Analyzing Sentiment of SiCepat Express User Reviews
Abstract
The development of e-commerce in Indonesia has led to an increase in the number of users of product delivery services to deliver their customers' orders to their destination. SiCepat Ekspres is the number one fastest delivery service in Indonesia, besides JNE and JNT Express. The study aims to evaluate the performance of sentiment analysis methods in identifying and classifying sentiments related to SiCepat Ekspres. Data from Twitter media as many as 10,000 dataset records. The experimental results show that Random Forest with SMOTE is the best method, as it has the highest accuracy (91.10%), followed by improvements in precision, recall, and F-measure. SVM with SMOTE is in second place, with 90.50% accuracy and stable performance in other metrics. Naive Bayes with SMOTE shows improvement, but its performance remains slightly below Random Forest and SVM, with an accuracy of 88.80%.
Downloads
References
Ika, N., Kalingara, P., Pratiwi, O. N., & Anggana, H. D. (2021). Analisis Sentimen Review Customer Terhadap Layanan Ekspedisi Jne Dan J & T Express Menggunakan Metode Naïve Bayes Sentiment Analysis Review Customer of Jne and J & T Express Expedition Services Using Naïve Bayes Method. 8(5), 9035–9048.
F. S. Jumeilah, "Klasifikasi Opini Masyarakat Terhadap Jasa Ekspedisi JNE dengan Naïve Bayes," Jurnal Sistem Informasi Bisnis, vol. 8, no. 1, pp. 92-98, Apr. 2018. https://doi.org/10.21456/vol8iss1pp92-98
Y. Marwanta and B. B, “Analisis Sentimen Pencitraan Perguruan Tinggi di Yogyakarta Menggunakan Metode Naїve Bayes Classifier”, JAIC, vol. 7, no. 1, pp. 21-27, Jul. 2023.
D. Vonega, A. Fadila, and D. Kurniawan, “Analisis Sentimen Twitter Terhadap Opini Publik Atas Isu Pencalonan Puan Maharani dalam PILPRES 2024”, JAIC, vol. 6, no. 2, pp. 129-135, Nov. 2022.
B. Ramadhan, R. Adam, and I. Maulana, “Analisis Sentimen Ulasan pada Aplikasi E-Commerce dengan Menggunakan Algoritma Naïve Bayes”, JAIC, vol. 6, no. 2, pp. 220-225, Dec. 2022.
Mahardika, Y. S., & Zuliarso, E. (2018). Analisis Sentimen Terhadap Pemerintahan Joko Widodo Pada Media Sosial Twitter Menggunakan Algoritma Naives Bayes. Prosiding SINTAK 2018, 2015, 409–413.
Salmaa. (2017). Teknik Pengumpulan Data: Pengertian, Jenis, dan Contoh. https://penerbitdeepublish.com/teknik-pengumpulan-data/
Slamet, C., Atmadja, A. R., Maylawati, D. S., Lestari, R. S., Darmalaksana, W., & Ramdhani, M. A. (2018). Recent citations Automated Text Summarization for Indonesian Article Using Vector Space Model. https://doi.org/10.1088/1757-899X/288/1/012037
Sugara, B. ; D. D. (2019). View of Pemanfaatan Sistem Temu Kembali Informasi dalam Pencarian Dokumen Menggunakan Metode Vector Space Model. http://jurnal.stiki.ac.id/J-INTECH/article/view/189/162
Zeniarja, J., Salam, A., & Achsanu, I. (2020). Sistem Koreksi Jawaban Esai Otomatis (E-Valuation) dengan Vector Space Model pada Computer Based Test (CBT). Seri Prosiding Seminar Nasional Dinamika Informatika, 4(1). http://prosiding.senadi.upy.ac.id/index.php/senadi/article/view/134
Lorosae, T. A., & Prakoso, B. D. (2018). Analisis Sentimen Berdasarkan Opini Masyarakat Pada Twitter Menggunakan Naïve Bayes. Seminar Nasional Teknologi Informasi Dan Multimedia 2018 Universitas Amikom Yogyakarta, 10 Februari 2018, 25–30.
S. Fauziah, D. N. Sulistyowati, and T. Asra, “Optimasi Algoritma Vector Space Model Dengan Algoritma K-Nearest Neighbour Pada Pencarian Judul Artikel Jurnal”, pilar, vol. 15, no. 1, pp. 21–26, Mar. 2019.2
Darmawan, A., Kustian, N., & Rahayu, W. (2018). Implementasi Data Mining Menggunakan Model SVM untuk Prediksi Kepuasan Pengunjung Taman Tabebuya. STRING (Satuan Tulisan Riset Dan Inovasi Teknologi), 2(3), 299. https://doi.org/10.30998/string.v2i3.2439
Insanudin, E. (2019). Implementation of python source code comparison results with Java using bubble sort method. Journal of Physics: Conference Series, 1280(3). https://doi.org/10.1088/1742-6596/1280/3/032027
Nitami, Mahardika Tania ; Februariyanti, H. (2022). Jurnal Manajemen Informatika nformatika & Sistem Informasi ( MISI ) i Jurnal Manajemen Informatika nformatika & Sistem Informasi ( MISI) ISSN : 2614-1701 ( Cetak ) – 2614-3739 ( Online ) ii. 5.
Song, J., Kim, K. T., Lee, B., Kim, S., & Youn, H. Y. (2017). A novel classification approach based on Naïve Bayes for Twitter sentiment analysis. KSII Transactions on Internet and Information Systems, 11(6), 2996–3011. https://doi.org/10.3837/tiis.2017.06.011
Widianto, M. H. (2019). Algoritma Naive Bayes | BINUS University Bandung - Kampus Teknologi Kreatif. https://binus.ac.id/bandung/2019/12/algoritma-naive-bayes/
Copyright (c) 2025 Endra Maulia Wicaksana, Nova Rijati
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) ) that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).