ABSTRACT
The tourism sector was among the most affected sector during the COVID-19 pandemic and has lost up to USD 5.87 billion potential revenue. Since many countries closed the borders, including Indonesia, by applying travel restrictions and thus tourists postponed their visits. Whereas vaccine distribution has shown good progress as the vaccination percentage in Jakarta and Bali has shown promising results since the majority of its population has been vaccinated, and it helps many industries, including tourism, recover. However, the pandemic might change tourist behavior. In addition, information about tourist destinations is spread poorly in various sources, and it psychologically affects tourists' decision to visit. Many works have been published to address this issue with the recommendation system. However, it does not provide geopolitical variables such as PPKM in Indonesia to ensure safeness for the tourist. Therefore, this research aims to enhance innovations in the tourism industry by considering the geopolitics factor into the system using Multiple Linear Regression. The result of this research demonstrates the effectiveness of geopolitics added variable on three different cities Jakarta, Java, and Bali. It can be implemented in a wide area in Indonesia. For further research, the proposed model can be used in a wide area in Indonesia and developed for a more comprehensive recommendation system. © 2022 IEEE.
ABSTRACT
Although Covid-19 cases are continuing to decrease, the practice of online learning has become common in education. Many education institutions have online classes besides face-to-face classes. However, many research reported several problems in distance learning practice mainly because of the limitation of interactive conversation and learning activities and finally lead to an ineffective knowledge creation process. It is reported that in a distance learning setting during the pandemic, the motivation and participation rate decreased while the absence and dropout rates increased. Knowledge conversion is a term to reflect the acquisition of new know-how or tacit knowledge from the learning activities. Currently, various technology vendor keeps making innovations to solve this problem, and available technologies that can be utilized to support distance learning education are increasing. Therefore, this paper aims to know the impact of the knowledge creation process on student satisfaction and explain how to utilize technologies throughout the knowledge creation chain. Based on the statistical analysis it is found that the knowledge creation process that is represented using the SECI model simultaneously has a significant positive effect on student satisfaction. This means all phases in SECI (socialization, externalization, combination, and internalization) are simultaneously able to improve student satisfaction. However, partially, only socialization and internalization that has a significant positive impact on student satisfaction, which indicates these two factors partially could lead to better student satisfaction if it is planned and managed appropriately. This paper also constructs a matrix that helps education practitioners choose the right technology for each knowledge creation phase. © 2022 IEEE.
ABSTRACT
The Policy of PPKM Covid from the government has become a popular topic to be discussed among the public, especially on Twitter. Due to the many responses or opinions about the PPKM that has been implemented by the government in Indonesia. Sentiment Analysis is the basis for research on the issue of Indonesian PPKM by using a deep learning model, namely LSTM. The data collection of tweets is obtained through crawling the data of Twitter API using the 'snscrape' module with the keyword 'PPKM COVID' and the target data is 15,001 tweets. The data is processed and divided into two parts become 80% training data, 20% testing data and using the GRU, BiLSTM and RNN comparison models. Accuracy performance obtained from the four models include LSTM 90%, GRU 89%, BiLSTM 90% and RNN 85%. The comparison of the best accuracy results is obtained from the LSTM and BilSTM models. Furthermore, the result of sentiment obtained a high percentage for negative sentiment with a total percentage of 54.6%, while the positive sentiment had a percentage of 37.0% and neutral sentiment is 8.5%. © 2022 IEEE.
ABSTRACT
INTRODUCTION Acute kidney injury (AKI) is one of the severe complications of COVID-19. The two distinct medical conditions sharing similar comorbidities are diabetes and hypertension. However, the correlation between AKI and COVID-19 patients with diabetes and/or hypertension, has not been extensively discussed. This study aims to assess the risk factors of AKI induced by COVID-19, using a meta-analysis approach. METHODS A meta-analysis was carried out by reviewing the latest relevant studies on online databases such as PubMed, Google Scholar and Medline, up to 21 March 2022. The required information related to hypertension and diabetes as the potential risk factors of AKI induced by COVID-19, was extracted. The association was analyzed using pooled odds ratio (OR) and a 95% confidence interval (95% CI). RESULTS We analyzed 29 studies consisting of 10698 AKI patients with COVID-19 and 20917 controls. Our results show that patients with diabetes test)=0.0001, pE (Egger test)=0.8074) and hypertension (OR=1.7921;95% develop AKI when infected with COVID-19. CONCLUSIONS Diabetes and hypertension are prominent risk factors of acute kidney injury induced by COVID-19.
ABSTRACT
The pandemic Covid-19 outbreak has caused fundamental changes in various sectors of life and especially in organizations. As Increasing employee motivation in serving the public is important for public organizations, this study aims to analyze how job burnout and engagement could affect public service motivation among civil servants in Bandung, West Java, Indonesia. The sample in this study was employees who worked in public organizations in Bandung Raya, West Java Province, Indonesia. By using a purposive sampling technique, about 73 civils who are willing to become respondents and participate in the research. The results reveal that all hypotheses proposed in the study can be confirmed. An important finding from this study is the mediating role of job engagement on the effect of job burnout on public service motivation. Although job burnout can directly reduce job engagement and public services motivation, if public organizations can manage job engagement better, they will be able to increase public services motivation even more. The development of relationships between concepts and patterns that apply in context and other research designs is highly recommended to uncover interesting things that may not have been found in this study. Recommendations for further research are to expand the scope of the research object, in addition to re-examining the validity of the model, it is also expected to reveal other things that are important information for policymakers and leaders in public sector organizations. © 2023, Association Res Militaris. All rights reserved.
ABSTRACT
Background: Coronavirus 2019 (COVID-19) is a global pandemic with various clinical manifestations and is affected by multifactor. Epidemiological data of COVID-19 in Indonesia, especially in Surabaya have not been well established yet. Purpose: This study aims to provide the COVID-19 patients profile in Surabaya City, Indonesia. Method: The study data were retrospectively collected from electrical medical records in Primasatya Husada Citra (PHC) Hospital of Surabaya, one of the referral hospitals for COVID-19 in Surabaya. Descriptive and Spearman correlation statistics were done for data analysis.
ABSTRACT
Due to Covid-19, body temperature measurement is mandatory and become an important consideration in determining whether an individual is healthy or not. This paper presents the development of portable temperature and air quality detector to prevent suspect of Covid-19 with the main symptom is the body of temperature above 38° Celsius. We propose an algorithm and architecture used for temperature detector with maximum distance 80cm and CO2 and Volatile Organic Compounds (VOC) measurement are as indicator of good air quality. Based on experiment, we can detect temperature accurately until 0.3° Celsius using digital temperature sensor MLX90614 comparing with commercial one, furthermore the system able to give information about the quality of air, allowing/not allowing someone to enter a room with accuracy 92.5%. © 2021 IEEE.
ABSTRACT
Tourism products are not just a single business service but consist of complementary products, including tourism products, travel services, hotels, and attractions. Today tourism has become one of the biggest economic boosters for the Indonesian nation. To support this, good accommodation is needed to attract them to come to Indonesia. During this covid-19 pandemic, the tourism sector is in crisis. But now, this industry tried to recover. This situation is a momentum for the hotel to provide their best service and program. This study aims to evaluate online hotel booking to get the most influenced factor and recommend to the hotel. This study is quantitative research by using DeLone and McLean model to measure the factor. The result shows some factors affected customer satisfaction such as Information Quality and Service Quality, while customers' satisfaction does not impact service quality. The result will impact the strategy and recommendation for hotel industry to focus on important factors. © 2021 Little Lion Scientific
ABSTRACT
This study proposes a systematic approach to the construction of a simulation model to support decision-making concerning the capacity limit and staffing configurations at the paediatric eye clinic in Singapore under the COVID-19 pandemic situation. During the pandemic, the clinic must ensure that the operations are aligned to the safe-distancing regulations put in place by the Ministry of Health while coping with the demand. We developed simulation models to examine the 'as-is' process and proposed numerous 'to-be' processes for new clinic configurations to operate under the pandemic conditions. We combined scenario-thinking and simulation optimization to determine the additional manpower and physical resource requirements to enable the decision-makers at the clinic to better plan the necessary for continuous care to the young patients in a populated city, while coping with the healthcare demands during the pandemic. © 2021 IEEE.
ABSTRACT
In the midst of the Covid-19 pandemic and intense market competition, e-wallet players need to stop only relying on sales promotions to retain their users and start switching to a more sustainable strategy to produce Continuance Intention of gen X, Y, and Z consumers as the largest number of users. The purposes of this study are to determine whether there is any difference in Continuance Intention among gen X, Y, and Z consumers in using e-wallet, to prove the influence of antecedent variables toward Continuance Intention, and whether there are differences in those antecedent variables among gen X, Y, and Z consumers in using e-wallet. Research data obtained by distributing questionnaire to 200 respondents then analyzed using ANOVA, Multiple Linear Regression, and MANOVA. The results indicate that there is a difference on Continuance Intention among gen X, Y and Z;Perceived Value, Perceived Enjoyment, Personal Innovation, Switching Cost, and Habit simultaneously influence Continuance Intention;and specifically there are differences on Personal Innovation and Habit among gen X, Y, and Z. © 2021 IEEE.
ABSTRACT
COVID-19 has not only an impact on health aspects but also other issues, including the economy. At times of crisis that is full of challenges, individuals who prefer to compelled to do what needs to protected from the negativity caused by the disaster. One who managed to save himself in times of crisis caused a panic of buying that happens a lot in retail stores. Companies must study the efforts made by buyers related to panic buying that is happening around them. Companies can explore these insights through sentiments formed from social media user posts on social media platforms. This research explores consumer sentiment related to panic purchases using qualitative analysis with NVivo software. The results of a study of 647 posts on Twitter microblogging revealed that panic buying contained negative attitude. Based on the results of this analysis, there are tactical steps that can be taken by companies in supporting individual efforts to protect themselves from losses caused by the COVID-19 outbreak.