Analisis tren cyber attack pada media sosial twitter menggunakan k-means clustering

Yuslianto, Kevin (2022) Analisis tren cyber attack pada media sosial twitter menggunakan k-means clustering. Bachelor thesis, Universitas Pelita Harapan.

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Abstract

Information about cyber attacks can be found on social media such as Twitter. This information can be analyzed to determine trends in cyber attacks. Due to the large quantity of information on Twitter, manual analysis takes time and effort. To perform the analysis, a program was built using web scraping techniques and the K-Means Clustering algorithm. The program is able to perform web scraping with an average speed of 1300 tweets per second. The results of web scraping were analyzed using the program and produced three topics that could be determined as trends. Total of 161.115 tweet were obtained using this techniques. The data was taken in the time period between 1 September 2021 and 30 November 2021 with the tags cyberattack, cyberattacks, and cybernews./ Informasi mengenai serangan siber dapat ditemukan pada sosial media seperti Twitter. Informasi tersebut dapat dianalisis untuk menentukan tren serangan siber. Karena banyaknya kuantitas informasi pada Twitter, analisis secara manual membutuhkan waktu dan usaha. Untuk melakukan analisis, sebuah program dibangun dengan memanfaatkan teknik web scraping dan algoritme K-Means Clustering. Program tersebut dapat melakukan web scraping dengan kecepatan rata-rata 1300 tweet per detik. Hasil web scraping dianalisis menggunakan program dan menghasilkan tiga topik yang dapat ditentukan sebagai tren. Tweet yang didapatkan menggunakan web scraping adalah 161.115 tweet. Data tersebut diambil pada periode waktu 1 September 2021 - 30 November 2021 dengan tag “cyberattack”, “cyberattacks”, dan “cybernews”.

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