Social media is an application that can make everyone interact with each other and can consume information by sharing content quickly, efficiently and real time. Various kinds of information about someone's activities that we can find on social media, making social media can help to conduct investigations. Some research, using visualization with several graph methods to facilitate the process of analyzing data on social media that is so abundant. But the data used only comes from one social media, while there is still a lot of information on other social media that can be used as data sources for analysis purposes. In this study visualization using the directed graph method will be carried out, then calculate the value of network property and the value of centrality to find out which nodes have many activities which will be carried out in depth searches to find patterns of interaction or activity. Based on the results of the calculated centrality, it is found that on Twitter and Instagram accounts there are many interactions, this can be seen in the value of the indegree and outdegree node. Based on the results of the analysis in this study, information that is important for investigating social media is obtained, such as information about user profiles, posts, comments, preferred social media pages, location, and timestamp, all of which are connected by a line that shows the relationship between the node.

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Data is a collection of information that contains a broad picture related to a situation. The amount of data is not necessarily better, because a large data set makes it difficult to convert data into information in a timely manner, especially in analyzing data which produces meaningful and relevant information which ultimately results in quick and appropriate action. Higher education management in Indonesia requires fast and accurate academic reports so that it can facilitate strategic decision making in order to improve the quality of education. This study aims to carry out a comprehensive process of analyzing academic data at universities to display them into interactive data visualizations, so that they can retrieve the information in it and make strategic decisions. The method used is a data visualization technique, which allows users to easily see the insights or insights contained in the data. The results obtained are data that has passed the preprocessing stage, can prepare data before being analyzed and processed to be used to make data visualization, so that the information obtained is more varied. This information can be used as a reference by academic managers to make strategic decisions.