scholarly journals Vaccine hesitancy in East Malaysia (Sabah): A survey of the national COVID-19 immunisation programme

2022 ◽  
Vol 17 (s1) ◽  
Author(s):  
Adi Jafar ◽  
Mohammad Tahir Mapa ◽  
Nordin Sakke ◽  
Ramli Dollah ◽  
Eko Prayitno Joko ◽  
...  
Keyword(s):  
Social Media ◽  
Principal Component Analysis ◽  
Principal Component ◽  
Immunisation Programme ◽  
Vaccine Hesitancy ◽  
Survey Method ◽  
Mainstream Media ◽  
The People ◽  
East Malaysia ◽  
Key Variables

The Malaysian government has introduced the National COVID-19 Immunisation Programme (PICK) as a new mechanism to address the transmission of coronavirus disease 2019 (COVID-19). Unfortunately, the number of PICK registrations is still unsatisfactory and is now even lower. The low level of participation of the Sabah (East Malaysia) population significantly impacts the PICK registrations. Therefore, this study aims to identify the factors that cause vaccine hesitancy among the people of Sabah. This study seeks to identify these trends based on zone and district boundaries. A total of 1024 respondents were sampled in this study. Raw data collected through the survey method were analysed using K-means clustering, principal component analysis (PCA), and spatial analysis. The study discovered that factors including confidence, authority, mainstream media, complacency, social media, and convenience are the top causes of vaccine hesitancy among respondents. This study also revealed that the Sabah population’s key variables causing vaccine hesitancy to vary by region (zones and districts). The conclusion is significant as a source of supporting data for stakeholders seeking to identify the Sabah population’s constraints in each region and therefore, it would help improve PICK management’s performance in Sabah.

scholarly journals POTRET KESEJAHTERAAN RAKYAT DI PROVINSI BALI MENGGUNAKAN METODE CHERNOFF FACES

2013 ◽  
Vol 2 (3) ◽  
pp. 1
Author(s):  
I WAYAN WIDHI DIRGANTARA ◽  
KOMANG GDE SUKARSA ◽  
KOMANG DHARMAWAN
Keyword(s):  
Principal Component Analysis ◽  
Graphical Method ◽  
Principal Component ◽  
Component Analysis ◽  
Facial Features ◽  
The People ◽  
Visualization Techniques

Chernoff Faces method is a graphical method of visualization techniques to present data with many variables in the form of a cartoon face which can be determined by 20 parameters or less. In this research it was shown how the Chernoff Faces method was used to see welfare of the people in the province of Bali and Bali's nine regencies. To pair the variables and Chernoff’s facial features, then we used  Principal Component Analysis and survey to make the faces look more human. The result from 18 indicators of welfare of the people in the province of Bali, only 8 indicators were not really well. It was obtained too that Tabanan was the most prosperous regency and Karangasem was the lest prosperous regency.

A Cross-Cultural Perspective on Motives and Patterns of Brand Recommendation in Social Media

2018 ◽  
Vol 8 (2) ◽  
pp. 27-44 ◽  
Author(s):  
Castulus Kolo ◽  
Stefan Widenhorn ◽  
Anna-Lena Borgstedt ◽  
David Eicher
Keyword(s):  
Social Media ◽  
Principal Component Analysis ◽  
Cultural Differences ◽  
Formal Education ◽  
Principal Component ◽  
Cross Cultural ◽  
Substantial Influence ◽  
Cultural Perspective ◽  
The Us ◽  
Do So

This article describes how today, social media enable users to comment on brands in a multitude of ways. Although it is undoubted that this can have a substantial influence on the way brands impact on consumers, comparatively little is known about what motivates consumers to recommend brands in social media and whether there are cultural differences therein. This article aims to determine the factors leading to either positive or negative communication about brands on Facebook, YouTube, Twitter, and brand-related blogs based on a representative sample from Germany and the US, each with 1,000 adults. Complementary to an analysis of factors determining a general inclination to recommend, a principal component analysis of the diverse motives to do so exhibits patterns being largely consistent in a cross-cultural perspective, however, with differences in specific practices concerning gender, age, and formal education. A cluster analysis as well as taking a look at “influencers” provide a basis for developing differentiated strategies of brand communication and management respectively.

A Cross-Cultural Perspective on Motives and Patterns of Brand Recommendation in Social Media

2019 ◽  
pp. 388-406
Author(s):  
Castulus Kolo ◽  
Stefan Widenhorn ◽  
Anna-Lena Borgstedt ◽  
David Eicher
Keyword(s):  
Social Media ◽  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Cultural Differences ◽  
Formal Education ◽  
Principal Component ◽  
Cross Cultural ◽  
Substantial Influence ◽  
Cultural Perspective ◽  
The Us

This article describes how today, social media enable users to comment on brands in a multitude of ways. Although it is undoubted that this can have a substantial influence on the way brands impact on consumers, comparatively little is known about what motivates consumers to recommend brands in social media and whether there are cultural differences therein. This article aims to determine the factors leading to either positive or negative communication about brands on Facebook, YouTube, Twitter, and brand-related blogs based on a representative sample from Germany and the US, each with 1,000 adults. Complementary to an analysis of factors determining a general inclination to recommend, a principal component analysis of the diverse motives to do so exhibits patterns being largely consistent in a cross-cultural perspective, however, with differences in specific practices concerning gender, age, and formal education. A cluster analysis as well as taking a look at “influencers” provide a basis for developing differentiated strategies of brand communication and management respectively.

Reconstructing Adulthood: Revising the Markers of Adulthood Scale for Increased Ecological Validity

2021 ◽  
pp. 003329412110617
Author(s):  
Kaley B. Norman ◽  
Jon E. Grahe ◽  
Seungyeon Lee
Keyword(s):  
Social Media ◽  
Principal Component Analysis ◽  
Statistical Analysis ◽  
Transition To Adulthood ◽  
Ecological Validity ◽  
Principal Component ◽  
Future Directions ◽  
Role Transitions ◽  
Demographic Survey ◽  
Best Fit

Young adults endorse more individualistic and internal adulthood milestones compared to prior generations. Arnett (1994) introduced the Markers of Adulthood (MoA) scale to capture this shift in the transition to adulthood using 38 markers associated with becoming an adult, including marriage, having children, and living independently. These items were based on psychological, anthropological, and sociological determinations concerning adulthood, and were arranged into subscales based on their theoretical association rather than statistical analysis. Since the scale was introduced, researchers have addressed crucial questions about the validity of the MoA scale’s milestones. A recurring theme was identifying items that could be sorted into reliable subscales. We examined a collection of original items and included new ones, such as “have a professional social media account” and “recognize personal capabilities and shortcomings” to configure a revised MoA model. A total of 861 participants in seven national locations responded to a demographic survey, the Inventory of the Dimensions of Emerging Adulthood (IDEA; Reifman, et al., 2007), and a collection of MoA items. We conducted a principal component analysis to identify 22 items and four factors (role transitions, independence, legality markers, and relative maturity) which represented 55% of the total variance in the dataset. All factors except legality markers were identified by prior researchers. While four factors demonstrated the best fit for subscale configurations, the revised MoA was considered most reliable when used in its entirety. Our examination ends with a discussion of future directions for configuring items which may produce reliable subscales.

Application of a very detailed soil survey method in viticultural zoning in Catalonia, Spain

OENO One ◽  
2009 ◽  
Vol 43 (2) ◽  
pp. 55 ◽  
Author(s):  
Josep Miquel Ubalde ◽  
Xavier Sort ◽  
Rosa Maria Poch
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Clustering Analysis ◽  
Survey Methodology ◽  
Principal Component ◽  
Soil Survey ◽  
Survey Method ◽  
Soil Maps ◽  
Soil Taxonomy ◽  
Soil Map

<p style="text-align: justify;"><strong>Aims</strong>: The aim of this study was to implement a very detailed soil survey methodology in 1,243 ha of vineyards in Catalonia (Spain) and analyse its suitability for viticultural zoning.</p><p style="text-align: justify;"><strong>Methods and results</strong>: The Soil Taxonomy at series level was used as the basis for classifying soils and delineating soil map units at 1:5,000 scale. A principal component analysis showed that most of the variability of soil properties, which was explained by factors related to water stress, iron chlorosis and vegetative growth, was not reflected exactly in the soil map unit classification. A k-means clustering analysis was proposed in order to group soils according to their potential for vine growing.</p><p style="text-align: justify;"><strong>Conclusion</strong>: A very detailed soil survey method, based on Soil Taxonomy, could be used as a basic map for viticultural zoning, when was directed at the differentiation of zones of distinct suitability for vineyard growing, by means of cluster analysis.</p><p style="text-align: justify;"><strong>Significance and impact of study</strong>: This study showed how very detailed soil maps, which can be difficult to interpret and put into practice, can be valorised as viticultural zoning maps by means of a simple methodology.</p>

scholarly journals Twitter Based Digital Social Movement Pattern to Fight COVID-19

2021 ◽  
Vol 25 (2) ◽  
pp. 95
Author(s):  
Mohammad Thoriq Bahri ◽  
Derajad Sulistyo Widhyharto
Keyword(s):  
Social Media ◽  
Social Movement ◽  
Movement Pattern ◽  
Point Of View ◽  
Mainstream Media ◽  
The People ◽  
Political Boundaries ◽  
Social Media Platforms ◽  
The Government ◽  
Ordinary Person

Twitter has become a tool for people to trigger a social change, like what is happening right now during COVID-19 outbreaks. Most people are using social media platforms to express their perspectives. For the first time, this research aimed to analyze the pattern of a social movement that happened during COVID-19 Outbreaks by analyzing the Twitter dataset contains 23,476 tweets worldwide with the #COVID19 hashtag which was obtained from 02 March to 09 April 2020. Social Network Analysis tools are used to understand the pattern of movement. This research concluded that if the Government and Mainstream Media Twitter account triggered the conversation in the social media platform, followed by the activists and celebrities who engage in conversation between their followers, an ordinary person spread the point of view of the Government and Mainstream Media across their conversation network. The COVID-19 hashtag successfully engaged 10 protest clusters, which pushed the people to fight against COVID-19 in their countries, mostly targeting the government-related account. The digital social movement pattern is relatively different from the traditional social movement, even it has the same steps, which emerge, coalesce, bureaucratise, and the movement itself, but it takes place in the Digital Public Sphere without any social or political boundaries. The digital social movement forced the government to implement a better policy to fight the COVID-19 Pandemic, including to close the national border to prevent unnecessary effects of International Migration.

scholarly journals STRATEGI PENGEMBANGAN MODEL PEMASARAN BERAS ORGANIK BERBASIS CONSUMER’S MARKET DI KABUPATEN BANYUMAS

2017 ◽  
Vol 13 (1) ◽  
pp. 1
Author(s):  
Amy Hartati ◽  
Dindy Darmawati Putri
Keyword(s):  
Principal Component Analysis ◽  
Qualitative Analysis ◽  
Principal Component ◽  
Complete Information ◽  
Survey Method ◽  
Factors Affecting ◽  
Organic Rice ◽  
Physical Chemical ◽  
Biological Characters ◽  
Farmer Groups

At  present,  many  farmer  groups  at  Banyumas  Regency  are  cultivating organic  rice.  Their  activities  are  very  progressive.  They  distribute  at  Baturraden, Sumbang,  Kedungbanteng,  and  Pekuncen.  The  activities  are  closed  relation  in  the market.  There  is  trend  in  moving  from  seller’s  merket  to  consumer’s  market.  The market  is  not  determined  by  middle  trader,  but  end  product   consumer  (consumers driven).  In  the  case,  consumer’s  require  complete  information  about  physical, chemical  and  biological  characters  of  product.  Therefore,  producers  must  enclose liable information on labels. The goals of  research were to analyze farming activity of organic rice, and study on consume’s preferences. Survey method was used, followed descriptive-qualitative analysis, and principal component analysis (PCA) for finding out  factors  affecting  consumers  in  buying  organic  rice  and  consuming  the  products based on profile and character of consumers. The research showed that (1) organic rice  cultivation  was  profitable;  (2)  Attributes  of  organic  rice  consisting  of  price,flavor,  availability,  and  guarantee  of  product  are  important;  (3)  Consumers  are satisfied to the organic rice producer’s perfomance in determining price and flavor. We recommend to the producer for maintenance of quality (flavour), availability and guarantee of product.

scholarly journals Perancangan Perangkat Lunak Kompresi Citra Menggunakan Transformasi Wavelet dan PCA

2019 ◽  
Vol 3 (1) ◽  
pp. 1
Author(s):  
Andrian Andrian
Keyword(s):  
Image Processing ◽  
Principal Component Analysis ◽  
Digital Image ◽  
Wavelet Transformation ◽  
Principal Component ◽  
Transformation Method ◽  
File Size ◽  
Compression Technique ◽  
The People ◽  
Good Compression

<p>Now days, The most needed of digital images is influenced by the people will that want to take a part of moment life into digital image. The good digital image has the big filesize, so it will need more space memory to saving more images. There is technique in image processing to decrease file size that is compression. By combine wavelet transformation method and Principal Component Analysis in developing application can produce the good compression technique.</p>

scholarly journals Hate Speech Detection using Modified Principal Component Analysis and Enhanced Convolution Neural Network on Twitter Dataset

2021 ◽  
Author(s):  
Majed Alowaidi
Keyword(s):  
Neural Network ◽  
Social Media ◽  
Principal Component Analysis ◽  
Feature Extraction ◽  
Social Networking ◽  
Hate Speech ◽  
Principal Component ◽  
Extraction Process ◽  
Online Social Media ◽  
The Given

Abstract Online social media are increasingly catching people’s eye among users of the Internet. Services provided by social networking vendors like Twitter and Facebook are very attractive, with widespread proliferation among internet users. As a downside of their predominance in the domain of social networking, Twitter and Facebook are frequently pestered with the problem of handling offensive, threat, fake, hate words. One of the major problems, apparent in online social media, is the toxic online content. In the existing system, the methods are not dealt with large dataset. Also the feature extraction method is not efficient to extract important features in the given dataset. To overcome the above mentioned issues, in this work, Modified Principal Component Analysis (MPCA) and Enhanced Convolution Neural Network (ECNN) is proposed. Natural Language Processing (NLP) is implemented to build an automatic system through the inclusion of syntactic and semantic analysis. This work contains main phases are such as pre-processing, feature extraction and classification process. The pre-processing is done by using normalization method which is used to remove the white spaces, replace the consecutive exclamation and question marks, and eliminate stop words. These preprocessed features are taken into feature extraction process. MPCA algorithm is applied to perform feature extraction process. It uses set of correlated features and extracts more informative features for the given dataset. Then the classification algorithm is proposed to detect the hate speech or abusive languages. ECNN is proposed to classify hate and non-hate from the online content more accurately. It takes many inputs and generates output with minimum amount of time with higher accuracy for larger dataset. Thus, the result concludes that the proposed MPCA+ECNN algorithm provides higher accuracy, precision, recall and F-measure values rather than the existing methods.

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