COVID-19 Cases In Indonesia Research Articles

The Impact Of Covid-19 On Stock Price And Stock Trade Volume (Case Study of Food and Beverages Companies Listed on the Indonesia Stock Exchange)

The first Covid-19 case in Indonesia was announced on March 2 2020. This study aims to find out whether there is a significant difference in stock prices and stock trading before and after Covid-19 entered Indonesia (Case Study of Registered Food and Beverages Companies on the Indonesian Stock Exchange). The data for this study were taken 9 months before and 9 months after Covid-19 in Indonesia. Data were processed by paired sample t-test, using SPSS. From the results of the data processing, it shows that there was a significant difference in stock prices before and after the announcement of the first case of Covid-19 in Indonesia. This is indicated by a significance value of 0.011 <0.05. Where stock prices have decreased compared to before the Covid-19 case. Meanwhile, stock trading volume also shows a significant difference. Where the significance value is 0.003 <0.05. The stock trading volume after the announcement showed an increasing value.

Edukasi Anak Terkait Protokol Kesehatan Dalam Pencegahan COVID-19 di SDN 003 Sanga-Sanga

<p><em>The increasing number of Covid-19 cases in Indonesia has a significant health impact on the community. The growth of the Covid-19 virus sticks to the hands every day through physical contact with the environment, and some of them can cause or cause various diseases. These microorganisms need to be destroyed or prevented from spreading, one of the easiest and most appropriate ways is with the 3 M, namely increasing knowledge related to Covid-19, and processes through washing hands, wearing masks and removing masks. This service activity aims to provide knowledge about how to prevent Covid-19. The participants of the activity were students of grades 4,5 and 6 at SDN 003 Sanga-sanga. The method used in this activity is in the form of lectures, discussions, practice and demonstrations. The results of the activities achieved through this activity are increasing knowledge about how to prevent Covid-19 so as to increase student awareness to work together in an effort to break the Covid-19 chain in school settings. This health education activity is expected to help health workers in Indonesia in preventing Covid-19 in schools.</em><em></em></p>

IMPACT OF THE COVID-19 PANDEMIC ON INDONESIAN CAPITAL MARKET (IDX COMPOSITE)

The COVID-19 pandemic has caused many problems globally. Various sectors have been affected by this pandemic. In this study, we aim to determine the impact of the COVID-19 pandemic on the Indonesian capital market (IDX Composite). The method used in this study is the quantitative method of collecting data on COVID-19 cases in Indonesia in 2020 and 2020 IDX Composite data from the government’s official website. We also use the Granger Causality Test to check the relationship between those two variables. The COVID-19 impact on Indonesian Capital Market can be seen from this study’s result, where the 2020 COVID-19 cases in Indonesia had a quite large impact on Indonesian Capital Market (IDX Composite). When the COVID-19 cases started in Indonesia in March 2020, the IDX Composite experienced a significant decline.

Predicting Factors for COVID-19 Infection: A Cross-Sectional Study in Indonesia

COVID-19 cases in Indonesia still remain a concern, particularly for public health. Several factors, such as gender, age, comorbidity, occupation, and vaccination status, might influence COVID-19 infection. Individuals who have many predicting factors have a higher risk of being infected by COVID-19. Other studies have not yet shown the significance of predicting factors for COVID-19 infection in Indonesia. The study explored the association between the predicting factors and COVID-19 infection in Indonesia. The study used a cross-sectional method with a population of all Indonesian communities. It was conducted in August 2021 by distributing a Google Form questionnaire in Indonesia. By a saturated sampling of the population in Jawa, Sumatera, Sulawesi, Kalimantan, and Papua, 776 Indonesians were selected; they were aged > 17 years and voluntarily completed the questionnaires. whereas respondents with incomplete data were excluded from this study. The data were analyzed using a binary logistic regression test in SPSS (version 21.0). The respondents include 134 men (17.3%) and 642 women (82.7%). The binary logistic regression analysis showed that COVID-19 infection was more common among respondents who were non-health-care workers (p 0.001) and less common among those who had been fully vaccinated (p 0.001). The COVID-19 infection was significantly associated with occupation and vaccination status. 
 Keywords: COVID-19 Infection, Predicting Factors, Public Health, Health-Care Worker, COVID-19 Vaccination, Comorbidity

Kebijakan- Kebijakan Pemerintah Di Masa Pandemi Dalam Perspektif Hukum Kesehatan

This study examines government policies during the COVID-19 pandemic in terms of health law. Health law is one of the laws reviewed in the COVID-19 pandemic. In handling the COVID-19 pandemic, the Government has issued several legal products such as Government Regulations that also implement the PSBB and Physical Distancing policies, but these policies are not effective in breaking the chain of COVID-19 spread, as seen the number of COVID-19 cases in Indonesia on January 28, 2021, has reached through 1 million cases, the highest in Southeast Asia. This type of research is a normative juridical research that is descriptive in nature by providing solutions to the handling of COVID-19 in Indonesia. This study concludes that the legal politics taken by the government (PSBB and physical distancing) in handling COVID-19 have not maximally protected the right to health of the Indonesian people as mandated by the constitution Article 28H paragraph (1) and Article 34 paragraph (2) and (3) of the 1945 Constitution. The government should implement a partial lockdown policy as China's success in carrying out a partial lockdown in Wuhan. With a partial lockdown in Jakarta Province as the epicenter of the COVID-19 pandemic in Indonesia, the virus will not spread to other provinces.

Citra Politik Kandidat Walikota Semarang dalam Instagram: Analisis Dramaturgi pada Pilwakot Semarang 2020

This article aims to analyze the political image of Hendrar Prihadi (Hendi), incumbent mayoral candidate of Semarang 2020 election shown on Instagram @hendrarprihadi in the midst of covid-19 pandemic. If most candidates concoct political slogans and deliver campaign promises, Hendi’s Instagram portrays more amusing content with a minimum amount of campaign messages. Dramaturgy theory used to analyze framing processes on Instagram as frontstage, and what backstage and offstage factors could affect this single candidate manage to get 91,4% of votes, even though activists consider election in the midst of pandemic as less humane, and single candidate could lower voters’ turnover. Qualitative analysis data collected from interviews and articles shows that amusing content on Hendi’s Instagram designed to pacify the public affected by covid-19, followers are easily extracted by amusing content, and as a method to sheer away from sensitive political issues. Backstage, although Semarang reported as the highest contributor of covid-19 cases in Indonesia, and numbers of rule violation campaigns, candidate characteristic, leadership, incumbent status, and also relation with public and political figure be the several things making candidate’s political image more stable, affecting candidate winning the 2020 Semarang Mayoral Election.

EVALUASI MODEL-MODEL BAYESIAN SPASIAL CONDITIONAL AUTOREGRESSIVE UNTUK PEMODELAN KASUS KEMATIAN CORONA VIRUS DISEASE (COVID-19) DI INDONESIA

Covid-19 cases in Indonesia occurred for the first time on 2 March 2020. By 30 September 2022, Indonesia had 158,173 Covid-19 deaths. Several studies have been done in modelling Covid-19 cases. However, research in modelling the number of Covid-19 deaths using the Bayesian Spatial Conditional Autoregressive (CAR) model is still rare. The Bayesian spatial CAR model has high flexibility in relative risk (RR) modeling. CAR models can include various types of spatial effects and can include covariates in the model. RR represents the ratio of the risk of outcome (Covid-19) in the exposed group compared to the population average (the unexposed group). This study aims to evaluate the BYM, Leroux, and Localised models with five hyperpriors, to obtain the best model for estimating the RR of Covid-19 deaths in Indonesia and to create RR maps. This study used aggregate data on Covid-19 deaths (2 March 2020 - 30 September 2022). Data on the total population and population density of each province in 2021 were also used. The best model selection is based on the lowest Watanabe Akaike Information Criterion (WAIC) and Deviance Information Criterion (DIC) values, and Modified Moran's I (MMI) residual values. The result showed that the CAR BYM model with covariates and with Inverse-Gamma IG(0.5; 0.0005) prior distribution had the lowest DIC and WAIC. As the BYM model does not converge, the model cannot be used in determining the RR of Covid-19 deaths in Indonesia. From the other three models that converge, the Bayesian CAR Leroux model without covariate with IG(0,5;0,0005) has the lowest DIC(393,76), and WAIC(400,12), and its MMI value (-0,26) is approximate to zero. Therefore, the Bayesian CAR Leroux model without covariate with IG(0,5;0,0005) is preferred. The province with the highest RR (2,76) and the lowest RR (0,22) are Yogyakarta and Papua, respectively.

Nutrition Intake, Physical Activity, and Sleep Quality in the Month of Fast During Covid-19 Pandemic

Central Java is one of the provinces with the highest number of positive Covid-19 cases in Indonesia, with 46,903 positive infected cases, with a death rate of 2,110 people (4.49%). During the COVID-19 pandemic, community activities decrease, especially during the fasting month. Their diet has also changed. This study aimed to describe and analyse the relationship between nutritional intake and physical activity on people's sleep quality during the fasting month during the COVID-19 pandemic. The benefit of this research is to provide information on factors related to people's sleep quality, so as to improve public health. The novelty of this research is on aspects of physical activity, and people's sleep quality during the fasting month during the covid-19 pandemic. This research method is observational using a cross-sectional approach. The research was conducted during the fasting month (Ramadan 2021) to find out the nutritional intake, physical activity, and quality of people's sleep while fasting amid the COVID-19 pandemic. This study was attended by 520 respondents who were willing to fill out a questionnaire distributed via Googleform. Respondents in this study were limited to people who live in Central Java. The selection of respondents using the cluster sampling technique and then the snowball method. The questionnaires were the Pittsburgh Sleep Quality Index (PSQI), IPAQ and DQI. The results showed no relationship between physical activity and slept quality during the fasting month (p : 0.402). There is a relationship between food consumption, sleep quality (p: 0.0001), and physical activity (0.007) during the fasting month.

Edukasi Pencegahan Covid-19 Mengunakan Whatsapp Pada Remaja Di Tangerang Selatan

COVID-19 has become a public health problem in the world. WHO has also designated COVID-19 as a pandemic on March 11, 2020. The number of cases of COVID-19 in Indonesia as of December 21, 2020, was 671,778 confirmed cases, with a death rate of 20,085 people. The government has carried out extensive information prevention and dissemination programs, but there is still a lot of disinformation and misinformation in the community, leading to panic and rejection of government recommendations to prevent the transmission of COVID-19. This community service activity aims to increase the role of youth organizations by increasing knowledge of implementing PHBS to prevent COVID-19 in Pondok Karya Village. This activity targets youth who are members of youth organizations (Karang Taruna). The method used provides education about efforts to prevent COVID-19 via Whatsapp Groups about preventing COVID-19. This activity will be held on September 18, 2021, for 60 minutes. During this pandemic, partners temporarily suspended activities that generated crowds so that based on the agreement between partners and the proposer team, community service activities were carried out through Whatsapp lectures. The proposed team will convey the material through text messages, images, and videos in the WhatsApp lecture activity. The results of the analysis showed that there was a difference in knowledge before and after being given education through Kulwap p value= 0.037.

IMPLEMENTASI PROTOKOL PENCEGAHAN PENYEBARAN COVID-19 PADA PROYEK KONSTRUKSI JALAN

The ongoing COVID-19 pandemic is yet to be resolved, and according to epidemiologists, a third wave of the outbreak was expected to occur in February–March 2022. During August–September 2022, the rate of daily COVID-19 exposure in Indonesia remained high. The Indonesian Doctors Association (PB IDI) reported a 36-fold increase in COVID-19 cases in Indonesia, from 107 cases in early May 2022 to 3,949 cases daily. Yogyakarta is the sixth most affected province in Indonesia in terms of COVID-19 exposure. Therefore, it is crucial to examine the implementation of COVID-19 Occupational Health and Safety (OHS) practices in construction projects, specifically in the case of road construction. The Planjan-Baron-Tepus Road and Jogja-Bawen Toll Road are the projects selected for data collection, using observational methods and purposive sampling. Occupational Health and Safety is part of the company's management system, which aims to manage work activity risks and create a safe, efficient, and productive workplace. The survey results indicate that the instrument used is reliable and valid. The management has effectively implemented and communicated COVID-19 prevention measures, and the construction workers are satisfied. The workers show high motivation, awareness, and knowledge in reducing the spread of COVID-19. The workers in Planjan-Baron-Tepus Road construction strictly adhere to personal health protocols in their daily behavior. However, workers in Jogja-Bawen toll road construction are less obedient and require further motivation to be classified as highly obedient.

Tracing Diagnosis COVID-19 Analysis on Google by COVID-19 Cases in Indonesia

COVID-19 transmission can be controlled through RT-PCR and RDT-Ag diagnostic tests, yet neither test performs well. This has encouraged people to search information for the COVID-19 pandemic response and exposure fears on Google. Therefore, this study analyzes the correlation between COVID-19 diagnosis tracing on Google and new COVID-19 cases in Indonesia. An explanatory mixed method study design was used. A quantitative study was done using time-lag correlation between the keywords, namely “Antigen”, “Swab” dan “PCR” based on Google Trends™ (https: // trend.Google.com/trends) from 13 July 2020 to November 2021. The search peaks for diagnosis and their geographical distribution were described qualitatively. There is a correlation between COVID-19 diagnosis searches on the keywords Swab (r = 0.787, P-Value = 0.000) and Antigen (r = 0.378, P-Value = 0.003) with COVID-19 new positive cases. The cumulative number of daily tests is also correlated with COVID-19 diagnosis searches (r = 0.617, P-Value = 0.000 (PCR keywords) and r = -0.337, P-Value = 0.003 (Keywords Swab)). There was also a correlation between searches for COVID-19-related keywords PCR, Swab, and Antigen and the frequency of daily PCR and Antigen tests (P-Value <0.005). Google Trend has the potential as a monitoring tool for people's diagnosis behavior. Further study of Google Trends is required to strengthen the potential of Google Trends for monitoring COVID-19 cases in Indonesia.

Simulasi Perhitungan Premi Asuransi Kesehatan dan Jiwa pada Penderita Covid-19 yang Dipengaruhi Model Penyebaran Penyakit Menular SIDRS

Determination of health and death insurance benefits according to the needs of policyholders is very important to determine from the beginning of making an insurance policy, especially for insurance that takes over the risk of being infected with the COVID-19 virus. Several factors that must be taken into account in determining the amount of benefits and premiums due to COVID-19 are the human population factor that is susceptible, infected and death in the SIDRS infectious disease spread model. In this study, the influence of these three factors on actuarial calculations is examined in more depth to produce an appropriate premium determination formula by taking into account two payment schemes in lump sum and annuity. From the simulation results by applying data on COVID-19 cases in Indonesia to determine the parameters of the SIDRS model, it is concluded that the premium with an annuity benefit payment scheme is smaller than the premium with a lump sum benefit scheme. Furthermore, it is also concluded that if the population of policyholders increases, the premium price will also be lower.

Generalized Space-Time Autoregressive Integrated Moving Average (GSTARIMA) Modeling in Forecasting Covid-19 Cases in Indonesia

Covid-19 is an infectious disease caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). The spread of Covid-19 in Indonesia has grown rapidly that the World Health Organization (WHO) has declared Covid-19 a pandemic. Covid-19 cases have spread to 34 provinces in Indonesia. Covid-19 data in Indonesia involves space and time so the appropriate modeling is the space-time model. Space-time modeling of the Covid-19 case in 34 provinces in Indonesia using the Generalized Space-Time Autoregressive Integrated Moving Average (GSTARIMA) model has not been carried out. The purpose of this research is to get the best GSTARIMA model and forecat the Covid-19 case for the next several times. This model incorporates time and location interdependence with different parameters for each location. Identification of the order of the AR and MA was carried out through the STACF and STPACF plots. For simplicity of interpretation, the spatial order is chosen first order. In this study, the queen contiguity and the inverse distance location weighting matrix were used. The parameter estimation used is Ordinary Least Square (OLS). The results show that the best model for predicting Covid-19 cases in 34 provinces in Indonesia is the GSTARIMA model (1,1,0)1 using an inverse distance weighting matrix with the smallest RMSE value of 1.22.Keywords: Covid-19, GSTARIMA, Queen Contiguity, Inverse Distance, OLS.

Perilaku Kepatuhan Masyarakat dalam Menerapkan Protokol Kesehatan Covid-19

Background: The Covid-19 pandemic in Indonesia is a health problem that has not yet ended. Covid-19 cases in Indonesia on 31 May 2022 were 6.054.973 cases. Indonesia ministry of Health informed that SARS-CoV-2 continues to mutate to form new variants. Therefore, efforts are needed to prevent the transmission of Covid-19 through the implementation of the Covid-19 health protocol. The purpose of this studi was to determine the factors related to community adherence in implementing the Covid-19 health protocol in the Karangsari Healthcare Center, Cirebon Regency. Method: This type of research uses an analytical survey with a cross sectional design. The research sampel is 99 respondents, with cluster sampling technique. The instrument used a questionnaire. Data were analyzed by chi square test and logostic regression. Results: The result show that knowledge (P=0,009, RP=1,470) and attitude (P=0,003, RP=1,564) are related to community adherence in implementing the Covid-19 health protocol in the Karangsari Healthcare Center, Cirebon Regency. Conclusion: There is a significant related between knowledge and attitude with adherence in implementing the Covid-19 health protocol. Attitude is the factors that most influence the adherence in implementing the Covid-19 health protocol in the Karangsari Healthcare Center, Cirebon Regency.

Tweets Emotions Analysis of Community Activities Restriction as COVID-19 Policy in Indonesia Using Support Vector Machine

With the rising number of COVID-19 cases in Indonesia, the government has implemented the Imposition of Restrictions on Emergency Community Activities (Pemberlakuan Pembatasan Kegiatan Masyarakat - PPKM) as Indonesia’s COVID-19 policy. Several controversies and protests have colored the implementation of this emergency policy. Some netizens on Twitter voice their opinions about the policy in their tweets. Emotions in tweets can be recognized through text-based emotion detection or emotion analysis. However, textbased emotion detection is a challenging task. One of the main issues in classifying text with a machine learningbased approach deals with the feature dimensions. As a result, appropriate methods for accurately identifying emotion based on the text are required. The research studies an emotions analysis task on Indonesians’ PPKMrelated tweets to understand their emotional state while implementing the PPKM. The machine learning classification algorithms used are Support Vector Machine (SVM) and random forest. The total number of tweets is 4,401. The results show that SVM with linear kernel function combined with the TF-IDF and Chi-Square methods outperforms other classifiers with an accuracy of 0.7528. The accuracy value is higher than those obtained by previous studies. Moreover, the results of the emotion classification on PPKM tweets reveal that most Indonesians are unhappy with the implementation of the PPKM policy.

Forecasting the Effectiveness of COVID-19 Vaccination Using Vector Autoregressive with an Exogenous Variable: On the Cases of COVID-19 in Indonesia

This study aims to forecast the COVID-19 spread in Indonesia involving vaccination factors using vector autoregressive with exogenous variables (VARX). The COVID-19 spread represented by active, recovered, and death case rate indicators acts as endogenous variables, while the COVID-19 vaccination represented by second-dose vaccination rates acts as exogenous variables. Because the sum of three COVID-19 spread indicators in one day is one, only two indicators with the highest correlation rates are involved in VARX modelling. The other indicator is practically projected by subtracting one from the sum of two indicator projection results. Based on the analysis results, the active and recovered case rates are two indicators chosen in VARX modelling. Using Akaike information criterion, the most suitable VARX model to project the case and recovered case rates are VARX (7, 1). This model is expected to help the Indonesian government project the COVID-19 spread in Indonesia.

Prediction Model for Covid-19 Cases in Indonesia Using Linear Regression and Polynomial Regression Methods

The World Health Organization on March 11, 2020, declared Coronavirus Disease 2019 (Covid-19) a pandemic. Covid-19 is a disease caused by a new type of coronavirus, namely Sars-CoV-2, which affects the respiratory system. Until now, positive confirmed cases of Covid-19 in Indonesia are still occurring every day. This study aims to predict the addition of Covid-19 cases in Indonesia. The data is sourced from the public API page covid19.go.id in the form of an additional number of Covid-19 cases in Indonesia by 122 lines of data. Predictions are made using linear regression and polynomial regression methods as comparisons. Evaluation of the linear regression method obtains a value of R2 = 0.57, while the polynomial regression method obtains a value of R2 = 0.84. Based on these evaluations, the polynomial regression method yields better results than the linear regression method. The prediction of Covid-19 cases in Indonesia from January to March 2022 using the polynomial regression methods predicts that the addition of Covid-19 cases will rise again.

PENGARUH BIAYA LINGKUNGAN TERHADAP NILAI PERUSAHAAN DENGAN KINERJA LINGKUNGAN SEBAGAI VARIABEL MODERASI-SUB SEKTOR PERTAMBANGAN DIBURSAEFEK INDONESIA TAHUN 2019-2021

This research aims to determine the difference in the earnings quality of company before and after the national announcement of Covid-19 cases in Indonesia in manufacturing companies. The Covid-19 pandemic has decreased the company's revenue so that it has the potential to cause company financial problems and information asymmetry. This can cause the management to potentially carry out earnings management so that it will affect the earnings quality. The variable used in this study is earnings quality. The indicator used to measure earnings quality is using Earnings Response Coefficients (ERC). This research was conducted on trading, service and investment sector companies listed on the Indonesia Stock Exchange. The sampling method used is purposive sampling and there are 145 companies used in this research. The results of this research indicate that there is no significant difference between the earnings quality before and after the announcement of the Covid-19 pandemic in Indonesia.

The Information Analysis on New Media in Period of Pandemic: An Observation of Infodemics Study case

Apart from fighting against pandemics, we are also fighting against infodemics which is a kind of biased information wave that made it difficult for people to receive original information. Such as misinformation, disinformation, rumors, and hoaxes during an emergency, hindering responses, and creating confusion and distrust in society. Here, media platforms have a crucial part in filtering any information before transmitting it through channels of news. However, in the modern era, Social Networking Services (SNS) platforms become a new lifestyle, particularly for receiving and sharing information. Therefore, as information receivers, it becomes essential to understand the information before sharing it with other people. The objective of this present study is to determine the degree of understanding SNS users in receiving and sharing information in their community during the pandemic era. The research method used is a case study approach that examines one case intensively, in-depth, in detail, and comprehensively. The result of this study are (1) during the pandemic, the news they got was about developments in the COVID-19 case in Indonesia, news related to alternative medicines and vaccine drugs. (2) Sources get news information from the social media they use and also the WhatsApp groups they follow, (3) This research indicates that the infodemic is increasingly rampant until now, mass media supervisors are already working to block hoax information, but users who do not have awareness in selecting and sorting news Keyword : Information, New Media, Infodemic, Social Media

ANALISIS KOMPARATIF KUALITAS LABA SEBELUM DAN SESUDAH PENGUMUMAN KASUS COVID-19 DI INDONESIA PADA PERUSAHAAN MANUFAKTUR YANG TERDAFTAR DI BURSA EFEK INDONESIA TAHUN 2019 – 2020

This research aims to determine the difference in the earnings quality of company before and after the national announcement of Covid-19 cases in Indonesia in manufacturing companies. The Covid-19 pandemic has decreased the company's revenue so that it has the potential to cause company financial problems and information asymmetry. This can cause the management to potentially carry out earnings management so that it will affect the earnings quality. The variable used in this study is earnings quality. The indicator used to measure earnings quality is using Earnings Response Coefficients (ERC). This research was conducted on trading, service and investment sector companies listed on the Indonesia Stock Exchange. The sampling method used is purposive sampling and there are 145 companies used in this research. The results of this research indicate that there is no significant difference between the earnings quality before and after the announcement of the Covid-19 pandemic in Indonesia.