites) Online Questionnaire Data Pre-Processing Remove Duplicate Impute Missing Value Standardisation Trend Analysis Food & Exchange Rate Pollution and Airport Traffic Test and Burial with COVID- 19 Procedure Perception Analysis Economy Aspect & Sub Aspects Social Aspect & Sub Aspects Health Aspect & Sub Aspects Regression Analysis Age Group Region Group Profession Group FINISH
4. 1. Do people feel anxious due to Corona Virus (COVID-19) outbreak? 2. Is there any trend caused by Corona Virus (COVID-19) outbreak phenomenon? 3. How anxious people are about Corona Virus (COVID-19) outbreak phenomenon? Next step: 1. Portray people anxiety due to Corona Virus (COVID-19) outbreak • Economy • Social • Health 2. Find the Representative Data • General: Social Media Data, News, & Website Release • Specific: Online Quetionaire Data PROBLEM UNDERSTANDING
5. 1. Social Media Data • Twitter (Collected Through API) per Day • Keyword: “Corona” and “COVID” • 10 miles radius from center point of Jakarta 2. Extenal Data from Website • Rice Price and Currency Exchange Rate • Jakarta Pollution and Airline Traffic • Total Corona Test 3. Online Questionaire • Demography • Anxiety in economy aspect in likert scale • Anxiety in social aspect in likert scale • Anxiety in health aspect in likert scale DATA UNDERSTANDING Field: • userID • statusID • Created_at • text Field: • Rice Price (Rp) • Pollution (PM 2.5) • Total test (count) Field: • Demography • Anxiety in Economy • Anxiety in Social • Anxiety in Health
6. 1. Data Cleansing • Clean unneeded column for twitter Data • Clean questionnaire data who gives non-standard answer 2. Impute Missing Value • For external data, missing value at t (time) will be replaced with t-1 value • For uncollected data, we use means of next 5 consecutive days data. 3. Remove Duplicate • Remove duplicate tweet • Check duplicate data in questionnaire data DATA PREPARATION
7. 1. Trend Analysis 2. Perception Analysis 3. Regression Analysis DATA ANALYSIS
8. TREND ANALYSIS BASED ON SOCIAL MEDIA & EXTERNAL DATA
9. TWITTER TREND March 2nd First case announce by the govt March 14th: Social Distancing suggestion by the govt *start collected from March 5th March 21st: Govt announced to hold rapid tests
10. TWITTER TREND
11. TWITTER TREND VS FOOD PRICE March 2nd First case announce by the govt March 6th The price start to increase significantly March 17th - 18th: The highest peak = 10.900/kg New normal: 10.700 – 10.900
12. TWITTER TREND
13. TWITTER TREND VS POLLUTION LEVEL March 2nd First case announce by the govt March 14th: Social Distancing suggestion by the govt Pollution is stable even during WFH suggestion by the govt Probably cause: Transportations and Factories
14. TWITTER TREND VS POLLUTION LEVEL
15. TWITTER TREND
16. TWITTER TREND VS TOTAL TEST March 2nd First case announce by the govt March 21st: Rapid test announcement by the Govt March 25st: Total test significantly increase (almost 500)
17. TWITTER TREND
18. CONCLUSSION 1. Total tweet significantly increase after flagged moment during COVID-19 pandemic situation (especially in Jakarta) 2. In economy aspect, COVID-19 issues could cause price increase, but fortunately for staple food price it was still controllable by the government (through BULOG) 3. In social aspect, WFH and social distancing suggestions in March 14th were not fully obeyed even it was discussed frequently in social media, according to pollution data. 4. In health aspect, rapid test impelementation by the government trigger many issues and discussion in social media (according to total tweet), but in total test data it effectively started in March 25th (identified by an increase of total test which reached about 500 in one day)
19. PERCEPTION ANALYSIS BASED ON ONLINE QUESTIONAIRE
20. DEMOGRAPHY Majority of respondents: young adult (based on age), live in Depok (based on city of living), and students and private company employees (based on profession)
21. ECONOMY ASPECT Summary: Most of respondent feel quite anxious in their economy during COVID-19 outbreak period (37.7%) According to 3 aspects, respondents feel worried the most in staple food prices and inflation/recession as the effects of COVID-19 outbreak
22. SOSIAL ASPECT Summary: Most of respondent feel anxious in their social life during COVID-19 outbreak period (37.7%) According to 3 aspects, respondents feel worried the most in mass people activity and meeting with foreigners as the effects of COVID- 19 outbreak
23. HEALTH ASPECT Summary: Most of respondent feel very anxious about their health during COVID-19 outbreak period (31.9%) According to 3 aspects, respondents feel worried the most in their higienity and immune system as the effects of COVID-19 outbreak
24. QUADRANT Daftar 2.1 Harga Bahan Pokok 2.2 Inflasi/Resesi 2.3 Penurunan Pendapatan 3.1 Berinteraksi 3.2 Berkumpul/Berada di Kerumunan 3.3 Bertemu orang asing 4.1 Higenitas 4.2 Masker 4.3 Daya tahan tubuh • Aspects with high anxiety and importance level: 2.2, 3.2, 3.3, 4.1, and 4.3 • Aspects with high anxiety level but middle importance level: 2.1, 2.3, 4.2 • Aspects with middle anxiety level but high importance level: 3.1 (border line)
25. CONCLUSSION 1. The aspect order start from the highest anxious aspect: 1. Health, 2. Social, 3.Economy. 2. In economy aspect, the most anxious sub aspect according to the survey were staple food price and inflation/recession occurrence during COVID-19 pandemic situation. 3. In social aspect, the most anxious sub aspect according to the survey were mass-acticities/activity in crowd and meeting with foreigners. 4. In health aspect, the most anxious sub aspect according to the survey were body-hygiene and body immunity. 5. Sub aspect with highest anxiety and importance level: 2.2 (recession anticipation), 3.2 (mass activities restriction), 3.3 (foreigner entrance limitation), 4.1 (hygiene guarantee in private & public area), 4.3. (guarantee in nutrition food/supplement resource)
26. REGRESSION ANALYSIS BASED ON ONLINE QUESTIONAIRE
27. REGRESSION • Refers to International Journal about public anxiety • Compare anxiety level between groups (whether it is significant or not) • Age group: <=27 (1), 28-36 (2), 37-45 (3), >45 (4/control) • Region group: Jakarta (1), Outside Jakarta (2/control) • Profession group: Govt. Employee (1), Comp. Employee (2), Self- employment (3), Unemployed (4/control) • Siginificancy using alpha = 0.05
28. ECONOMY ASPECT Significant Differences: • <27, 28–36, and 37-45 vs >45 in Economy • 28-36 and 37-45 vs >45 in Food Price Sub-Aspect Summary Anxiety in Economy Anxiety in Food Price Anxiety in Recession Anxiety in Income Age Group Coef P-Value Coef P-Value Coef P-Value Coef P-Value Age <= 27 -2.761 0.021 -2.117 0.074 -1.211 0.29 -1.96 0.099 28 <= Age <= 36 -2.431 0.047 -2.574 0.035 -1.663 0.159 -2.946 0.017 37 <= Age <= 45 -3.129 0.046 -3.162 0.043 -2.903 0.059 -2.853 0.069 Age > 45 - - - - - - - - Region Group Coef P-Value Coef P-Value Coef P-Value Coef P-Value Jakarta 3.82E-01 0.374 0.009 0.983 0.145 0.736 7.90E-02 0.852 Outside Jakarta - - - - - - - - Profession Group Coef P-Value Coef P-Value Coef P-Value Coef P-Value Govt Employee 0.761 0.346 0.643 0.424 0.496 0.538 -0.181 0.82 Comp Employee 1.166 0.012 0.674 0.137 0.669 0.141 0.302 0.498 Self Employment 1.651 0.062 0.279 0.747 -0.751 0.384 0.848 0.327 Unemployed - - - - - - - - • 28–36 vs >45 in Income Sub-Aspect • Comp Employee vs Unemployed in Economy
29. ECONOMY ASPECT Significant Differences: • All age groups <45 have lower anxiety level than age >45 in Economy • 28-45 age group have lower anxiety level than age >45 in food price • 28-36 age group have lower anxiety level than age >45 in income
30. ECONOMY ASPECT Significant Differences: • Company employee (public or private company) have higher anxiety level than Unemployed (student or housewife).
31. SOCIAL ASPECT Significant Differences: • 37 – 45 vs >45 in Crowd Sub-Aspect Summary Anxiety in Social Anxiety in Interaction Anxiety in Crowd Anxiety in Foreigners Age Group Coef P-Value Coef P-Value Coef P-Value Coef P-Value Age <= 27 0.123 0.909 -0.104 0.923 -1.348 0.288 -0.228 0.838 28 <= Age <= 36 -0.465 0.676 -0.069 0.951 -1.615 0.214 -1.146 0.32 37 <= Age <= 45 -1.408 0.34 -1.473 0.321 -3.437 0.036 -2.124 0.165 Age > 45 - - - - - - - - Region Group Coef P-Value Coef P-Value Coef P-Value Coef P-Value Jakarta -0.087 0.84 0.371 0.389 -0.081 0.851 -7.35E-01 0.092 Outside Jakarta - - - - - - - - Profession Group Coef P-Value Coef P-Value Coef P-Value Coef P-Value Govt Employee 0.037 0.963 0.144 0.857 0.405 0.619 -0.598 0.457 Comp Employee 0.317 0.48 0.457 0.311 0.278 0.539 -0.168 0.711 Self Employment -0.635 0.461 -0.837 0.338 -0.43 0.618 -1.453 0.102 Unemployed - - - - - - - -
32. SOCIAL ASPECT Significant Differences: • Respondent with age 37-45 have lower anxiety level than >45 in Crowd
33. HEALTH ASPECT Significant Differences: • Jakarta vs Outside Jakarta in Hygiene Sub-Aspect • Self Employment vs Unemployed in Hygiene Sub-Aspect Summary Anxiety in Health Anxiety in Hygiene Anxiety in Mask Anxiety in Immunity Age Group Coef P-Value Coef P-Value Coef P-Value Coef P-Value Age <= 27 -0.348 0.754 -0.128 0.91 -0.559 0.608 -0.145 0.894 28 <= Age <= 36 -0.892 0.436 -0.843 0.471 -1.576 0.163 -0.995 0.375 37 <= Age <= 45 -2.38 0.116 -7.50E-17 1 -2.6 0.084 -1.601 0.285 Age > 45 - - - - - - - - Region Group Coef P-Value Coef P-Value Coef P-Value Coef P-Value Jakarta -0.085 0.842 -0.913 0.049 -0.077 0.857 -5.34E-01 0.218 Outside Jakarta - - - - - - - - Profession Group Coef P-Value Coef P-Value Coef P-Value Coef P-Value Govt Employee 0.096 0.905 -0.456 0.591 -0.09 0.91 -0.356 0.657 Comp Employee 0.306 0.498 -0.336 0.479 0.118 0.791 0.148 0.741 Self Employment -1.508 0.085 -2.718 0.003 -1.449 0.098 -0.693 0.427 Unemployed - - - - - - - -
34. HEALTH ASPECT Significant Differences: • Self-employment respondents have lower anxiety level than unemployed in Hygiene • Jakarta respondents have lower anxiety level than Outside Jakarta in Hygiene
35. CONCLUSSION 1. In economy aspect, significant difference occurred between age groups in economy aspect, staple food price sub-aspect, and income sub-aspect. At the same aspect, significant difference also occurred between company employee and unemployed respondent. 2. In social aspect, significant difference occurred between 37-45 age group and >45 age group in crowd sub-aspect. 3. In health aspect, significant difference occurred between self- employment and unemployed respondent. At the same sub-aspect, significant difference also occurred between Jakarta and Outside Jakarta respondent.
36. THANK YOU