Analisis Sentimen Pengguna Twitter Terhadap Universitas Pamulang Periode Penerimaan Mahasiswa Gelombang I Tahun Ajaran 2024/2025
Keywords:
Universitas Pamulang, Analisis Sentimen, Orange, Naive BayesAbstract
The development of information technology has had a significant impact on various aspects of life, including education. One of the universities that has gained public attention is Universitas Pamulang. As one of the largest private higher education institutions in Indonesia, Universitas Pamulang needs to continuously improve. One of the key references for these improvements is public opinion. To understand public opinion regarding Universitas Pamulang, an analysis was conducted on the social media platform Twitter. Therefore, this study examines public sentiment toward Universitas Pamulang using Twitter data and the Naïve Bayes method. The Naïve Bayes method was chosen due to its advantages in text classification, particularly in sentiment analysis. The research data was collected from Twitter during the first wave of new student admissions for the 2024/2025 academic year. The analysis process involved identifying the dominant sentiment (positive, negative, or neutral) in public opinion, exploring the institution's strengths and weaknesses, and providing recommendations for improving the quality of academic services, administration, and the reputation of Universitas Pamulang. The results of this study indicate that the Naïve Bayes algorithm can be effectively used for sentiment analysis, achieving a high level of accuracy. This research is expected to contribute academically to sentiment analysis studies in the higher education sector in Indonesia.
References
[1] Rahardjo, B. (2021). Teknologi Informasi dan Transformasi Pendidikan di Era Digital. Jakarta: Pustaka Cendekia.
[2] Kumar, S., Roy, P. P., Dogra, D. P., & Kim, B. G. (2023). A Comprehensive Review on Sentiment Analysis: Tasks, Approaches and Applications. arXiv preprint arXiv:2311.11250. https://arxiv.org/abs/2311.11250
[3] Hasmadi, I., dkk. (2021). Analisis Sentimen terhadap Kualitas Layanan Driver Gojek di Aplikasi Play Store Menggunakan Algoritma Naive Bayes dan Aplikasi Orange. Jurnal Teknologi Informasi dan Komputer, 8(2), 45-52. Universitas Muhammadiyah Kalimantan Timur.
[4] Apriani, R., & Gustian, D. (2020). Analisis Sentimen dengan Naive Bayes terhadap Komentar Aplikasi Tokopedia. Jurnal Informatika dan Komputasi, 6(1), 32-39. Universitas Nusa Putra, Sukabumi.
[5] Assiva, M. A. (2022). Analisis Sentimen terhadap Pariwisata di Kabupaten Grobogan Berbasis Orange Menggunakan Naive Bayes. Jurnal Sistem Informasi dan Teknologi, 10(3), 56-63. Institut Teknologi dan Bisnis Muhammadiyah Grobogan.
[6] Zhai, C., & Massung, S. (2020). Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining. ACM Books.
[7] Cambria, E., Poria, S., Gelbukh, A., & Thelwall, M. (2020). Sentiment Analysis: What Else Beyond Opinion Mining? Cognitive Computation, 12(4), 847-881. https://doi.org/10.1007/s12559-020-09787-7.
[8] Norlaila, W. W., & Luthfi, E. T. (2024). Analisis Sentimen Masyarakat Tentang Tambang Di Indonesia Pada Twitter Menggunakan Data Mining. JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika), 9(3), 1091-1099. https://doi.org/10.29100/jipi.v9i3.5402:contentReference[oaicite:2]{index=2}.
[9] Munawaroh, A., Ridhoi, R., & Rudiman, R. (2024). Sentiment Analysis dengan Naïve Bayes Berbasis Orange Terhadap Resiko Pembangunan IKN. JATI (Jurnal Mahasiswa Teknik Informatika), 8(1), 587-590.
[10] Saptari, R. (2021). Analisis sentimen pengguna Twitter terhadap pelayanan unit gawat darurat rumah sakit umum di Indonesia menggunakan seleksi fitur Information Gain dan Support Vector Machine. Joined Journal (Journal of Informatics Education), 4(2), 104–110. https://doi.org/10.31331/joined.v4i2.1925.
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