Analisa Kepuasan Pelanggan Terhadap Layanan Aplikasi E-Commerce Menggunakan Algoritma C4.5
DOI:
https://doi.org/10.30865/resolusi.v4i6.1960Keywords:
Customer Satisfaction; E-Commerce; C4.5 Algorithm; Data AnalysisAbstract
Customer satisfaction is one of the key factors that greatly influences loyalty and business sustainability of an e-commerce application. This research focuses on analyzing the level of customer satisfaction with e-commerce services using the C4.5 algorithm. This research aims to identify key factors that influence customer satisfaction and provide recommendations that can help e-commerce companies improve the quality of their services. Customer satisfaction data is collected through surveys that cover various attributes such as product quality, delivery speed and customer service responsiveness. The analysis results show that the product delivery attribute is the factor that most influences customer satisfaction, with a gain value of 0.337981562. The resulting model has an accuracy of 93%, showing good ability in predicting customer satisfaction. These findings are expected to provide practical insights for e-commerce companies in their efforts to increase customer satisfaction and loyalty.
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References
A. S. S. o’g’li Shirin, Mirzaeva Nodirovna, “E-Commerce Trends Shaping The Future of Retail.pdf.” 2024.
R. Setyawati, “Pengaruh Kualitas Pelayanan Terhadap Tingkat Kepuasan Konsumen,” Inov. J. Ekon. Keuang. dan Manaj., vol. 19, no. 1, pp. 57–63, 2023, [Online]. Available: https://journal.feb.unmul.ac.id/index.php/INOVASI/article/view/12660/2345
W. Yuliyanto, “Pengaruh Promosi Terhadap Kepuasan Pelanggan di Toko Aleea Shopid Kebumen,” J. Bus. Econ. Res., vol. 1, no. 2, pp. 168–172, 2020, doi: 10.47065/jbe.v1i2.244.
F. Anggraini and A. Budiarti, “PENGARUH HARGA, PROMOSI, DAN KUALITAS PELAYANAN TERHADAP LOYALITAS PELANGGAN DIMEDIASI KEPUASAN PELANGGAN PADA KONSUMEN GOJEK,” J. Pendidik. Ekon., vol. 08, pp. 86–94, 2020, [Online]. Available: https://ejournal.unesa.ac.id/index.php/jupe/article/view/36354
S. A. A. Wazir, Indra, “Analisis Kepuasan Konsumen Dengan Algoritma C4.5 Pada Umkm Minimall,” Comasie, vol. 3, no. 3, pp. 21–30, 2020.
Nurul Farhana, Harly Okprana, and Rizky Khairunnisa Sormin, “Analisis Tingkat Kepuasan Pelanggan Pada Aplikasi Tiktok Shop Dengan Metode Algoritma C4.5,” SmartEDU J., vol. 1, no. 3, pp. 101–111, 2022.
W. T. Wu et al., “Data Mining in Clinical Big Data: The Frequently Used Databases, Steps, And Methodological Models,” Mil. Med. Res., vol. 8, no. 1, pp. 1–12, 2021, doi: 10.1186/s40779-021-00338-z.
C. R. Aditya Nugroho and T. Kristiana, “Penerapan Algoritma C4.5 Untuk Kepuasan Pelanggan Toko Online Parfume Chantik,” J. Algoritm., vol. 3, no. 1, pp. 10–21, 2022, doi: 10.35957/algoritme.v3i1.3169.
K. A. Saputra, J. T. Hardinata, M. R. Lubis, S. R. Andani, and I. S. Saragih, “Klasifikasi Algoritma C4.5 Dalam Penerapan Tingkat Kepuasan Siswa Terhadap Media Pembelajaran Online,” Kaji. Ilm. Inform. dan Komput., vol. 1, no. 3, pp. 113–118, 2020, [Online]. Available: https://djournals.com/klik
S. N. Bardab, T. M. Ahmed, and T. A. A. Mohammed, “Data mining classification algorithms: An overview,” Int. J. Adv. Appl. Sci., vol. 8, no. 2, pp. 1–5, 2021, doi: 10.21833/ijaas.2021.02.001.
A. Triayudi and W. O. Widyarto, “Educational Data Mining Analysis Using Classification Techniques,” J. Phys. Conf. Ser., vol. 1933, no. 1, 2021, doi: 10.1088/1742-6596/1933/1/012061.
R. C. Chen, C. Dewi, S. W. Huang, and R. E. Caraka, “Selecting critical features for data classification based on machine learning methods,” J. Big Data, vol. 7, no. 1, 2020, doi: 10.1186/s40537-020-00327-4.
B. Charbuty and A. Abdulazeez, “Classification Based on Decision Tree Algorithm for Machine Learning,” J. Appl. Sci. Technol. Trends, vol. 2, no. 01, pp. 20–28, 2021, doi: 10.38094/jastt20165.
S. W. Siahaan, K. D. R. Sianipar, and P. P. P. A. N. W. F. I. R. H. Zer, “Penerapan Algoritma C4 . 5 Dalam Meningkatkan Kemampuan Bahasa Inggris Pada Mahasiswa,” vol. 13, no. 2, pp. 229–239, 2020.
M. Bansal, A. Goyal, and A. Choudhary, “A comparative analysis of K-Nearest Neighbor, Genetic, Support Vector Machine, Decision Tree, and Long Short Term Memory algorithms in machine learning,” Decis. Anal. J., vol. 3, no. May, p. 100071, 2022, doi: 10.1016/j.dajour.2022.100071.
M. F. Rizqullah, N. T. Raihana, and M. I. Jambak, “Komparasi Penerapan Algoritma C4.5, K-Nearest Neighbor, dan Naïve Bayes untuk Keberlangsungan Pasien Gagal Jantung,” Klik Kaji. Ilm. Inform. Dan Komput., vol. 4, no. 5, pp. 2580–2587, 2024, doi: 10.30865/klik.v4i5.1788.
R. Sovia, A. Muhammad, S. Arlis, Guslendra, and S. Defit, “Analysis of sales levels of pharmaceutical products by using data mining algorithm C45,” Indones. J. Electr. Eng. Comput. Sci., vol. 22, no. 1, pp. 476–484, 2021, doi: 10.11591/ijeecs.v22.i1.pp476-484.
S. A. S. Ratih Nurdiyani Sari,Novrina, “Penerapan algoritma c4.5 untuk memprediksi bencana gunung meletus di indonesia,” Tek. dan Sci., vol. 3, no. 2, pp. 1–9, 2024.
A. R. S. Nasution, “Identifikasi Permasalahan Penelitian,” ALACRITY J. Educ., vol. 1, no. 2, pp. 13–19, 2021, doi: 10.52121/alacrity.v1i2.21.
L. Thorndahl, Katrine and D. Stentoft, “Educating Students for a Complex Future – Why Integrating a Problem Analysis in Problem Based Learning has Something to Offer,” Interdiscip. J. Probl. Learn., vol. 14, no. 1, 2020.
A. Setiawan and D. Pasha, “Sistem Pengolahan Data Penilaian Berbasis Web Menggunakan Metode Piecies,” J. Teknol. dan Sist. Inf., vol. 1, no. 1, pp. 97–104, 2020, doi: 10.33365/jtsi.v1i1.225.
I. Ahmad, S. Samsugi, and Y. Irawan, “Implementasi Data Mining Sebagai Pengolahan Data,” J. Teknoinfo, vol. 16, no. 1, p. 46, 2022, [Online]. Available: http://portaldata.org/index.php/portaldata/article/view/107
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