During the Coronavirus pandemic, social media played an essential role in disseminating information online by utilizing various message frames and hashtags. Instagram is a popular social media worldwide that are used to spread various information. This study applied the social network analysis (SNA) approach as a theoretical framework and explored how the relationship between users on the Instagram platform related to Coronavirus outbreaks. Moreover, we also investigate how the relationship between users and their hashtags. SNA techniques were used for visualizing network models using an undirected graph, measuring network attributes, and centrality measures to find the most influential users in the network. A total of 10,403 posts based on #wabahcorona on Instagram from February 28, 2020, to May 18, 2020, were analyzed. Based on the analysis results, hashtags play an important role in this topic. Degree centrality measure as connectivity number shows that only two user accounts can make it into the list’s top ten. When using the Eigenvector centrality measure, there are no users in the top ten. The modularity measure detects 122 distinct communities that show the dense connection of nodes in the networks. Betweenness centrality measure shows that there are six related hashtags to COVID-19 pandemic out of ten hashtags. They are #wabahcorona, #covid19, #corona, #viruscorona, #dirumahaja, and #coronavirus and the four are Islamic related hashtags. The Islamic related hashtags are caused by the date of Ramadhan month.
The Police as law enforcers who authorize in terms of social protection are expected to do both the prevention and investigation efforts also the settlement of criminal cases that occurred in the society. This research can help police to identify the main actor faster and leads to solving crime-cases. The use of overall centrality is very helpful in determining the main actors from other centrality measures. The purpose of this research is to identify the central actor of crimes done by several people. Semantic Social Network Analysis is used to perform central actor identification using five centrality measurements, such as degree centrality, betweenness centrality, closeness centrality, eigenvector centrality, and overall centrality. As for the relationship between actors, this research used social relation such as friendship, colleague, family, date or lover, and acquaintances. The relationship between actors is measured by first four centrality measures then accumulated by overall centrality to determine the main actor. The result showed 80.39% accuracy from 102 criminal cases collected with at least 3 actors involved in each case.
Sistem informasi eksekutif merupakan salah satu sistem yang digunakan untuk menganalisa masalah yang ada dalam suatu organisasi, serta memfasilitasi kebutuhan informasi yang berkaitan dengan pemenuhan tujuan organisasi. Namun pada penggunaan SIE belum terdapat analisi kajian yang membahas mengenai tingkat kepuasan user terhadap sistem yang digunakan. Sehingga tujuan dari penelitian ini adalah untuk memberbaiki sistem yang ada serta meningkatkan kepuasan user terhadap sistem informasi. Penelitia ini menggunakan jenis penelitian deskriptif dengan jumlah populasi sebanyak 28 orang. Teknik sampling yang digunakan dalam penelitian ini adalah teknik teknik sampling jenuh, yakni menggunakan seluruh populasi sebagai sampel penelitian. Metode pengumpulan data dalam penelitian ini yang digunakan dalam penelitian ini yakni metode dilakukan dengan menggunakan metode User Experience Questionaire (UEQ), dengan tahapan pengumpulan data yang terdiri dari tahapan merancang konsep dan kajian pustaka, identifikasi masalah, pengumpulan data, analisis data dan menarik kesimpulan. Hasil dalam penelitian ini menunjukkan bahwa analisis hasil pengujian sistem informasi eksekutif dengan menggunakan metode User Experience Questionnaire memperoleh dua parameter yang dengan nilai Above Average yaitu stimulasi dan kebaruan, sehingga perlu dilakukan pengembangan penyegaran user interface terhadap sistem informasi eksekutif tersebut.
This research aims to analyze and describe the development of tourism in Maluku Province, Indonesia on Instagram. The data used in this study are hashtags from several excellent tourist attractions or tourist priorities set by the maluku province tourism office. The data is then processed using social network analysis to find the level of importance and connectedness of tourism hashtags with other hashtags used in image captions on Instagram posts. The results showed that there are nine hashtags that have an important role in the network because they have high values in the measurement of degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality. The hashtags are #maluku, #ambon, #natsepa, #pulauosi, #pulaubair, #beach, #repost, #indonesia, and #namalatu. Two of nine hashtags have a high betweenness centrality value, namely #natsepa that represent natsepa beach tourism and #namalatu that represents namalatu beach tourism. Both of these tours have a high value betweenness centrality with a different form of hashtags, namely #natsepa.id and #namalatu02. This research conducted using social network analysis degree measurements such as degree, betweeness, closeness, and eigenvector to analyze insight of tourism topics in Instagram. The result of this research can give insights to the tourism actors, especially in Maluku Province, of how the hashtags are connected and related. The relation of the hashtags can be used as social media marketing strategy.
This research was conducted to find the groups of elementary schools in the Special Capital Region of Jakarta, also known as DKI Jakarta. Elementary school data were selected because it is the first stage of formal education in Indonesia. This research used K-means clustering with the elbow method to determine optimal cluster numbers. The optimal cluster number is three with Cluster 2 having the most members, followed by Cluster 1 and Cluster 0. The data distribution of Cluster 2 shows that the second-most student body and public schools located in East and West Jakarta have an adequate student-to-teacher ratio based on Article 17 of Government Regulation 74, 2008.
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