ANALISIS SENTIMEN REVIEW APLIKASI STOCKBIT DI GOOGLE PLAY STORE DAN X(TWITTER) MENGGUNAKAN SUPPORT VECTOR MACHINE
SENTIMENT ANALYSIS OF STOCKBIT APPLICATION REVIEWS ON GOOGLE PLAY STORE AND X (TWITTER) USING SUPPORT VECTOR MACHINE
DOI:
https://doi.org/10.36341/rabit.v10i2.6446Keywords:
Sentiment, Stockbit, SVM, TF-IDF, Play Store, XAbstract
This study examines sentiment analysis of user reviews of the Stockbit application obtained from the Google Play Store and platform X (formerly Twitter). The aim of this research is to classify user opinions into two sentiment categories: positive and negative, using the Support Vector Machine (SVM) method. A total of 3,000 review data points were used in this study, consisting of 2,100 training data points and 900 test data points (stratified split with a 70:30 ratio) to ensure balanced sentiment distribution. The research process includes text preprocessing, feature weighting using Term Frequency-Inverse Document Frequency (TF-IDF), sentiment classification with the SVM algorithm, and model performance evaluation. Based on the evaluation results, the SVM model demonstrated high performance with an accuracy of 95.5%, precision of 93.5%, recall of 97.4%, and an F1-score of 95.3%. Although its accuracy is lower than that of Maulana et al.'s (2024) study, which achieved 99.50% on the Pluang application, this research excels in using data from two different platforms and evaluating class imbalance, making the analysis results more representative of real-world conditions. These findings indicate that SVM remains an effective method for text-based sentiment analysis in digital financial service applications.
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B. A. Maulana, M. J. Fahmi, A. M. Imran, and N. Hidayati, “Analisis Sentimen Terhadap Aplikasi Pluang Menggunakan Algoritma Naive Bayes dan Support Vector Machine (SVM),” MALCOM: Indonesian Journal of Machine Learning and Computer Science, vol. 4, no. 2, pp. 375–384, Feb. 2024, doi: 10.57152/malcom.v4i2.1206.
A. Kusuma and H. Nurramdhani Irmanda, “Analisis Sentimen Pada Ulasan Aplikasi Indodax di Google Play Store Menggunakan Metode Support Vector Machine,” 2022.
D. S. Putri, A. Sentimen, U. Aplikasi, and T. Ridwan, “Analisis Sentimen Ulasan Aplikasi Pospay dengan Algoritma Support Vector Machine,” 2023.
D. Toresa, S. Rico, F. Sitorus, I. Muzdalifah, F. Wiza, and R. Syelly, “Analisis Sentimen Terhadap Ulasan Penggunaan Dompet Digital DANA Mengunakan Metode Klasifikasi Support Vector Machine Sentiment Analysis of Reviews on the Use of DANA’s Digital Wallet Using the Support Vector Machine Classification Method,” vol. 3, no. 2, pp. 64–74, 2024.
S. Mujilahwati, “Analisis Sentimen Pengguna Aplikasi ChatGPT Berdasarkan Rating Menggunakan Metode Lexicon,” Rabit : Jurnal Teknologi dan Sistem Informasi Univrab, vol. 9, no. 1, pp. 131–137, Dec. 2023, doi: 10.36341/rabit.v9i1.3845.
Y. Afrillia, L. Rosnita, and D. Siska, “Analisis Sentimen Ciutan Twitter Terkait Penerapan Permendikbudristek Nomor 30 Tahun 2021 Menggunakan TextBlob dan Support Vector Machine,” G-Tech: Jurnal Teknologi Terapan, vol. 6, no. 2, pp. 387–394, Oct. 2022, doi: 10.33379/gtech.v6i2.1778.
A. A. Obos, A. Rahim, and A. Arbansyah, “Perbandingan Kinerja Metode Naïve Bayes dan Support Vector Machine untuk Analisis Sentimen Ulasan Pengguna Aplikasi Pintu,” Jurnal Informatika dan Teknik Elektro Terapan, vol. 13, no. 2, Apr. 2025, doi: 10.23960/jitet.v13i2.6220.
D. F. Setiawan, T. Tristiyanto, and A. Hijriani, “Aplikasi Web Scraping Ekstraksi Deskripsi Produk,” Jurnal Teknoinfo, vol. 14, no. 1, p. 41, Jan. 2020, doi: 10.33365/jti.v14i1.498.
A. A. Lutfi, A. E. Permanasari, and S. Fauziati, “Sentiment Analysis in the Sales Review of Indonesian Marketplace by Utilizing Support Vector Machine,” Journal of Information Systems Engineering and Business Intelligence, vol. 4, no. 1, p. 57, Apr. 2018, doi: 10.20473/jisebi.4.1.57-64.
R. W. ; F. S. H. ; D. A. D. I. ; A. Q. R. ; F. A. G. Pratiwi, “Analisis Sentimen Pada Review SkincareFemale DailyMenggunakan Metode Support Vector Machine(SVM),” 2021, doi: 10.20895/inista.v4i1.387.
Abd. C. Fauzan and K. Hikmah, “Implementasi Algoritma Naive Bayes dalam Analisis Polarisasi Opini Masyarakat Terkait Vaksin COVID-19,” Rabit : Jurnal Teknologi dan Sistem Informasi Univrab, vol. 7, no. 2, pp. 122–128, Jul. 2022, doi: 10.36341/rabit.v7i2.2403.
N. Nurdin, S. Fitriani, Z. Yunizar, and B. Bustami, “Clustering the Distribution of COVID-19 in Aceh Province Using the Fuzzy C-Means Algorithm,” JTAM (Jurnal Teori dan Aplikasi Matematika), vol. 6, no. 3, p. 665, Jul. 2022, doi: 10.31764/jtam.v6i3.8576.
N. Resti Wardani, S. Saepudin, and C. Warman, “Sentimen Analisis Kegiatan Trading Pada Ap-likasi Twitter dengan Algoritma SVM, KNN Dan Random Forrest,” 2022.
A. P. Natasuwarna, “Seleksi Fitur Support Vector Machine pada Analisis Sentimen Keberlanjutan Pembelajaran Daring Support Vector Machine Feature Selection on Online Learning Sustainability Sentiment Analysis,” 2020. doi: 10.33633/tc.v19i4.4044.
A. Agustin, S. Andrean, S. Susanti, R. Rahmiati, and H. Hamdani, “Review Aplikasi Kredivo Menggunakan Analisis Sentimen dengan Algoritma Support Vector Machine,” Rabit : Jurnal Teknologi dan Sistem Informasi Univrab, vol. 9, no. 1, pp. 39–49, Dec. 2023, doi: 10.36341/rabit.v9i1.4107.
J. Meiyazhagan, S. Sudharsan, A. Venkatasen, and M. Senthilvelan, “Prediction of Occurrence of Extreme Events using Machine Learning,” Oct. 2021, [Online]. Available: http://arxiv.org/abs/2110.09304
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