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dc.contributor.advisorZarlis, Muhammad
dc.contributor.advisorEfendi, Syahril
dc.contributor.advisorBudiman, Mohammad Andri
dc.contributor.authorSembiring, David Jumpa Malem
dc.date.accessioned2024-05-27T03:43:12Z
dc.date.available2024-05-27T03:43:12Z
dc.date.issued2023
dc.identifier.urihttps://repositori.usu.ac.id/handle/123456789/93428
dc.description.abstractAdvances in internet and communication technology underlie the growth of e-commerce, e-business applications and social media which are expected to contribute to increasing economic growth and community welfare, therefore the community needs to be involved in the development process through various technology initiatives to build services that focus on community needs. and provide better access to government services. Data has grown on a large scale and in various fields. Big data expressions are increasingly popular in the academic field, including research on awareness, adoption, and perceived usage in social media interactions. Big data can improve decision-making processes and increase organizational efficiency and effectiveness, but only if organizations use scientific methods to create knowledge about data. With the opportunity for the development of big data by utilizing social media, how to build a model to capture hot news as decision support in optimizing e-government. A new approach is proposed to identify the most popular news stories to identify hot topics accurately, which has four main parts, namely a method is proposed to identify new topics separated by word segmentation algorithms in news according to community service, utilization of time distribution of use of topics. identified topics to increase the IDF score, calculate the average weight for each hot news topic, offer a model for finding hot news or viral news related to government services in the community. So in this study, a model called DS TF IDF was produced in capturing patterns, trends, hot news which was developed by calculating the weight value of hot news about government services experienced by the community based on a certain period on social media platforms. As a comparison with other dimensions of social media, the average weight of hot news is calculated from a number of social media platforms and the attention used to regulate the distribution of time and distribution of public attention to the importance of developing news or information.en_US
dc.language.isoiden_US
dc.publisherUniversitas Sumatera Utaraen_US
dc.subjectBig data social mediaen_US
dc.subjectclassification and segmentation of news with time distributionen_US
dc.subjectSDGsen_US
dc.titleOptimasi Kinerja E Government melalui Data Media Sosial Berskala Besar (Big Data)en_US
dc.title.alternativeOptimization of E-Government Performance Through Large-Scale Social Media Data (Big Data)en_US
dc.typeThesisen_US
dc.identifier.nimNIM208123004
dc.identifier.nidnNIDN0010116706
dc.identifier.nidnNIDN0008107507
dc.identifier.kodeprodiKODEPRODI55001#Ilmu Komputer
dc.description.pages86 Pagesen_US
dc.description.typeDisertasi Doktoren_US


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