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All Journal snimed Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Prosiding SNATIF Sistemasi: Jurnal Sistem Informasi Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Abdimas Umtas : Jurnal Pengabdian kepada Masyarakat Jurnal Bumigora Information Technology (BITe) ABIDUMASY : Jurnal Pengabdian kepada Masyarakat Jurnal Computer Science and Information Technology (CoSciTech) J-Intech (Journal of Information and Technology) Jurnal Minfo Polgan (JMP) MATRIX : JURNAL MANAJEMEN TEKNOLOGI DAN INFORMATIKA Journal Of Information System And Artificial Intelligence Knowbase : International Journal of Knowledge in Database Bakti Sekawan : Jurnal Pengabdian Masyarakat Jurnal Masyarakat Madani Indonesia Journal Of Artificial Intelligence And Software Engineering Jurnal INFOTEL Jurnal Pengabdian Sosial Journal of Management, Entrepreneurship and Tourism JUAN: Jurnal Pengabdian Nusantara Jurnal Pengabdian kepada Masyarakat IPTEKS Jurnal Pengabdian Pada Masyarakat IPTEKS Prosiding Seminar Nasional CORISINDO
Neny Sulistianingsih
Bumigora University
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Journal : Jurnal Computer Science and Information Technology (CoSciTech)

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Visualisasi data twitter menjadi graph untuk social network analysis Galih Hendro Martono; Sulistianingsih, Neny
Computer Science and Information Technology Vol 4 No 3 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v4i3.5722

Abstract

Twitter is one of the most widely used social media in Indonesia. As a form of social media, Twitter is widely used to express opinions/opinions, discuss specific issues, convey complaints or sentiments about a product, and political communication. Twitter user communication data can be processed into useful information for various purposes, so we need a way to process Twitter data. The development of information technology makes it possible to multiply this information so that it becomes valuable information. For example, Twitter data can be helpful for companies to profile consumers so that they can improve marketing efforts. In the political field, Twitter data can be used to find people who influence Twitter who can be used to assist the campaign process. In the legal area, this Twitter data can help analyze networks and the distribution of information related to hate speech and hoaxes. To analyze Twitter data, we need to convert it into a data graph to be explored further. Twitter data visualization into data graphs is done because there are differences in data formats. Twitter data is in the form of string data consisting of tweets reflecting user communication. The data graph is a collection of vertices and edges, denoted as Vertex represents Twitter users, and Edge represents user relationships or communication. This study aims to form a data graph based on Twitter data to facilitate the analysis of Twitter data for various interests.
Co-Authors Agus Syahid Ahmad, Muhammad Maulana Alfian Nurlifa Christine Eirene christofer satria Dewi, Ni Putu Sinta Dian Syafitri Galih Hendro Martono Hairani Hairani Hasbullah Hasbullah Hasbullah Hasbullah I Nyoman Switrayana Irving Vitra Paputungan Kariyam - Khasnur Hidjah Lilik Widyawati Lukmana, Aldi Mayasari, Novyta Indah Muhammad Fathoni, Muhammad Muhid , Abdul Nafiani Nur Khamidah Ni Ketut Putri Nila Sudewi Ni Putu Sinta Dewi Noviansyah Noviansyah, Noviansyah Putradi, Angga Ria Rismayati Rismayanti, Ria Rismayati, Ria Rizki, M Setyawan, Ari Shofwan, Ari Sirojul Hadi Sri Kusumadewi Sutarman Sutarman Syahrir, Moch. Triwijoyo, Bambang Krismono Uswatun Hasanah Vira Megasari Haqni