Parent-Preschooler Kid?s Activities in the Time of COVID-19 Outbreak: an Autoethnography on Child?s Second

The present study reported a life experience of a teacher family in Indonesia with a 4-year-old daughter. The observation occurred from March 2020 to July 2021 during the COVID-19 pandemic. This stay-at-home moment became an opportunity to create more parent-kid preschooler bonding and interaction that could impact the developing children language. Indonesian is our family native language (L1);therefore, the exposure started earlier for the kids. However, as parent-kid interaction was enhanced during the pandemic, we boosted our kid English (L2) with a variety of Edu-home activities such as reading aloud, storytelling, role-playing, and watching YouTube-kid. Her language production was documented, and the progress was analyzed. The aim was to generate a more profound understanding of our roles as parents in scaffolding the acceleration of preschoolers' English development, especially in creating meaningful activities. Going through an autoethnography, we reflect on our practice to know how the family members played the role of a language catalyst and which activities were taken more into account.

Comparison of Texture Feature Extraction Method for COVID-19 Detection With Deep Learning

This paper describes research on texture feature extraction for COVID-19 detection. Fractal Dimension Texture Analysis (FDTA) and Gray Level Co-occurrence Matrix (GLCM) were used for feature extraction. A dense neural network is used for classification. Three classes were used for classification to classify Normal, COVID-19, and Other pneumonia. The data entered in the texture feature extraction is a chest x-ray (CXR) image that is grey scaled and resized into 400400 pixels. Performance analysis of the model uses a confusion matrix. The best performance feature extraction method for detecting COVID-19 is FDTA, with an accuracy testing of 62.5%. © 2022 IEEE.

Age Classification of Moviegoers Based on Facial Image Using Deep Learning

The number of moviegoers in Indonesia continues to rise year after year until 2019. However, due to the COVID-19 pandemic, most Indonesian cinemas were closed in early 2020. Moviegoers are increasingly turning to digital platforms to watch films. Based on the films shown, they can be divided into three categories: films for children, films for adolescents, and films for adults. A system that can automatically classify the faces of the audience based on their age category is required. Using Deep Learning, this study aims to classify the audience's age based on facial photos. The first stage involves collecting data from three datasets: All-Age-Face, FaceAge, and FGNET, which are then combined and relabeled based on age group. Preprocessing and hyperparameter testing were also performed. Finding the best learning rate and bottleneck layer is the goal of hyperparameter testing. The training process employs learning rete and the two best bottleneck layers with six models, namely MobileNet, MobileNetV2, VGG16, VGG19, Xception, and ResNet101V2. Global Average Pooling was added at the end of the layer in each model. The MobileNet model on two bottleneck layers yielded the best testing accuracy value of 85.44 percent in this study © 2022, Abba Suganda Girsang & Dewa Bagus Gde Khrisna Jayanta Nugraha;published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 License

The Content of Breast Milk and the Challenges Experienced by Breastfeeding Mothers during the COVID-19 pandemic: A Systematic Review

Introduction: Every postpartum mother is recommended to breastfeed her baby because breast milk is the main need of newborns. The COVID-19 pandemic has had an impact on life in various aspects, including on the breastfeeding mothers, especially if they suffer from COVID-19 infection. Aim: The study aims to provide comprehensive evidence regarding potential virus transmission and antibody transfer through breastmilk and the experiences of mothers related to breastfeeding during the COVID-19 pandemic. Methods: A systematic review was conducted following the PRISMA guidelines. The search strategy involved the use of keywords related to COVID-19 and breastfeeding in PubMed and Science Direct databases. Articles were selected according to inclusion and exclusion criteria. Results: Breastfeeding has been recommended to be continued during the pandemic due to the benefits associated with it and the absence of sufficient evidence for transmission of COVID-19 infection through breast milk. During the lockdown period, there was a change in breastfeeding patterns, although most mothers believed that breastfeeding should be continued. Anxiety and lack of support affected breastfeeding practices. Breastfeeding mothers reported a dilemmatic situation. They felt protected because of the lockdown policy but also struggled to get support from their social environment. The impact varied in terms of stopping breastfeeding practice altogether, breastfeeding irregularly, and even giving formula milk. Conclusion: Adherence to health protocols can reduce the risk of transmission of COVID-19 infection through breastfeeding from mother to baby. Support from the family and the environment is needed to ensure the continuity of breastfeeding practice. © 2022 Kurniawati et al.

English-Indonesian crisis translation: accuracy and adequacy of Covid-19 terms translated by three MT tools

This study focuses on one basic question: how accurate and adequate are the three MT tools, namely Google Translate, Bing and Systran, in generating Covid-19 terms? It measures mainly the accuracy and adequacy of Covid-19 terms translated by three popular MT tools between English and Indonesian. Data analysis is conducted manually through human evaluation toward translation products by using a translation rubric. The assessment includes several samples covering the level of words, sentences and paragraphs. All samples are purposively retrieved from the Coronavirus Corpus and are translated by using the three MT tools. Two raters are involved to analyze texts at sentence and paragraph levels. The raters are used to provide the credibility of translation texts analysis. Results showed that the three MT tools produce different language accuracy and adequacy in revealing COVID-19 terms. Translating noun and pronoun in particular context from English into Indonesian language still remains unclear. This may affect paragraph cohesion. Furthermore, even though these MT tools successfully translate a number of English words into Indonesian, several of the words cited are officially absent in the Great Indonesian Dictionary. This gap raises confusion for Indonesian readers whose English is not sufficient to understand the lexical meaning. In this case, the study highlights the importance of updating the words data base. As this article implements an evaluation translation method, the goal is to produce some recommendations that may be useful for several parties: reader of target language, MT's developer, linguist and government. © 2022 Minerva Obstetrics and Gynecology. All rights reserved.

The Effect of Service Quality and Brand Trust on Customer Loyalty during COVID-19 Pandemic: Moderating Effect of Customer Satisfaction

This research was conducted to detect how service quality and brand trust influence JNE customer loyalty in Karawang through customer satisfaction as an intervening variable. The research was carried out using descriptive and causal research types with a quantitative approach involving 400 respondents who used JNE services by taking samples through a non-probability sampling technique that was purposive sampling type, namely through determining specific criteria that were in line with the research objectives. The analytical method used in this research is path analysis, data analysis using the SmartPLS version 3.0 software. The results of the analysis show that service quality variables owns a great and substantial reaction on JNE customer satisfaction, brand trust owns a great and substantial reaction on customer loyalty, service quality owns a great and substantial reaction on customer satisfaction, customer satisfaction owns a great and substantial reaction on customer loyalty. © Kalahari Journals.

The influence of e-trust on e-customer loyalty of online food delivery customers in Indonesia (Study conducted during COVID-19 Pandemic)

GoFood is an online food delivery service on the Gojek application that leads the market share in Indonesia with transaction growth that exceeds transportation service transactions and has the highest brand identity, does not guarantee satisfaction to GoFood users. There are many complaints that consumers feel when using GoFood services, related to problems of trust in the service due to mismatches in customer expectations of GoFood services. This problem, if left unchecked, can affect customer satisfaction (e-customer satisfaction) so that it can reduce consumer loyalty (e-customer loyalty). This study aims to determine the effect of e-trust on e-customer loyalty through e-customer satisfaction on GoFood service users in Indonesia. This type of research is descriptive and causal with a quantitative approach. Sampling in this study using a non-probability sampling method with a purposive sampling type of 100 people. The analysis technique used in this research is Structural Equity Modeling (SEM) processed with SmartPLS software. The results of his research prove that e-trust does not have a positive and insignificant effect on e-customer loyalty, e-trust has a positive and significant effect on e-customer satisfaction, e-customer satisfaction has a positive and significant effect on e-customer loyalty, e-trust has a positive and significant effect on e-customer loyalty through e-customer satisfaction. © IEOM Society International.

The Utilisation of Uniform Backgrounds in Indonesia: Individual Cultural Factors and Perceived Benefits

As COVID-19 spreads, the Indonesian government urges workers to keep their distance and carry out activities at home, including studying from home and working from home whenever possible. Face-to-face or offline meetings such as teaching and learning processes, meetings, even national and international conferences that were originally held in person or offline have turned into online meetings. As time goes by, the use of online meeting technology creates a new behavior, which is a uniform background in online meeting activities. This phenomenon opens up the possibility to investigate the reason why they use background features during online meetings. Based on the previous literature, we hypothesised that in this phenomenon, the perceived benefits of changing the background based on the demand of the event organizer are driven by internal stimuli, in particular individualism and collectivism. We conducted a survey of 302 respondents and examined using the covariance-based Structural Equation Modeling (SEM). The results showed that the internal stimuli in particular individualism and collectivism factors had no effect on Perceived Economic Benefit (PEB) and Perceived Social Benefit (PSB) when using Virtual Background in online meetings. However, the Individualism and Collectivism factors had a positive influence on Perceived Hedonic Benefit (PHB) and had a negative influence on Perceived Altruistic Benefit (PAB) when using Virtual Background in online meeting activities. © 2021 ACM.

A Critical Discourse Analysis to Prevent the Second Wave of COVID-19 Pandemic in Indonesia

The government's choice of complicated language style in communicating issues or cases of Covid-19 risks bringing misunderstandings among the public. The choice of terms which are very elitist will only target certain circles. The government's communication strategy during this pandemic certainly creates new problems. One of the impacts arising from the government's elitist communication approach is the emergence of an information gap between the upper middle class and lower middle class which has a systemic impact, for example the panic buying phenomenon ahead of the implementation of the Social Restrictions Large-Scale (PSBB). In linguistics, an information (discourse) can be framed with topicalization techniques. This technique is a strategy for promoting information that will be highlighted. The part of the information that has a higher negative meaning burden tends to be not highlighted. The issue of the increase in positive cases of Covid-19 does not seem too prominent. © 2021. All Rights Reserved.

Covid-19 Outbreak in Social Media: Semiotics Analysis

Social interactions that occur in the middle The Covid-19 outbreak has to do with the media. The position of the media in the midst of the pandemic is as current information to the public. Media is seen as an important actor at the same time public discourse forums, hence the media social must perform a function as existence of the media. Media, in the middle of the situation Covid-19 is crucial and important for always running as, a channel of information, educate and also as well as social control elites and society. The COVID-19 outbreak which has hit various parts of the world, including in Indonesia has become the object of many research, especially semiotics. That matter is a medium of public expression in responding to the COVID-19 outbreak which is channeled on the internet both on various social media such as Instagram, Facebook, Twitter, TikTok, vlog, etc., as well as on personal blogs that can be accessed from Google. The sign can contain only pictures or images accompanied by speech in the form of text related to the COVID-19 outbreak.

'new normal' in covid-19 era: The textual analysis of jokowi's speech

In the critical discourse analysis, every discourse has three dimensions: It is a written or spoken language text;an interaction between people - which involves the process of production and interpretation of texts (practice of discourse);and is part of a practice or social act. The implication in critical discourse analyses is how this study raises the rules of language and linguistic practices that are implanted together with the relationship of a practice or social act that is often not realized by us so far. This study also criticizes the tendency of language studies to simply use linguistic rules and practices, as objects that are described, in a way that obscures their ideological and political inculcations. In this research, the authors examine the impact of the spread of the virus on the Indonesian economy, as well as the government's response to the public health crisis, as well as the efforts made to overcome the economic crisis that has arisen Covid -19 and 'new normal' based on the textual analysis of Jokowi's Speech. This research was conducted using a qualitative-descriptive type with critical discourse analysis approach. The data was taken from the Cabinet Secretariat of the Republic of Indonesia and online media (tempo). The results showed that online media consistently supported the application of the new normal to restore economic conditions. the Cabinet Secretariat of the Republic of Indonesia emphasizes its frame using sensational and eye-catching vocabulary. © 2021 Karadeniz Technical University. All rights reserved.

A current update in COVID-19 associated acute respiratory distress syndrome: Focus on mesenchymal stem cell therapy

Indonesia has been fighting the COVID-19 pandemic since the beginning of March 2020, and it doesn't look that the situation is getting better any soon. Besides the country's current strategies to minimize the rising mortality rate, a novel therapeutic intervention is required. After a thorough search in several databases, we found stem cells to be a likely candidate. Regardless of the general use of stem cells, studies showed positive results regarding the efficacy of using these in lung injuries. Especially, mesenchymal stem cells (MSCs) are known for their easy accessibility and their diverse mechanisms of action, including MSCs immunomodulatory antiviral effect, and its ability to improve lung function. Moreover, some researches perceived these components to be applicable in COVID-19 patients with end stage acute respiratory distress syndrome (ARDS). While randomized clinical trials are still in progress, many case reports show MSCs to be an advantageous alternative to suppress the cytokine storm and help regulate the immune system. This review summarizes the common functions of MSCs and highlights its therapeutic assets to fully tackle this global pandemic.

Electrical peak load clustering analysis using K-means algorithm and silhouette coefficient

Nowadays, data analysis widely used in many fields especially in engineering. Clustering is one of data analysis methods to organize the amount of data into groups with similarity characteristics. One powerful analysis method to learn information by grouping data is clustering algorithms. The clustering advantages for electrical power utilities is to learn load behavior and provide information for power plant operation and also generation cost. In this paper, a simulation concept is proposed for analysis of peak load data by K-means clustering algorithm based on historical dataset. The results show electrical peak loads clustering by K-means algorithm are optimum classified into three clusters. This cluster evaluated by silhouette scores which high, intermediate, and low load level interpretation. One cluster has centroid during January, June, and July are relatively lower than another cluster caused by Indonesia national holiday. This concept also evaluates the load level affected by Covid-19 pandemic condition. © 2020 IEEE.