Analisis Sentimen Pengguna Aplikasi Bukalapak di Platform Playstore Menggunakan Metode Naïve Bayes
Abstract
Indonesia, as a country with significant growth in internet users, recorded a 7.3% digital economy contribution to GDP in 2017, surpassing the overall economic growth of 5.1%. One of the main challenges is efficiency in managing user reviews to improve services, as done by Bukalapak app using data scraping to collect 5000 reviews. This study uses the Naïve Bayes algorithm to analyze the sentiment of Bukalapak app user reviews, focusing on identifying positive and negative sentiment patterns. The goal is to deepen the understanding of user perceptions of Bukalapak services and provide a basis for strategic decision-making in improving user experience and application services. The Naïve Bayes algorithm in this study achieved an accuracy rate of 67.9%, with 13.3% of reviews found to be positive and 86.7% of reviews negative. The analysis results highlight the importance of improvements in certain aspects of Bukalapak's services, which can lead to further development to increase user satisfaction. The majority of Bukalapak reviews indicate shortcomings or criticism of its services, which highlights the importance of improvement in certain aspects. The Naïve Bayes model provides a clear understanding of user sentiment, which is key in strategic decision-making and efforts to improve user experience on the Bukalapak platform. Thus, this research makes an important contribution in directing further improvement and development steps in enhancing Bukalapak app services as well as better understanding user perceptions.
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References
A. A. Tanjung, M. Syafii, S. B. Tarigan, and W. G. Harahap, “Analisis Pengaruh Ekonomi Digital Terhadap Pertumbuhan Ekonomi di Indonesia: Model Data Panel,” ekuitas, vol. 4, no. 2, pp. 567–575, Dec. 2022, doi: 10.47065/ekuitas.v4i2.2223.
E. M. Asih, “Analisis pada Shopee sebagai E-Commerce Terpopuler di Indonesia”, jeba, vol. 2, no. 1, pp. 73–79, Jun. 2024.
I. Verawati and S. N. Jaelani, “Analisis Sentimen Pengguna Twitter Terhadap Bus Listrik Menggunakan Naïve Bayes,”, MIB, vol. 8, no. 2, 2024, doi: 10.30865/mib.v8i2.7030.
D. S. Sayogo, B. Irawan, and A. Bahtiar, “ANALISIS SENTIMEN ULASAN BUKALAPAK DI GOOGLE PLAY STORE MENGGUNAKAN ALGORITMA NAÏVE BAYES,”, JNANALOKA, vol. 7, no. 6, 2023. doi: 10.36802/jnanaloka
I. Darmawan and O. Nurul Pratiwi, “ANALISIS SENTIMEN ULASAN PRODUK TOKO ONLINE RUBYLICIOUS UNTUK PENINGKATAN LAYANAN MENGGUNAKAN ALGORITMA NAIVE BAYES,”, vol. 7, no. 2, 2020. Availabel: https://openlibrarypublications.telkomuniversity.ac.id/index.php/engineering/article/view/12679
I. S. K. Idris, Y. A. Mustofa, and I. A. Salihi, “Analisis Sentimen Terhadap Penggunaan Aplikasi Shopee Mengunakan Algoritma Support Vector Machine (SVM),” JJEEE, vol. 5, no. 1, pp. 32–35, Jan. 2023, doi: 10.37905/jjeee.v5i1.16830.
Z. A. Nurdiyansah, “Sentiment Analysis of Reviews on Lazada Apps using Naïve Bayes Algorithm,” vol. 8, 2024, http://dx.doi.org/10.30865/mib.v8i1.7255.
I. Darmawan and O. Nurul Pratiwi, “ANALISIS SENTIMEN ULASAN PRODUK TOKO ONLINE RUBYLICIOUS UNTUK PENINGKATAN LAYANAN MENGGUNAKAN ALGORITMA NAIVE BAYES (BUKALAPAK),”, vol. 7, no. 2, 2020. Availabel: https://openlibrarypublications.telkomuniversity.ac.id/index.php/engineering/article/view/12679
D. Wijaya, R. A. Saputra, and F. Irwiensyah, “Analisis Sentimen Ulasan Aplikasi Samsat Digital Nasional Pada Google Playstore Menggunakan Algoritma Naïve Bayes”, KLIK, vol. 4, no.4, 2024, doi: https://doi.org/10.30865/klik.v4i4.1738.
N. R. Siahaan, R. Y. Tiffany, S. R. E. Sinaga, V. N. B. Naibaho, and M. I. Fahmi, “ANALISIS SENTIMEN ULASAN APLIKASI MEDIA SOSIAL WHATSAPP MENGGUNAKAN METODE NAÏVE BAYES CLASSIFIER,”, BETRIK, vol. 14, no. 22 , 2023, https://doi.org/10.36050/betrik.v14i02%20AGUSTUS.104.
K. Anwar, “Analisa sentimen Pengguna Bukalapak Di Indonesia Pada Review Smartphone Menggunakan Naïve Bayes,” KLIK, vol. 2, no. 4, pp. 148–155, Feb. 2022, doi: 10.30865/klik.v2i4.315.
V. Alviani, S. Alam, and I. Kurniawan, “ANALISIS SENTIMEN REVIEW APLIKASI WETV PADA PLATFORM TWITTER MENGGUNAKAN SUPPORT VECTOR MACHINE,” STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer, vol. 2, no. 3, pp. 143–149, Aug. 2023, doi: 10.55123/storage.v2i3.2351.
T. A. Azzahra et al., “Perbandingan Efektivitas Naïve Bayes dan SVM dalam Menganalisis Sentimen Kebencanaan di Youtube,”, MIB, vol. 8 no. 1, 2024, doi: 10.30865/mib.v8i1.7186.
S. M. Siroj, I. Arwani, and D. E. Ratnawati, “Analisis Sentimen Opini Publik pada Twitter terhadap Efek Pembelajaran Daring di Universitas Brawijaya menggunakan Metode K-Nearest Neighbor,”, JPTIIK, vol. 5, no. 7, 2021. Available: http://j-ptiik.ub.ac.id.
T. Taslim, S. Handayani, and F. Fajrizal, “Kinerja Komparatif Optimasi Algoritma Naïve Bayes dalam Klasifikasi Teks untuk Uji Klinis Kanker,” eksplora, vol. 13, no. 1, pp. 113–123, Sep. 2023, doi: 10.30864/eksplora.v13i1.994.
D. Darwis, N. Siskawati, and Z. Abidin, “PENERAPAN ALGORITMA NAÏVE BAYES UNTUK ANALISIS SENTIMEN REVIEW DATA TWITTER BMKG NASIONAL,” JTK, vol. 15, no. 1, p. 131, Feb. 2021, doi: 10.33365/jtk.v15i1.744.
N. Agustina, D. H. Citra, W. Purnama, C. Nisa, and A. R. Kurnia, “Implementasi Algoritma Naïve Bayes untuk Analisis Sentimen Ulasan Shopee pada Google Play Store: The Implementation of Naïve Bayes Algorithm for Sentiment Analysis of Shopee Reviews On Google Play Store,” MALCOM, vol. 2, no. 1, pp. 47–54, Apr. 2022, doi: 10.57152/malcom.v2i1.195.
M. S. Simanjuntak and N. Damanik, “Performance Analysis Of Support Vector Machine In Identifying Comments And Ratings On E-Commerce,”, International Journal of Basic and Applied Science, vol. 11 no. 1, 2022. doi.org/10.35335/ijobas.v11i1.79
M. I. Syafii, “Sentimen Analisis Pada Media Sosial Menggunakan Metode Naïve Bayes Classifier,” Jurnal Teknologi Pintar, vol. 3, no. 2, 2023.
A. M. Simarmata, A. Z. Putra, and A. M. Husein, “Penerapan Metode Computer Vision Dalam Klasifikasi Buah Jeruk Menggunakan Teknik Image Pre-Processing”, DSI, vol. 3, no. 2, 2023, doi: 10.47709/dsi.v3i2.4010.
T. Jamaluddin, M. A. Bijaksana, and I. Asror, “Perbandingan Algoritma Sentencepiece BPE dan Unigram Pada Tokenisasi Artikel Bahasa Indonesia,” eProceedings of Engineering, vol. 7, no. 2, 2020.
W. Rifai and E. Winarko, “Modification of Stemming Algorithm Using A Non Deterministic Approach To Indonesian Text,” Indonesian J. Comput. Cybern. Syst., vol. 13, no. 4, p. 379, Oct. 2019, doi: 10.22146/ijccs.49072.
B. Wijaya Rauf, “Sentimen Analisis Pertambangan Di Konawe Utara Dengan Metode Naïve Bayes,”, Prosiding Seminar Nasional Pemanfaatan Sains Dan Teknologi Informasi, vol. 1, no. 1, 2023, pp. 1–5. [Online]. Available: https://t.co/fSdh2dCADm.
R. Situmorang, U. M. Husni Tamyis, and L. S. Andar Muni, “Analisis Sentimen Destinasi Wisata di JawaBarat Pada Twitter Menggunakan Algoritma Naïve Bayes Classifier,” Simtek: j. sist. inf. dan Teknik kompûter., vol. 8, no. 2, pp. 339–342, Oct. 2023, doi: 10.51876/simtek.v8i2.287.
Tania Puspa Rahayu Sanjaya, Ahmad Fauzi, and Anis Fitri Nur Masruriyah, “Analisis sentimen ulasan pada e-commerce shopee menggunakan algoritma Naïve Bayes dan support vector machine,” infotech, vol. 4, no. 1, pp. 16–26, Jun. 2023, doi: 10.37373/infotech.v4i1.422.
G. Gumelar, Q. Ain, R. Marsuciati, S. A. Bambang, A. Sunyoto, and S. Mustafa, “Kombinasi Algoritma Sampling dengan Algoritma Klasifikasi untuk Meningkatkan Performa Klasifikasi Dataset Imbalance,”, Prosiding SISFOTEK, vol. 5, no. 1, 2021. Available: https://seminar.iaii.or.id/index.php/SISFOTEK/article/view/295.
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