STUDI ALGORITMA NEURAL NETWORK DALAM KLASIFIKASI SENTIMEN PENGGUNA SHOPEE: PENINGKATAN AKURASI MODEL
DOI:
https://doi.org/10.23960/jitet.v13i2.6113Abstract Views: 302 File Views: 277
Abstract
Advances in technology and the growth of e-commerce have generated a large amount of user sentiment data, which can be leveraged to improve user experience. Shopee is an e-commerce platform in Indonesia that allows users to buy and sell various products online. Through the Shopee app, users can find a variety of products ranging from clothing, electronics, cosmetics, household needs, to food. However, sentiment data analysis is often constrained by data complexity and the low accuracy of conventional models. This research aims to improve accuracy in Shopee app users by applying Neural Network algorithm. Evaluation of application user sentiment is important for e-commerce companies, such as Shopee, because it provides an overview of user satisfaction and experience with the services offered. In this research, the Neural Network algorithm is used to process sentiment data by optimizing parameters to improve the optimal parameters, including the best K value that can improve model performance. Experimental results show that the best K value is 2, with model accuracy reaching 95.08%. To further measure effectiveness, recall and precision values were calculated for positive and negative categories. The recall result for positive sentiment reached 98.77%, while for negative sentiment it was 93.33%. In addition, the precision for the positive category was 93.73% and for the negative category was 93.33%.
Downloads
References
Achmad, A. A., Iin, K., & Iska, Y. (2023). Analisis Klasifikasi Sentimen Berbasis Topik pada Ulasan Layanan Dana dan Sakuku dengan Convolutional Neural Network. INFORMASI (Jurnal Informatika Dan Sistem Informasi), 15(2), 225–236. https://doi.org/10.37424/informasi.v15i2.267
Al Azies, H., Rohmatullah, F. A., Rochmanto, H. B., & Isnarwaty, D. P. (2024). Towards Optimization: a Data-Driven Approach Using K-Medoids Clustering Algorithm for Regional Education Quality Assessment. Jurnal Informatika Dan Teknik Elektro Terapan, 12(3). https://doi.org/10.23960/jitet.v12i3.4862
Fersellia, F., Utami, E., & Yaqin, A. (2023). Sentiment Analysis of Shopee Food Application User Satisfaction Using the C4.5 Decision Tree Method. Sinkron, 8(3), 1554–1563. https://doi.org/10.33395/sinkron.v8i3.12531
Goyal, G., & Gupta, V. (2022). A Deep Learning based hybrid model for improving accuracy of sentiment analysis. Proceedings - 2022 5th International Conference on Computational Intelligence and Communication Technologies, CCICT 2022, October, 204–209. https://doi.org/10.1109/CCiCT56684.2022.00047
Idris, I. S. K., Mustofa, Y. A., & Salihi, I. A. (2023). Analisis Sentimen Terhadap Penggunaan Aplikasi Shopee Mengunakan Algoritma Support Vector Machine (SVM). Jambura Journal of Electrical and Electronics Engineering, 5(1), 32–35. https://doi.org/10.37905/jjeee.v5i1.16830
Indiani, N. L. P., & Febriandari, S. N. S. (2021). Key antecedents of consumer purchasing behaviour in emerging online retail market. Cogent Business & Management, 8(1), 1978370. https://doi.org/10.1080/23311975.2021.1978370
K. R., B., C., A., Orlando, B., & Parameswaran, L. (2018). An Algorithm for Text Prediction Using Neural Networks BT - Computational Vision and Bio Inspired Computing (D. J. Hemanth & S. Smys (eds.); pp. 186–192). Springer International Publishing.
Kalaiarasu, M., & Ranjeeth Kumar, C. (2022). Sentiment Analysis using Improved Novel Convolutional Neural Network (SNCNN). International Journal of Computers, Communications and Control, 17(2). https://doi.org/10.15837/ijccc.2022.2.4351
Karista, T. (2023). OPTIMALISASI PELAYANAN SISTEM APLIKASI KEPUASAN PENERIMAAN ANGGOTA KEPOLISIAN ( SILAK-PAK ) DALAM REKRUTMEN BINTARA POLRI DI WILAYAH HUKUM POLDA NUSA TENGGARA BARAT OPTIMIZATION OF POLICE RECRUITMENT SATISFACTION APPLICATION SYSTEM ( SILAK-PAK ) SERVICES. 1(3), 275–297.
Katsko, S. (2022). Transformation of the university course “Informatics.” Actual Problems of Education, 180–185. https://doi.org/10.33764/2618-8031-2022-1-180-185
Khatami, F. A., Irawan, B., Si, S., & Setianingsih, C. (2020). Analisis Sentimen Terhadap Review Aplikasi Layanan E-Commerce Menggunakan Metode Convolutional Neural Network Sentiment Analysis of E-Commerce Application Reviews Using the Convolutional Neural Network Method. E-Proceeding of Engineering, 7(2), 4559–4566. https://openlibrarypublications.telkomuniversity.ac.id/index.php/engineering/article/view/12305
Legiawati, N., Hermanto, T. I., & Ramadhan, Y. R. (2022). Analisis Sentimen Opini Pengguna Twitter Terhadap Perusahaan Jasa Ekspedisi Menggunakan Algoritma Naïve Bayes Berbasis PSO. JURIKOM (Jurnal Riset Komputer), 9(4), 930. https://doi.org/10.30865/jurikom.v9i4.4629
Lindgaard, G., & Dudek, C. (2003). What is this evasive beast we call user satisfaction? Interacting with Computers, 15, 429–452. https://doi.org/10.1016/S0953-5438(02)00063-2
Melia, M., Irawan, B., & Nurdiawan, O. (2024). Analisis Sentimen Terhadap Pengguna Gojek Dan Grab Pada Media Sosial Twitter Menggunakan Random Forest. JATI (Jurnal Mahasiswa Teknik Informatika), 7(5), 3614–3618. https://doi.org/10.36040/jati.v7i5.7694
Nababan, H., Kelana Jaya, I., Manurung, S., & Artikel, H. (2023). Analisis Sentimen Produk Penjualan Shopee Pada Pengguna Twitter Menggunakan Metode K-Means. Jurnal Ilmiah Sistem Informasi, 3(2), 137–142. http://ojs.fikom-methodist.net/index.php/methosisfo
Rika Widianita, D. (2023). E-COMMERCE CUSTOMER SATISFACTION ANALYSIS ON MICROBLOGS. AT-TAWASSUTH: Jurnal Ekonomi Islam, VIII(I), 1–19.
Rivaldi, R. C., Wismarini, T. D., Lomba, J. T., & Semarang, J. (2024). Analisis Sentimen Pada Ulasan Produk Dengan Metode Natural Language Processing (NLP) (Studi Kasus Zalika Store 88 Shopee). 17(1), 120–128.
Sihombing, R., Rumapea, N., Tarigan, J., Pandi, F., & Sinaga, F. (2023). Evaluasi Usability Aplikasi Shopee pada Proses Pembelian Online Dengan Metode User Centered Design. Jurnal SIFO Mikroskil, 24, 81–94. https://doi.org/10.55601/jsm.v24i2.1023
Sundari, I., & Hadisaputro, E. L. (2022). Implementasi Servqual dan Importance Performance Analysis Terhadap Tingkat Kepuasan Pelanggan pada Aplikasi Shopee Indonesia. Jurnal Sosial Teknologi, 2(4), 330–341. https://doi.org/10.59188/jurnalsostech.v2i4.323
Thakkar, A., Agarwal, A., Mungra, D., & Chaudhari, K. (2022). Improving the Performance of Sentiment Analysis Using Enhanced Preprocessing Technique and Artificial Neural Network. IEEE Transactions on Affective Computing, PP. https://doi.org/10.1109/TAFFC.2022.3206891
Thamrin, T., Stevy, S., Linda, T., & Sembiring, L. (2022). Investigating the Online Shopping Pattern for Beauty Brands Most Liked by Indonesian Women. Frontiers in Business and Economics, 1(1), 24–34. https://doi.org/10.56225/finbe.v1i1.82
