Analysis of E-commerce User Tweet Sentiment Using the Naïve Bayes Classification Method
Analisis Sentimen Tweet Pengguna E-commerce Dengan Menggunakan Metode Klasifikasi Naïve Bayes
DOI:
https://doi.org/10.21070/ups.3750Keywords:
Sentiment Analysis, Naïve Bayes Classification, E-commerceAbstract
In the context of e-commerce using the Naïve Bayes classification method. The rapid growth of e-commerce has given rise to user-generated content that reflects different opinions and experiences. By using the Naïve Bayes algorithm, the aim of this research is to classify and understand the opinions contained in tweets. These emotions are classified into positive and negative categories. In this research, thoughts and feelings expressed by users through tweets are searched, read and classified using Naïve Bayes classification. In this research, researchers show how to effectively segment and classify e-commerce users' tweet opinions using the Naïve Bayes classification method. Analyzing user-generated content provides valuable insights into consumer information. From this average value, accuracy, precision and recall are produced. It can be concluded that the average accuracy, precision and recall of data is 92.00% for accurate data, 90.35% for correct data and 100% for recall data.
Downloads
References
Ayu, S., & Lahmi, A. (2020). Peran e-commerce terhadap perekonomian Indonesia selama pandemi Covid-19. Jurnal Kajian Manajemen Bisnis, 9(2), 114. https://doi.org/10.24036/jkmb.10994100
Wandani, A. (2021). Sentimen Analisis Pengguna Twitter pada Event Flash Sale Menggunakan Algoritma K-NN, Random Forest, dan Naive Bayes. In Jurnal Sains Komputer & Informatika (J-SAKTI (Vol. 5, Issue 2)
Bayhaqy, A., Sfenrianto, S., Nainggolan, K., & Kaburuan, E. R. (2018, July 2). Sentiment Analysis about e-commerce from Tweets Using Decision Tree, K-Nearest Neighbor, and Naïve Bayes. 2018 International Conference on Orange Technologies, ICOT 2018.
Sentimen Untuk Penilaian Pelayanan Situs Belanja Online Menggunakan Algoritma Naïve Bayes Muljono, A., Putri Artanti, D., Syukur, A., Prihandono, A., & Rosal Moses Setiadi, D. I. (2018). Konferensi Nasional Sistem Informasi 2018 STMIK Atma Luhur Pangkalpinang. http://twitter.com
Minfo Polgan, J., Melina Salsabila, S., Alim Murtopo, A., Fadhilah, N., Sentimen Pelanggan Toko Online Tokopedia Menggunakan Metode Naïve Bayes Classifier, A., Informatika, T., & YMI Tegal, S. (n.d.). Analisis Sentimen Pelanggan Tokopedia Menggunakan Metode Naïve Bayes Classifier. www.tokopedia.com
Nofitri, R., & Irawati, N. (2019). ANALISIS DATA HASIL KEUNTUNGAN MENGGUNAKAN SOFTWARE RapidMiner. JURTEKSI (Jurnal Teknologi Dan Sistem Informasi), 5(2), 199–204. https://doi.org/10.33330/jurteksi.v5i2.365
Webb, G. I. (2016). Naïve Bayes. In Encyclopedia of Machine Learning and Data Mining (pp. 1–2). Springer US. https://doi.org/10.1007/978-1-4899-7502-7_581-1
Gunawan, B., Sasty, H., #2, P., Esyudha, E., & #3, P. (2018). JEPIN (Jurnal Edukasi dan Penelitian Informatika) Sistem Analisis Sentimen pada Ulasan Produk Menggunakan Metode Naive Bayes. 4(2), 17–29. www.femaledaily.com
Widya Ningsih, E. (2019). Penerapan Algoritma Naïve Bayes Dalam Penentuan Kelayakan Penerima Kartu Jakarta Pintar Plus. https://doi.org/10.31294/jtk.v4i2
Komara, D. A., & Hadiapurwa, A. (2022). PUBLIS JOURNAL AUTOMATING Twitter DATA COLLECTION: A RapidMiner-BASED CRAWLING SOLUTION. 6. http://journal.umpo.ac.id/index.php/PUBLIS
Yan, K., Arisandi, D., & Tony, ). (n.d.). Jurnal Ilmu Komputer dan Sistem Informasi ANALISIS SENTIMEN KOMENTAR NETIZEN TWITTER TERHADAP KESEHATAN MENTAL MASYARAKAT INDONESIA.
Wongkar, M., & Angdresey, A. (2019, October 1). Sentiment Analysis Using Naïve Bayes Algorithm Of The Data Crawler: Twitter. Proceedings of 2019 4th International Conference on Informatics and Computing, ICIC 2019. https://doi.org/10.1109/ICIC47613.2019.8985884
Garbian Nugroho, D., Herry Chrisnanto, Y., Wahana Jurusan Informatika, A., & Matematika dan Ilmu Pengetahuan Alam Universitas Jenderal Achmad Yani Jalan Terusan Jenderal Sudirman, F. (n.d.). ANALISIS SENTIMEN PADA JASA OJEK ONLINE MENGGUNAKAN METODE NAÏVE BAYES.
Susana, H., & Suarna, N. (2022). PENERAPAN MODEL KLASIFIKASI METODE NAIVE BAYES TERHADAP PENGGUNAAN AKSES INTERNET Program Studi Teknik Informatika STMIK IKMI Cirebon Jl Perjuangan No 10B Kesambi Kota Cirebon 3) Program Studi Rekayasa Perangkat Lunak STMIK IKMI Cirebon Jl Perjuangan No 10B Kesambi Kota Cirebon 4) Program Studi Komputerisasi Akuntansi STMIK IKMI Cirebon Jl Perjuangan No 10B Kesambi Kota Cirebon. Jurnal Sistem Informasi Dan Teknologi Informasi), 4(1), 1–8.
Aditya, D., Mubarok, A., Kom, M., & Susanti, S. (2019). Analisis Sentimen Pada Media Sosial Twitter Menggunakan Metode Naïve Bayes Classifier (Studi Kasus: Komentar Publik Kepada Tri Indonesia). JURNAL INFORMATIKA, 6(1), 1–8. http://ejournal.bsi.ac.id/ejurnal/index.php/ji/article/view/-https://doi.org/10.1109/ICOT.2018.8705796
Downloads
Additional Files
Posted
License
Copyright (c) 2024 UMSIDA Preprints Server
This work is licensed under a Creative Commons Attribution 4.0 International License.
