Sentiment Analysis of Customer Satisfaction of Shopee Service Quality

Debby Erce Sondakh; Semmy  Taju; Regina Patricia; Reinhard Tumbal

doi:10.35974/isc.v11i5.3574

Authors

Debby Erce Sondakh Universitas Klabat
Semmy Taju Universitas Klabat
Regina Patricia Universitas Klabat
Reinhard Tumbal Universitas Klabat

https://doi.org/10.35974/isc.v11i5.3574

Keywords:

E-commerce, Sentiment Analysis, SVM, k-NN, Random Forest

Abstract

E-commerce has become one of the most popular services, especially during the coronavirus (COVID-19) pandemic that restricts activities outside the home. Customer satisfaction is an important factor for the success of e-commerce companies. Therefore, this study aims to analyse customer satisfaction with the service quality of Shopee, one of the e-commerce platforms widely used by the public. Sentiment analysis and Support Vector Machine algorithm are used to model customer satisfaction. The analysis results show good performance. In the positive class, Sensitivity reached 81.7%, Specificity 95.3%, Accuracy 90.8%, and MCC 0.79. In the neutral class, sensitivity reached 91.8%, specificity 83.5%, accuracy 86.3%, and MCC 0.721. In the negative class, sensitivity reached 77.5%, specificity 96.6%, accuracy 90.3%, and MCC 0.778. Thus, the resulting model can accurately identify customer sentiment based on the reviews provided.

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Author Biography

Debby Erce Sondakh, Universitas Klabat

Computer Science

References

Abirami, A. M., & Gayathri, V. (2017). A survey on sentiment analysis methods and approach. 2016 Eighth International Conference on Advanced Computing (ICoAC), 72–76. https://doi.org/10.1109/ICoAC.2017.7951748

Cahyaningtyas, C., Nataliani, Y., & Widiasari, I. R. (2021). Analisis Sentimen Pada Rating Aplikasi Shopee Menggunakan Metode Decision Tree Berbasis SMOTE. AITI, 18(2), 173–184. https://doi.org/10.24246/aiti.v18i2.173-184

Dey, S., Wasif, S., Tonmoy, D. S., Sultana, S., Sarkar, J., & Dey, M. (2020). A Comparative Study of Support Vector Machine and Naive Bayes Classifier for Sentiment Analysis on Amazon Product Reviews. 2020 International Conference on Contemporary Computing and Applications (IC3A), 217–220. https://doi.org/10.1109/IC3A48958.2020.233300

Erlyana, Y., & Hartono, H. (2017). Business model in marketplace industry using business model canvas approach: An e-commerce case study. IOP Conference Series: Materials Science and Engineering, 277, 012066. https://doi.org/10.1088/1757-899X/277/1/012066

Hariguna, T., Baihaqi, W. M., & Nurwanti, A. (2019). Sentiment Analysis of Product Reviews as A Customer Recommendation Using the Naive Bayes Classifier Algorithm. IJIIS: International Journal of Informatics and Information Systems, 2(2), 48–55. https://doi.org/10.47738/ijiis.v2i2.13

Isnain, A. R., Supriyanto, J., & Kharisma, M. P. (2021). Implementation of K-Nearest Neighbor (K-NN) Algorithm For Public Sentiment Analysis of Online Learning. IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 15(2), 121. https://doi.org/10.22146/ijccs.65176

Kütz, M. (2016). E-commerce: Combining Business and Information Technology. Bookboon.

Oktora, R., Kusumatrisna, A. L., Hasyyati, A. N., & Untari, rima. (2022). Statistik eCommerce 2022.

Pratmanto, D., Rousyati, R., Wati, F. F., Widodo, A. E., Suleman, S., & Wijianto, R. (2020). App Review Sentiment Analysis Shopee Application In Google Play Store Using Naive Bayes Algorithm. Journal of Physics: Conference Series, 1641(1), 012043. https://doi.org/10.1088/1742-6596/1641/1/012043

Rhohmawati, U., Slamet, I., & Pratiwi, H. (2019). Sentiment Analysis Using Maximum Entropy on Application Reviews (Study Case: Shopee on Google Play). Jurnal Ilmiah Teknik Elektro Komputer Dan Informatika, 5(1). https://doi.org/10.26555/jiteki.v5i1.13087

Sandag, G. A., Soegiarto, E. H. E., Laoh, L., Gunawan, A., & Sondakh, D. (2022). Sentiment Analysis of Government Policy Regarding PPKM on Twitter Using LSTM. 2022 4th International Conference on Cybernetics and Intelligent System (ICORIS), 1–6. https://doi.org/10.1109/ICORIS56080.2022.10031474

Singh, J., & Tripathi, P. (2021). Sentiment analysis of Twitter data by making use of SVM, Random Forest and Decision Tree algorithm. 2021 10th IEEE International Conference on Communication Systems and Network Technologies (CSNT), 193–198. https://doi.org/10.1109/CSNT51715.2021.9509679

Sitepu, M. B., Munthe, I. R., & Harahap, S. Z. (2022). Implementation of Support Vector Machine Algorithm for Shopee Customer Sentiment Anlysis. Sinkron, 7(2), 619–627. https://doi.org/10.33395/sinkron.v7i2.11408

Uly, Y. A., & Djumena, E. (2022, August 3). Nilai Transaksi E-Commerce Indonesia Capai Rp 108,54 Triliun di Kuartal I-2022. Kompas.Com. https://money.kompas.com/read/2022/08/03/211200826/nilai-transaksi-e-commerce-indonesia-capai-rp-108-54-triliun-di-kuartal-i-2022

Veselova, A. (2020). Marketplace vs. Online Shop. Proceedings of the 62nd International Scientific Conference on Economic and Social Development, 30–36.