Analisis Sentimen Dalam Pemasaran Digital:Kajian Literatur

Agnes Irene Silitonga, Agnes Putri Farida Sitorus, Hafiz Irwandi, Ferry Indra Sakti H. Sinaga

Abstract


Pemasaran digital merupakan arah baru dalam pemasaran di seluruh dunia. Dengan memanfaatkan internet dan teknologi terbaru, pemasaran menjadi lebih kuat dan tepat sasaran. Untuk membantu bisnis digital mewujudkan pemasaran yang lebih efektif dan efisien, analisis sentimen hadir menjadi bagian dalam menganalisis opini konsumen yang dapat dimanfaatkan dalam realisasi personalisasi konsumen yang dapat membantu mewujudkan tujuan bisnis. Studi ini bertujuan untuk menjawab pertanyaan tentang bagaimana penggunaan analisis sentimen pada pemasaran digital dengan menggunakan kajian literatur. Dengan membandingkan penelitian-penelitian yang relevan, ditemukan bahwa analisis sentimen digunakan dalam sistem rekomendasi, deteksi polaritas konsumen, dan prediksi peringkat atau tren. Dengan menggunakan analisis sentimen, kegiatan pemasaran digital dapat berjalan lebih efektif, efisien, dan menyesuaikan preferensi konsumen.


Keywords


Analisis Sentimen, Pemasaran Digital, Kecerdasan Buatan, Pemrosesan Bahasa Alami

References


Abbasi-Moud, Z., Vahdat-Nejad, H., & Sadri, J. (2021). Tourism recommendation system based on semantic clustering and sentiment analysis. Expert Systems with Applications, 167, 114324. https://doi.org/10.1016/j.eswa.2020.114324

Akerkar, R. (2019). Artificial Intelligence for Business. SpringerBriefs in Business. https://doi.org/10.1007/978-3-319-97436-1_3

AL-Sharuee, M. T., Liu, F., & Pratama, M. (2021). Sentiment analysis: dynamic and temporal clustering of product reviews. Applied Intelligence, 51(1), 51–70. https://doi.org/10.1007/s10489-020-01668-6

Ameen, N., Baden-Fuller, C., Champion, R., Sharma, G. D., Dowsett, M., Jablokov, I., Lasmoles, O., Maiden, N., Pagani, M., Schulman, S. L., Sorin, N., Tarba, S. Y., & Wind, Y. (Jerry). (2024). Artificial Intelligence for Business Creativity. In M. Pagani & R. Champion (Eds.), Artificial Intelligence for Business Creativity. Routledge Focus on Business and Management. https://doi.org/10.4324/9781003287582

Beysolow, T. (2018). Applied Natural Language Processing with Python: Implementing Machine Learning and Deep Learning Algorithms for Natural Language Processing. In Applied Natural Language Processing with Python: Implementing Machine Learning and Deep Learning Algorithms for Natural Language Processing. https://doi.org/10.1007/978-1-4842-3733-5

Chaffey, D., & Ellis-Chadwick, F. (2024). Digital Marketing Strategy, Implementation and Practice. In Digital Marketing Technologies (6th ed.). Pearson Education Limited. https://doi.org/10.1007/978-981-97-0607-5_3

Ciocodeică, D.-F., Chivu, R.-G. (Popa), Popa, I.-C., Mihălcescu, H., Orzan, G., & Băjan, A. M. (Dumitrache). (2022). The Degree of Adoption of Business Intelligence in Romanian Companies—The Case of Sentiment Analysis as a Marketing Analytical Tool. Sustainability (Switzerland), 14(12), 1–20. https://doi.org/10.3390/su14127518

Eisenstein, J. (2018). Natural Language Processing. MIT Press. https://doi.org/10.4324/9780203103517-5

Gharzouli, M., Hamama, A. K., & Khattabi, Z. (2022). Topic-based sentiment analysis of hotel reviews. Current Issues in Tourism, 25(9), 1368–1375. https://doi.org/10.1080/13683500.2021.1940107

Goldfarb, A., & Tucker, C. (2019). Chapter 5 - Digital marketing. In Handbook of the Economics of Marketing, Volume 1 (Vol. 1, pp. 259–290). Elsevier B.V. https://doi.org/10.1016/bs.hem.2019.04.004

Golondrino, G. E. C., Alarcón, M. A. O., & Muñoz, W. Y. C. (2022). Proposal of an Automated Tool for the Application of Sentiment Analysis Techniques in the Context of Marketing. (IJACSA) International Journal of Advanced Computer Science and Applications, 13(3), 396–402. https://doi.org/10.14569/IJACSA.2022.0130348

Gooljar, V., Issa, T., Hardin-Ramanan, S., & Abu-Salih, B. (2024). Sentiment-based predictive models for online purchases in the era of marketing 5.0: a systematic review. Journal of Big Data, 11(107). https://doi.org/10.1186/s40537-024-00947-0

Haque-Fawzi, M. G., Iskandar, A. S., Erlangga, H., Nurjaya, & Sumarsi, D. (2022). STRATEGI PEMASARAN Konsep, Teori dan Implementasi. In Pascal Books. Pascal Books. http://repository.ibs.ac.id/id/eprint/4973

Hemanth, D. J. (2024). Computational Intelligence Methods for Sentiment Analysis in Natural Language Processing Applications. In Computational Intelligence Methods for Sentiment Analysis in Natural Language Processing Applications. Morgan Kaufmann. https://doi.org/10.1016/C2022-0-02821-X

Kamsinah, & Miftahkhus Surur. (2024). Perspective on Digital Marketing Toward Purchase Intention: A Sentiment Analysis. El-Mal: Jurnal Kajian Ekonomi & Bisnis Islam, 5(8), 3483–3496. https://doi.org/10.47467/elmal.v5i8.2693

Karthik, R. V., & Ganapathy, S. (2021). A fuzzy recommendation system for predicting the customers interests using sentiment analysis and ontology in e-commerce. Applied Soft Computing, 108, 107396. https://doi.org/10.1016/j.asoc.2021.107396




DOI: https://doi.org/10.30998/semnasristek.v10i1.8879

Refbacks

  • There are currently no refbacks.


Prosiding SEMNAS RISTEK indexed by: