Implementasi Model Support Vector Machine Dalam Analisa Sentimen Masyarakat Mengenai Kebijakan Penerapan Aplikasi Mypertamina

Salsabila Dwi Fitri ; Dewi Lestari ; Rizqa Raaiqa Bintana ; Reni Aryani ; Mohamad Ilhami ; Yolla Noverina
Bridge : Jurnal Publikasi Sistem Informasi dan Tel... 📅 2024 Vol 2, No 2 🔗 DOI: 10.62951/bridge.v2i3.180
Abstract
The policy for using the MyPertamina application issued does not rule out the possibility of differences of opinion due to changes in the policy. There are many positive, neutral, and negative responses to the MyPertamina application implementation policy. To see the public's reaction to the MyPertamina application implementation policy, it can be seen through various media, including social media. Twitter is a social network that is widely used by people in Indonesia. The number of Twitter users in Indonesia reached 18.45 million in 2022, making Indonesia the fifth largest Twitter user country in the world. Researchers conducted a sentiment analysis of the search results for tweets containing the keyword "MyPertamina" using the support vector machine algorithm. 382 tweet data were obtained and classified using the support vector machine algorithm. Support vector machine is a supervised learning algorithm for data classification. SVM is very fast and effective in solving text data problems. Text data is suitable for classification with the SVM algorithm because the basic nature of text tends to be high-dimensional. Of the 382 data analyzed, the support vector machine classification using the RBF kernel with parameter C=2 gave the highest accuracy value of 80.51%, precision value of 81%, recall value of 81%, and F1 score value of 80%.
Keywords
classification; sentiment analysis; support vector machine; text mining
How to Cite

Salsabila Dwi Fitri, et al. (2024). Implementasi Model Support Vector Machine Dalam Analisa Sentimen Masyarakat Mengenai Kebijakan Penerapan Aplikasi Mypertamina. Bridge : Jurnal Publikasi Sistem Informasi dan Telekomunikasi, 2(2). https://doi.org/10.62951/bridge.v2i3.180

Salsabila Dwi Fitri; Dewi Lestari; Rizqa Raaiqa Bintana; Reni Aryani; Mohamad Ilhami; Yolla Noverina, "Implementasi Model Support Vector Machine Dalam Analisa Sentimen Masyarakat Mengenai Kebijakan Penerapan Aplikasi Mypertamina," Bridge : Jurnal Publikasi Sistem Informasi dan Telekomunikasi, vol. 2, no. 2, 2024.

Salsabila Dwi Fitri; Dewi Lestari; Rizqa Raaiqa Bintana; Reni Aryani; Mohamad Ilhami; Yolla Noverina. "Implementasi Model Support Vector Machine Dalam Analisa Sentimen Masyarakat Mengenai Kebijakan Penerapan Aplikasi Mypertamina." Bridge : Jurnal Publikasi Sistem Informasi dan Telekomunikasi, vol. 2, no. 2, 2024.

Salsabila Dwi Fitri; Dewi Lestari; Rizqa Raaiqa Bintana; Reni Aryani; Mohamad Ilhami; Yolla Noverina. "Implementasi Model Support Vector Machine Dalam Analisa Sentimen Masyarakat Mengenai Kebijakan Penerapan Aplikasi Mypertamina." Bridge : Jurnal Publikasi Sistem Informasi dan Telekomunikasi 2, no. 2 (2024).

Salsabila Dwi Fitri, et al. (2024) 'Implementasi Model Support Vector Machine Dalam Analisa Sentimen Masyarakat Mengenai Kebijakan Penerapan Aplikasi Mypertamina', Bridge : Jurnal Publikasi Sistem Informasi dan Telekomunikasi, 2(2). doi: 10.62951/bridge.v2i3.180.

Salsabila Dwi Fitri; Dewi Lestari; Rizqa Raaiqa Bintana; Reni Aryani; Mohamad Ilhami; Yolla Noverina. Implementasi Model Support Vector Machine Dalam Analisa Sentimen Masyarakat Mengenai Kebijakan Penerapan Aplikasi Mypertamina. Bridge : Jurnal Publikasi Sistem Informasi dan Telekomunikasi. 2024;2(2).

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