Klasifikasi Interaksi Kampanye di Media Sosial Menggunakan Naïve Bayes Kernel Estimator

  • Aryo Nugroho Institut Teknologi Sepuluh Nopember
  • Rumaisah Hidayatillah Universitas Narotama
  • Surya Sumpeno Institut Teknologi Sepuluh Nopember
  • Mauridhi Hery Purnomo Institut Teknologi Sepuluh Nopember
Keywords: Pola Interaksi, Klasifikasi, Naive Bayes, Kernel Estimator

Abstract

The development of technology also influences changes in campaign patterns. Campaign activities are part of the process of Election of Regional Heads. The aim of the campaign is to mobilize public participation, which is carried out directly or through social media. Social media becomes a channel for interaction between candidates and their supporters. Interactions that occur during the campaign period can be one indicator of the success of the closeness between voters and candidates. This study aims to get the pattern of campaign interactions that occur on Twitter social media channels. This interaction pattern is classified as a model in measuring the success of campaigns on social media. The research begins with obtaining data through the data retrieval process using the API feature provided by Twitter. Furthermore, pre-processing is carried out before data can be processed in an algorithmic method. This stage is done to improve data quality so as to improve accuracy. Naive Bayes Classifier was chosen because of a simple procedure, then Kernel Estimator (KE) was used to improve performance. The use of naive Bayes Kernel Estimator can improve model performance from 76.74% to 80.14%. Testing models with split percentage methods on several combinations get satisfactory results.

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Published
2019-05-31
How to Cite
Aryo Nugroho, Rumaisah Hidayatillah, Surya Sumpeno, & Mauridhi Hery Purnomo. (2019). Klasifikasi Interaksi Kampanye di Media Sosial Menggunakan Naïve Bayes Kernel Estimator. Jurnal Nasional Teknik Elektro Dan Teknologi Informasi, 8(2), 107-114. Retrieved from https://dev.journal.ugm.ac.id/v3/JNTETI/article/view/2591
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Articles