Data dan informasi merupakan bagian penting dalam pertimbangan mengambil keputusan terkait penanganan COVID-19. Data COVID-19 baik demografi maupun agregat di Provinsi DKI Jakarta diolah dan dianalisis untuk memberikan informasi mengenai situasi dan kondisi terkini terkait pandemi COVID-19 di Provinsi DKI Jakarta. Data COVID-19 tersebut juga dimanfaatkan untuk analisis prediktif untuk mengetahui perkiraan jumlah kasus COVID-19 di masa depan. Analisis prediktif yang digunakan dalam artikel ini adalah metode Autoregressive Integrated Moving Average (ARIMA). Model ARIMA merupakan salah satu metode forecasting hasil dari perluasan model Autoregressive Moving Average (ARMA) untuk data yang tidakstasioner. Analisis dan visualisasi data dilakukan menggunakan program Python dan Tableau dimana hasil analisis prediktif memperlihatkan tren kasus positif harian yang cenderung naik di kurun waktu 14 hari ke depan dari data yang digunakan. Hasil analisis ini dapat digunakan sebagai pertimbangan bagi pemerintah dalam mengambil kebijakan dan intervensi dalam penanganan COVID-19 di Jakarta, dan untuk masyarakat agar tetap melakukan tindakan preventif dalam mencegah kenaikan kasus, seperti mematuhi protokol kesehatan yang sudah ditetapkan oleh Pemerintah.

Almost all countries obtain significant and multidimensional challenges of COVID-19. Various countries possess varied responses and policies regarding COVID-19. Since the Indonesian government affirmed COVID-19 a national emergency on March 2, 2020, it is necessary to have official information that can be accessed by the public, which at that time did not yet have the Central Government Website. Moreover, the importance of the availability of public information/data contained in official online pages can be used by governments to formulate data-based policies. Jakarta is a pioneer in developing a government website related to COVID-19. This paper provides lessons learned from developing an official COVID-19 website of the Provincial Government of Jakarta. This paper outlines different aspects of developing an official COVID-19 website and an ideal solution to the challenges involved in developing one. This paper uses agile development methods as an evidence base to develop a website. The most interesting finding is that the corona website has been successful in attaining 27,569,404 visitors, 120 collaborators who donate 151,567 pcs of social aid. This finding confirms that this study provides a better understanding of common elements in building an official COVID-19 website. The no-nonsense method of developing an official COVID-19 website can be easily replicated and followed by other cities to consider the model in developing a similar website.

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COVID-19 has a severe and widespread impact, especially in Indonesia. One of the efforts of the DKI Jakarta Provincial Government in reducing the risk of spreading the virus is by implementing a Large-Scale Social Restriction (hereafter referred to as PSBB) policy. The hope of implementing this policy is to detain or even reduce active (positive) cases in Jakarta. In this paper, we conduct Exploratory Data Analysis (EDA) to analyze and evaluate the effect of the PSBB policy that has been made by the DKI Jakarta Provincial Government in minimizing the active cases and in increasing the number of tests in Jakarta. The results show that the PSBB policy was not directly able to limit the rate of active cases, but specific cases of people in intensive care were able to be suppressed. The results suggest that the other local governments can use EDA method in making further policies and interventions for handling COVID-19. The results also indicate that the public is expected to continue to take preventive actions, such as complying with health protocols established by the government.

Coronavirus disease 2019 (COVID-19) has been a global disaster, with over 746,312 confirmed cases and still counting in Indonesia, especially Jakarta, which has about 50 per cent asymptomatic confirmed cases. This paper aims to investigate the persistent factors of COVID-19 diagnosis using four scenarios of asymptomatic inclusion. We use Bayesian Logistic Regression to identify the factors of COVID-19 positivity, which can address issues in the traditional approach such as overfitting and uncertainty. This study discovers three main findings: (1) COVID-19 can infect people regardless of age; (2) Among twelve symptoms of coronavirus (COVID-19), five symptoms increase the COVID-19 likelihood, and two symptoms decrease the possibility of COVID-19 infection; and (3) From an epidemiological perspective, the contact history rises the probability of COVID-19, while healthcare workers and people who did travel are less likely to become infected from COVID-19. Therefore given this study, it is essential to be attentive to the people who have the symptoms and contact history. Surprisingly, health care workers and travelers who apply health protocols strictly according to the rules have a low risk of COVID19 infection.