Abstract:ABSTRAKPenelitian ini berfokus pada bagaimana niqab (cadar) diwakili di media sosial oleh penggunanya (niqabis). Niqabis di Indonesia memiliki pertumbuhan yang signifikan dalam dua tahun terakhir, mereka juga mulai menunjukkan eksistensinya dalam masyarakat Indonesia yang heterogen. Di sisi lain, penerimaan publik terhadap niqab sangat beragam, ada yang menerimanya sebagai bentuk praktik keagamaan, tetapi banyak orang menolak niqab karena melihatnya sebagai praktik budaya belaka, sementara yang lain sangat men… Show more
“…The previous research from [4] described that from a historical perspective there are some negative opinions about hijab and veil as well as positive opinions. And from the other research [3], [6] some positive and neutral opinions just treat hijab and veil as the law from Qur'an and Hadith.…”
Section: Resultsmentioning
confidence: 98%
“…Veil (Cadar) user (niqabis) communities often used social media to introduce their community [3]. Along with the increasing popularity of its community, public opinion about veil is also increased.…”
Section: Introductionmentioning
confidence: 99%
“…Thus, make many people interest to research hijab or veil. Some studies about hijab or veil were discussed through religion and culture perspective [6], norm and historical perspective [4], its function [3], and so on. Therefore, the author conducting research about hijab and veil by analyzing the sentiment impact of twitter users' discussion.…”
Section: Introductionmentioning
confidence: 99%
“…As told in [4], after September 11 th , 2001 tragedy that demolishes WTC Building in America, the existence of hijab and veil was greatly rejected almost in all regions of Europe and America, they treat veil as the symbol of terrorists and radicals. And in [3], they said that niqabis use social media to show that women that wear veil can still be attractive and make their appearance more powerful and forming a strong character. These three studies show that there is a negative of positive public opinion regarding veil and hijab, which is why the author tries to analyze the sentiment impact of these two words from social media Twitter to know a new perspective.…”
Controversies about veil and hijab are often occur in society. Especially in today’s digital era, public opinion expressed through social media can greatly influence the others opinions, regardless of whether it is positive or negative. Therefore, this research was aiming to conduct an approach through analysis sentiment of public opinion about the veil and hijab to know how much accurate the sentiment analysis predict the positive, negative, or other sentiments with using Twitter data as the research object. The algorithm used in this study is Support Vector Machine (SVM) because of its fairly good classification model though it trained using small set of data. The SVM on this research was combined with Radial Base Function (RBF) kernel because of its numerical difficulties that are fewer than linear and polynomial kernel and also because this research doesn’t have a large feature. The amount of data used is 3556 tweets data. Tweets data, which is numbered 1056, is classified manually for the learning process. The remaining 2500 data will be classified automatically with the classifier model that has been created. A total of 1056 tweets data that have been classified manually is separated into training and testing data with a ratio of 8: 2. The result of the sentiment analysis process using Support Vector Machine algorithm RBF kernel with C=1 and γ=1 has an accuracy score of 73.6% with precision to negative opinions are 62%, positive opinions are 83%, neutral opinions reach 53% and irrelevant opinions that talk about hijab and veil reach 98%. It shows that sentiment analysis can be used for predicting the negative, positive or other sentiments of a sentence based on a certain topic, in this case veil and hijab.
“…The previous research from [4] described that from a historical perspective there are some negative opinions about hijab and veil as well as positive opinions. And from the other research [3], [6] some positive and neutral opinions just treat hijab and veil as the law from Qur'an and Hadith.…”
Section: Resultsmentioning
confidence: 98%
“…Veil (Cadar) user (niqabis) communities often used social media to introduce their community [3]. Along with the increasing popularity of its community, public opinion about veil is also increased.…”
Section: Introductionmentioning
confidence: 99%
“…Thus, make many people interest to research hijab or veil. Some studies about hijab or veil were discussed through religion and culture perspective [6], norm and historical perspective [4], its function [3], and so on. Therefore, the author conducting research about hijab and veil by analyzing the sentiment impact of twitter users' discussion.…”
Section: Introductionmentioning
confidence: 99%
“…As told in [4], after September 11 th , 2001 tragedy that demolishes WTC Building in America, the existence of hijab and veil was greatly rejected almost in all regions of Europe and America, they treat veil as the symbol of terrorists and radicals. And in [3], they said that niqabis use social media to show that women that wear veil can still be attractive and make their appearance more powerful and forming a strong character. These three studies show that there is a negative of positive public opinion regarding veil and hijab, which is why the author tries to analyze the sentiment impact of these two words from social media Twitter to know a new perspective.…”
Controversies about veil and hijab are often occur in society. Especially in today’s digital era, public opinion expressed through social media can greatly influence the others opinions, regardless of whether it is positive or negative. Therefore, this research was aiming to conduct an approach through analysis sentiment of public opinion about the veil and hijab to know how much accurate the sentiment analysis predict the positive, negative, or other sentiments with using Twitter data as the research object. The algorithm used in this study is Support Vector Machine (SVM) because of its fairly good classification model though it trained using small set of data. The SVM on this research was combined with Radial Base Function (RBF) kernel because of its numerical difficulties that are fewer than linear and polynomial kernel and also because this research doesn’t have a large feature. The amount of data used is 3556 tweets data. Tweets data, which is numbered 1056, is classified manually for the learning process. The remaining 2500 data will be classified automatically with the classifier model that has been created. A total of 1056 tweets data that have been classified manually is separated into training and testing data with a ratio of 8: 2. The result of the sentiment analysis process using Support Vector Machine algorithm RBF kernel with C=1 and γ=1 has an accuracy score of 73.6% with precision to negative opinions are 62%, positive opinions are 83%, neutral opinions reach 53% and irrelevant opinions that talk about hijab and veil reach 98%. It shows that sentiment analysis can be used for predicting the negative, positive or other sentiments of a sentence based on a certain topic, in this case veil and hijab.
“…Fenomena muslimah bercadar di Indonesia sudah ada sejak sepuluh tahun terakhir (Qibtiyah, 2019;Ramadhini, 2017;Ratri, 2011). Cadar sudah masuk pada trend fashion masa kini, dan perkembangan muslimah bercadar semakin terlihat di masyarakat (Dewi, 2019;Rasyid & Bukido, 2018;Sartika & Yusuf, 2020). Hal tersebut tercatat melalui penelitian yang dilakukan oleh Alvara Research Centre tahun 2015 yang menyatakan bahwa lebih dari 2% muslimah Indonesia mengenakan jilbab hingga menutupi wajahnya atau mengenakan cadar (Hasanuddin & Purwandi, 2017).…”
Nowdays the hijrah culture is becoming a trend. Not a few Muslim women who emigrated by wearing the veil as a face covering, but then it became a challenge for them when they get discrimination, which is linked to terrorism. The phenomenon of veiled Muslim women in Indonesia continues to increase until it has become a trendy outfit as evidenced by the number of veiled Muslim women who are increasingly open on Instagram in expressing themselves. This study uses a constructivist paradigm with qualitative methods and a phenomenological approach. The subject of the study is five Muslimah Instagram users. This study found that there was expressive self-disclosure with enlarged open areas (open self) and Islamic self-disclosure with enlarged hidden self areas. There are functions of expression, self validation, social control and relationship development experienced by veiled Muslim women, and there is no function of self clarification. This study concluded that Muslims on Instagram can influence the community in removing the negative stigma of muslims and giving direction to other muslims to stay open and not shut away from society.
<span id="docs-internal-guid-1f385a66-7fff-470b-1633-49ff7d86f4d0"><span>This study aims to describe the manifestation of piety constructed by women who are members of the Muslimah Ummahat Sholihah Community. Also, to analyze the level of their religious behavior. This research is a qualitative descriptive study that emphasizes field research. Researchers used observation techniques, interviews, questionnaires, and documentation to collect data. It turns out that the manifestation of women's piety is manifested by being obedient to the commands of Allah and His Messenger through the intermediary of teachers, covering their genitals and wearing the hijab, obeying their husbands, balancing ritual worship with social activities, and participating in religious activities. Meanwhile, the level of religious behavior of members of the Muslimah Ummahat Sholihah Community based on the results of the distribution of the questionnaire is categorized as high. Thus, the symbol of piety that they carry has absolutely nothing to do with conservatism, even radicalism, as some observers have alleged.</span></span>
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.