Analisis Sentimen Sistem Ganjil Genap di Tol Bekasi Menggunakan Algoritma Support Vector Machine

  • Heru Sukma Utama PASCA SARJANA STMIK NUSA MANDIRI
  • Didi Rosiyadi STMIK Nusa Mandiri Jakarta
  • Bobby Suryo Prakoso STMIK Nusa Mandiri Jakarta
  • Dedi Ariadarma LIPI
Keywords: analysis, odd, even, SVM, Text Mining, analisis, ganjil, genap, SVM, Text Mining

Abstract

Analysis of the odd even-numbered sentiment systems in Bekasi toll using the Support Vector Machine Algorithm, is a process of understanding, extracting, and processing textual data automatically from social media. The purpose of this study was to determine the level of accuracy, recall and precision of opinion mining generated using the Support Vector Machine algorithm to provide information community sentiment towards the effectiveness of the odd system of Bekasi tiolls on social media. The research method used in this study was to do text mining in comments-comments regarding posts regarding even odd oddities on Bekasi toll on Twitter, Instagram, Youtube and Facebook. The steps taken are starting from preprocessing, transformation, datamining and evaluation, followed by information gaon feature selection, select by weight and applying SVM Algorithm model. The results obtained from the study using the SVM model are obtained Confusion Matrix result, namely accuracyof 78.18%, Precision of 74.03%, and Sensitivity or Recall of 86.82%. Thus this study concludes that the use of Support Vector Machine Algorithms can analyze even odd sentiments on the Bekasi toll road.

 

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Published
2019-08-03
Section
Artikel Rekayasa Sistem Informasi