ABSTRACT
The COVID-19 pandemic that has hit the whole world has caused losses in various aspects. Several countries have implemented lockdowns to curb the spread of the SARS-CoV-2 virus that caused death. However, for developing countries such as Indonesia, it is not suitable for lockdown because it considers the economic recession. Instead, the Large-scale Social Restrictions (LSSR) regulation is applied, the same as the partial lockdown. Thus, it is hypothesized that implementing LSSR that limits anthropogenic activities can reduce heat emissions and air pollution. Utilization of remote sensing data such as Terra-MODIS LST and Sentinel-5P images to investigate short-term trends (i.e., comparison between baseline year and COVID-19 year) in surface temperature, Surface Urban Heat Islands Intensity (SUHII), and air pollution such as NO2, CO, and O3 in Malang City and Surabaya City, East Java Province. Spatial downscaling of LST using the Random Forest Regression technique was also carried out to transform the spatial resolution of the Terra-MODIS LST image to make it feasible on a city scale. Raster re-gridding was also implemented to refine the Sentinel-5P spatial resolution. The accuracy of LST spatial downscaling results is quite satisfactory in both cities. Surface temperatures in both cities slightly decreased (below 1 °C) during LSSR was applied (P < 0.05). SUHII in both cities experienced a slight increase in both cities during LSSR. NO2 gas was reduced significantly (P < 0.05) in Malang City (â¼38%) and Surabaya City (â¼28%) during LSSR phase due to reduced vehicle traffic and restrictions on anthropogenic activities. However, CO and O3 gases did not indicate anomaly during LSSR. Moreover, this study provides insight into the correlation between SUHII change and the distribution of air pollution in both cities during the pandemic year. Air temperature and wind speed are also added as meteorological factors to examine their effect on air pollution. The proposed models of spatial downscaling LST and re-gridding satellite-based air pollution can help decision-makers control local air quality in the long and short term in the future. In addition, this model can also be applied to other ecological research, especially the input variables for ecological spatial modeling.
ABSTRACT
Masa kenormalan baru menuntut masyarakat untuk beradaptasi terhadap virus Corona. Sehingga pemerintah desa mengeluarkan kebijakan agar masyarakat membiasakan diri untuk menerapkan perilaku hidup sehat. Namun kebijakan tersebut belum dapat dilakukan dengan baik karena keterbatasan pengetahuan tidak ada pengalaman dan penglihatan dan banyaknya berita bohong yang beredar di media sosial. Kepercayaan masyarakat yang rendah terhadap keberadaan virus Corona juga merupakan salah satu masalah yang serius jika tidak segera ditindaklanjuti. Banyak masyarakat menganggap bahwa virus Corona merupakan konspirasi orang elit yang mempunyai kepentingan tersendiri menurut berita bohong yang beredar di media sosial. Oleh karena itu diperlukan kegiatan pengabdian kepada masyarakat berupa pendampingan khususnya masyarakat Desa Bangsri agar mematuhi protokol kesehatan dengan berperilaku hidup sehat. Metode pendampingan yang digunakan adalah metode PAR (Participation Action Research). Dengan demikian dalam proses pengabdian tim terlibat secara partisipatif di antara masyarakat untuk mendorong terjadinya perubahan perilaku terkait perilaku hidup sehat. Setelah pengabdian kepada masyarakat dilaksanakan masyarakat Desa Bangsri menjadi antusias dalam menerapkan protokol kesehatan dan berperilaku hidup sehat seperti selalu memakai masker dimanapun rajin cuci tangan memakai sabun jaga jarak menghindari kerumunan rajin mengonsumsi vitamin olahraga secara teratur rajin membersihkan lingkungan sekitar dan rajin mengonsumsi empon-empon. Kata kunci: Hidup Sehat Kenormalan Baru Desa Bangsri The new normality requires people to adapt to the Coronavirus. So that the village government issued a policy so that people get used to implementing healthy living habits. However, this policy has not been implemented properly due to limited knowledge lack of experience and vision and the large number of fake news circulating on social media. The low public trust in the existence of the Coronavirus is also a serious problem if it is not followed up immediately. Many people think that the Coronavirus is a conspiracy of elite people who have their own interests according to fake news circulating on social media. Therefore, Community service activities are needed in the form of assistance especially for the Bangsri Village community to comply with health protocols by behaving in a healthy life. The mentoring method used is the PAR (Participation Action Research) method. Thus, in the process of community service the team is involved in a participatory manner among the community to encourage behavior change related to healthy living behaviors. After the community service was carried out the people of Bangsri Village became enthusiastic in implementing health protocols and behaving in a healthy life such as always wearing a mask wherever diligently washing hands with soap keeping distance avoiding crowds diligently consuming vitamins exercising regularly diligently cleaning the surrounding environment and diligently consume empon-empon. Keywords: Healthy living New normalcy Bangsri
ABSTRACT
Selama pandemi COVID-19, terjadi perilaku konsumen yang tidak biasa, seperti membeli kebutuhan pokok dalam jumlah besar. Peneliti menyelidiki perilaku ini saat ketakutan akan gangguan pasar konsumen mulai beredar, untuk mengetahui perilaku manusia dalam situasi yang unik ini. Berdasarkan kerangka stimulus-organisme-respons (SOR), konstruksi model struktural yang menghubungkan pajanan sumber informasi online (stimulus lingkungan) dengan dua respons perilaku: pembelian yang tidak biasa dan isolasi diri sukarela. Untuk menguji model yang diajukan, kami mengumpulkan data dari 236 responden di Indonesia melalui survei online, dan melakukan analisis menggunakan PLS-SEM. Hasil analisis menemukan hubungan yang kuat antara niat diri untuk mengisolasi diri dan niat untuk melakukan pembelian yang tidak biasa, dan memberikan bukti empiris bahwa perilaku konsumen yang dilaporkan terkait langsung dengan perkiraan waktu yang dihabiskan untuk isolasi diri. Lebih lanjut, hasil penelitian menemukan kelebihan beban informasi merupakan prediktor kuat cyberchondria. Persepsi keparahan situasi dan cyberchondria berdampak signifikan terhadap niat orang untuk melakukan pembelian yang tidak biasa dan melakukan isolasi diri secara sukarela. Penelitian di masa depan diperlukan untuk memastikan efek jangka panjang pandemi terhadap layanan konsumen dan ritel.
ABSTRACT
In this research, we analyzed COVID-19 distribution patterns based on hotspots and space–time cubes (STC) in East Java, Indonesia. The data were collected based on the East Java COVID-19 Radar report results from a four-month period, namely March, April, May, and June 2020. Hour, day, and date information were used as the basis of the analysis. We used two spatial analysis models: the emerging hotspot analysis and STC. Both techniques allow us to identify the hotspot cluster temporally. Three-dimensional visualizations can be used to determine the direction of spread of COVID-19 hotspots. The results showed that the spread of COVID-19 throughout East Java was centered in Surabaya, then mostly spread towards suburban areas and other cities. An emerging hotspot analysis was carried out to identify the patterns of COVID-19 hotspots in each bin. Both cities featured oscillating patterns and sporadic hotspots that accumulated over four months. This pattern indicates that newly infected patients always follow the recovery of previous COVID-19 patients and that the increase in the number of positive patients is higher when compared to patients who recover. The monthly hotspot analysis results yielded detailed COVID-19 spatiotemporal information and facilitated more in-depth analysis of events and policies in each location/time bin. The COVID-19 hotspot pattern in East Java, visually speaking, has an amoeba-like pattern. Many positive cases tend to be close to the city, in places with high road density, near trade and business facilities, financial storage, transportation, entertainment, and food venues. Determining the spatial and temporal resolution for the STC model is crucial because it affects the level of detail for the information of endemic disease distribution and is important for the emerging hotspot analysis results. We believe that similar research is still rare in Indonesia, although it has been done elsewhere, in different contexts and focuses.