ABSTRACT
Introduction: The COVID-19 pandemic has caused disruptions in educational institutions across the country, prompting medical schools to adopt online learning systems. This study aims to determine impact on medical education and the medical student’s attitude, practice, mental health after 1 year of the Covid-19 pandemic in Indonesia. Methods: This study utilized a cross-sectional design. An online questionnaire was distributed digitally to 49 medical schools in Indonesia from February–May 2021. A total of 7,949 medical students participated in this study. Sampling was carried out based on a purposive technique whose inclusion criteria were active college students. This research used questionnaires distributed in online version among 49 medical faculties that belong to The Association of Indonesian Private Medical Faculty. Instruments included demographic database, medical education status, experience with medical tele-education, ownership types of electronic devices, availability of technologies, programs of education methods, career plans, attitudes toward pandemic, and the mental health of respondents. Univariate and bivariate statistical analysis was conducted to determine the association of variables. All statistical analyses using (IBM) SPSS version 22.0. Results: Most of the respondents were female (69.4%), the mean age was 20.9 ± 2.1 years. More than half of the respondents (58.7%) reported that they have adequate skills in using digital devices. Most of them (74%) agreed that e-learning can be implemented in Indonesia. The infrastructure aspects that require attention are Internet access and the type of supporting devices. The pandemic also has an impact on the sustainability of the education program. It was found that 28.1% were experiencing financial problems, 2.1% postponed their education due to this problems. The delay of the education process was 32.6% and 47.5% delays in the clinical education phase. Around 4% student being sick, self-isolation and taking care sick family. the pandemic was found to affect students’ interests and future career plans (34%). The majority of students (52.2%) are concerned that the pandemic will limit their opportunities to become specialists. Nearly 40% of respondents expressed anxiety symptoms about a variety of issues for several days. About a third of respondents feel sad, depressed, and hopeless for a few days. Conclusion: The infrastructure and competency of its users are required for E-learning to be successful. The majority of medical students believe that e-learning can be adopted in Indonesia and that their capacity to use electronic devices is good. However, access to the internet remains a problem. On the other side, the pandemic has disrupted the education process and mental health, with fears of being infected with SARS-CoV-2, the loss of opportunities to apply for specialty training, and the potential for increased financial difficulties among medical students. Our findings can be used to assess the current educational process in medical schools and maximize e-learning as an alternative means of preparing doctors for the future. Copyright © 2022 Turana, Primatanti, Sukarya, Wiyanto, Duarsa, Wratsangka, Adriani, Sasmita, Budiyanti, Anditiarina, Ainin, Sari, Darwata, Astri, Prameswarie, Tursina, Purbaningsih, Kurniawan, Widysanto, Setiawan, Ma’roef, Yuliyanti, Rahayu, Sahadewa, Raharjo, Lestari, Pinilih, Dewi, Dinata, Permatasari, Rahayu, Mahardhika, Herlinawati, Hayati, Setyonugroho, Diarsvitri, Purwaningsari, Chiuman, Latief, Triliana, Tubarad, Triastuti, Sompa, Angreni, Lubis, Tadjudin, Pandhita, Pramuningtyas, Anas, Ayuningtiyas, Ivone, Yunita, Handayani, Puspitasari, Tendean, Suswanti and Kurniawan.
ABSTRACT
Based on information on the BNPB website on 2 September 2020, the positive rate for coronavirus disease (COVID-19) in Indonesia reached 25.25% on 30 August 2020. This is a big challenge for the Indonesian government to reduce the positivity rate to meet the standards safe accepted by World Health Organization (WHO) is 5%. To ensure the accuracy of government policies, accurate data predictions are needed. Therefore, the prophet's machine learning algorithm can be used to see trends in the spread of COVID-19 in the next one year. This algorithm has a fairly high level of accuracy because the data contains time variables which are adjusted to the dataset. In several previous research, the dataset was vast uncertain and small. Meanwhile in this research, data was taken from 2 March 2020 to 12 February 2021 on the KawalCOVID19 website. This data is used to predict from 13 February 2021 to 12 February 2022. There are 3 data used;namely data confirmed, recovered and died. Based on the analysis, the confirmed patient was 22.60-42.11%, died amounted to 21.67%-39.00%, and recovered by 22.53-41.82%. The prediction percentage that the average cases died was 2.43% every day. The accuracy of data confirmed was 43.97%, died was 72.50% and recovered was 84.24%. © 2021 Institute of Advanced Engineering and Science. All rights reserved.
ABSTRACT
Internet of Things (IoT) technological assistance for infectious disease surveillance is urgently needed when outbreaks occur, especially during pandemics. The IoT has great potential as an active digital surveillance system, since it can provide meaningful time-critical data needed to design infectious disease surveillance. Many studies have developed the IoT for such surveillance;however, such designs have been developed based on authors' ideas or innovations, without consideration of a specific reference model. Therefore, it is essential to build such a model that could encompass end-to-end IoT-based surveillance system design. This paper proposes a reference model for the design of an active digital surveillance system of infectious diseases with IoT technology. It consists of 14 attributes with specific indicators to accommodate IoT characteristics and to meet the needs of infectious disease surveillance design. The proof of concept was conducted by adopting the reference model into an IoT system design for the active digital surveillance of the Covid-19 disease. The use-case of the design was a communitybased surveillance (CBS) system utilizing the IoT to detect initial symptoms and prevent closed contacts of Covid-19 in a nursing home. We then elaborated its compliance with the 14 attributes of the reference model, reflecting how the IoT design should meet the criteria mandated by the model. The study finds that the proposed reference model could eventually benefit engineers who develop the complete IoT design, as well as epidemiologists, the government or the relevant policy makers who work in preventing infectious diseases from worsening. © 2021. All Rights Reserved.
ABSTRACT
This analysis aims to investigate Muslim youths' compliance behavior towards the Malaysian government's MCO and analyze the differences in compliance behaviors towards MCO between male and female youth. The design of this study is a survey study on 545 respondents who were purposefully selected among Muslim youth. Meanwhile, the data was analyzed using descriptive statistical techniques and inferential test Mann-Whitney U. The results of the study revealed that the majority of youths reacted positively and complied towards MCO. While the Mann-Whitney U test showed no significant difference between the compliance behaviors of male and female youth towards MCO (p> 0.05).