Klasifikasi Tingkat Minat Belanja Online Melalui Media Sosial pada Masyarakat di Kota Binjai Meggunakan Algoritma K-Means
DOI:
https://doi.org/10.62951/bridge.v2i3.169Keywords:
Online Shopping, Social Media, K-Means Clustering, Binjai CityAbstract
The advancement of information technology and globalization has transformed shopping behaviors, with social media becoming the primary platform for online shopping. This study aims to analyze the online shopping preferences of residents in Binjai City through social media using clustering methods, specifically the K-Means algorithm. Data were collected via a questionnaire targeting 523 respondents in Binjai City, focusing on variables such as gender, age, and the social media platforms used. Clustering methods are employed to group online shopping data into representative clusters, helping identify community preferences for specific social media platforms for shopping. Matlab is used to process the data and generate relevant insights into online shopping patterns, facilitating decision-making regarding the selection of the most suitable social media platform for transactions.The findings of this study are expected to provide valuable insights for both sellers and buyers in determining the most effective social media platforms for online shopping. Additionally, the results will be useful for residents of Binjai City to understand and choose the social media platforms that best meet their online shopping needs.
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References
Agus Sri Iswiyanti. (2021). Analisis Tingkat Belanja Online Dikalangan Mahasiswa Universitas GunaDarma. Jurnal Inovasi Penelitian, 2, 391–396.
Aristika, W., & Hartono, W. J. (2020). Penerpana Clustering K-Means Untuk Menentukan Pengaruh Media Sosial Facebook Terhadap Usaha Mikro, Kecil Dan Menengah (UMKM) Di Kecamatan Pekanbaru Kota. 11, 2389–2395.
Ayuh et al. (2021). Analisis Komunikasi Bisnis Online Shop Mantan Karyawan Melalui Media Sosial Instagram. 3, 12–18.
Fakhri, D. A., Defit, S., & Sumijan. (2021). Optimalisasi Pelayanan Perpustakaan terhadap Minat Baca Menggunakan Metode K-Means Clustering. Jurnal Informasi Dan Teknologi, 3, 160–166. https://doi.org/10.37034/jidt.v3i3.137
I Gusti Ngurah Triyana. (2018). Media Sosial Dalam Proses Pembelajaran. Jurnal Pendidikan Hindu, 5, 79–90.
Kesuma, P. W., Risalah, A., & Purba, B. P. (2020). Penerapan Data Mining Dalam Proses Pengelompokkan Data Masyarakat Kurang Mampu di Kota Deli Serdang Menggunakan Metode Clustering. Jurnal Masyarakat Informatika Sumatera Utara, 10(5). https://doi.org/10.14710/jmasif.v7i1.10794
Mai, P., Tarigan, S., Hardinata, J. T., Qurniawan, H., Safii, M., & Winanjaya, R. (2022). Implementasi Data Mining Menggunakan Algoritma Apriori Dalam Menentukan Persedian Barang (Studi Kasus : Toko Sinar Harahap)). 12(2), 51–61.
Oktarian, S., Defit, S., & Sumijan. (2020). Clustering Students’ Interest Determination in School Selection Using the K-Means Clustering Algorithm Method. Jurnal Informasi Dan Teknologi, 2, 68–75. https://doi.org/10.37034/jidt.v2i3.65
Puspitarini, D. S., & Nuraeni, R. (2019). Pemanfaatan Media Sosial Sebagai Media Promosi. Jurnal Common, 3(1), 71–80. https://doi.org/10.34010/common.v3i1.1950
Sari, A. C., Hartina, R., Awalia, R., Irianti, H., Ainun, N., Sastra, F., & Indonesia, U. M. (2018). Komunikasi dan media sosial.
Sinaga, W. I. S., Buaton, R., & Sembiring, H. (2023). Klasifikasi Data Penduduk Pada Pemilihan Umum Di Kota Binjai Menggunakan Algoritma K-Means (Studi Kasus: KPU Kota Binjai). Explorer, 3(2), 95–102. https://journal.fkpt.org/index.php/Explorer/article/view/794%0Ahttps://journal.fkpt.org/index.php/Explorer/article/download/794/429
Sundari, M. A., & Pane, R. (2023). Data Mining Clustering Korban Kejahatan Pelecehan Seksual dengan Kekerasan Berdasarkan Provinsi Menggunakan Metode AHC. 5(1). https://doi.org/10.47065/bits.v5i1.3499
Yulianti, Y., Utami, D. Y., Hikmah, N., & Hasan, F. N. (2019). Penerapan Data Mining Menggunakan Algoritma K-Means Untuk Mengetahui Minat Customer Di Toko Hijab. Jurnal Pilar Nusa Mandiri, 15(2), 241–246. https://doi.org/10.33480/pilar.v15i2.650
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