Application of Data Mining Using Methods K-Means Clustering for Clustering Baby Goods Rental Patterns (Case Study: Baby Kha House Store)

Authors

  • Roja' Putri Cintani Universitas Pancasila
  • Shafa Aurelia Putri Universitas Pancasila
  • Desti Fitriati Universitas Pancasila
(*) Corresponding Author

DOI:

https://doi.org/10.34288/jri.v6i2.265

Keywords:

Rental Pattern, Data Mining, Clustering, K-Means Clustering

Abstract

A baby item rental business is a practical option for parents who want to fulfill their baby's needs without buying them. Babykhahouse is one of the stores that offer rental services for various kinds of mother, baby, and child equipment. As the volume of data related to rental transactions increases, it is also increasingly difficult to know and understand the rental patterns found at the Babykhahouse store. This research aims to get a rental pattern that can later be a consideration for the store in determining promos and adding stock items. In handling these problems, data mining methods, especially clustering, are applied to group data and classify it based on certain groups. The clustering method used in this research is K-Means Clustering, which generates clusters to find similar rental patterns. In this study, 2 (two) types of clusters were formed, where, based on the 2 (two) clusters, it will be known which products have high and low rental rates. Based on the research, the results are 100 data in cluster 0, or the unsold cluster, and 64 in cluster 1, or the sold cluster. Products included in cluster 1 or in-demand clusters are products with a high level of sales.

Downloads

Download data is not yet available.

References

Amelia, S. (2023). The Role of Technology in Economic and Business Transformation in the Digital Era. IC-ITECHS, 4(1), 264–270. https://snatika.stiki.ac.id/IC-ITECHS/article/view/1082

Ardiansyah, W. M. (2023). Peran Teknologi dalam Transformasi Ekonomi dan Bisnis di Era Digital. JMEB: Jurnal Manajemen Ekonomi Dan Bisnis, 1(1), 1–12. https://doi.org/10.59561/jmeb.v1i01.89

Awalina, E. F. L., & Rahayu, W. I. (2023). Optimalisasi Strategi Pemasaran dengan Segmentasi Pelanggan Menggunakan Penerapan K-Means Clustering pada Transaksi Online Retail. Jurnal Teknologi Dan Informasi, 13(2), 122–137. https://doi.org/10.34010/JATI.V13I2.10090

Cholik, C. A. (2021). Perkembangan Teknologi Informasi Komunikasi / ICT dalam Berbagai Bidang. Jurnal Fakultas Teknik Kuningan, 2(2), 39–46. https://jurnal.unisa.ac.id/index.php/jft/article/view/83

Handoko, S., Fauziah, F., & Handayani, E. T. E. (2020). Implementasi Data Mining Untuk Menentukan Tingkat Penjualan Paket Data Telkomsel Menggunakan Metode K-Means Clustering. Jurnal Ilmiah Teknologi Dan Rekayasa, 25(1), 76–88. https://doi.org/10.35760/TR.2020.V25I1.2677

Mutiasari, A. I. (2020). Perkembangan Industri Perbankan Di Era Digital. Jurnal Ekonomi Bisnis Dan Kewirausahaan, 9(2), 32–41. https://doi.org/10.47942/IAB.V9I2.541

Nainggolan, R., & Tobing, F. A. T. (2023). Developing HIV/AIDS Patient Profile Model Using K-Means Clustering Method. IJNMT (International Journal of New Media Technology), 10(1), 35–41. https://doi.org/10.31937/IJNMT.V10I1.3199

Panggabean, D. S. O., Buulolo, E., & Silalahi, N. (2020). Penerapan Data Mining Untuk Memprediksi Pemesanan Bibit Pohon Dengan Regresi Linear Berganda. JURIKOM (Jurnal Riset Komputer), 7(1), 56. https://doi.org/10.30865/jurikom.v7i1.1947

Pivoto, D., Laimer, C. G., Mores, G. D. V., Waquil, P. D., Talamin, E., Corte, V. F. D., & Matos, E. De. (2023). Smart Farming In Brazil: An Overview Of Technology, Adoption And Farmer Perception. Revista Brasileira de Gestão e Desenvolvimento Regional, 19(1), 85–100. https://doi.org/10.54399/RBGDR.V19I1.6040

Purwadi, P., Ramadhan, P. S., & Safitri, N. (2019). Penerapan Data Mining Untuk Mengestimasi Laju Pertumbuhan Penduduk Menggunakan Metode Regresi Linier Berganda Pada BPS Deli Serdang. Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika Dan Komputer), 18(1), 55–61. https://doi.org/10.53513/JIS.V18I1.104

Putriana, P., Suarna, N., & Prihartono, W. (2023). Analisis Clustering Prestasi Atlet Pada Berbagai Cabang Olahraga Menggunakan Algoritma K-Means. JATI (Jurnal Mahasiswa Teknik Informatika), 7(6), 3435–3442. https://doi.org/10.36040/JATI.V7I6.8211

Raynard, M., & Wang, G. (2022). Information Technology Risk Management Analysis on Money Transfer Services in Post Offices Using Framework Standardization ISO 22301. Journal on Education, 5(1), 1214–1221. https://doi.org/10.31004/JOE.V5I1.743

Sari, W. P., & Sutabri, T. (2023). Analisa Cluster Dengan K-Mean Clustering Untuk Pengelompokan Data Cybercrime. Jurnal Informatika Teknologi Dan Sains (Jinteks), 5(1), 49–53. https://doi.org/10.51401/JINTEKS.V5I1.2209

Siregar, L. Y., & Nasution, M. I. P. (2020). Perkembangan Teknologi Informasi Terhadap Peningkatan Bisnis Online. Hirarki : Jurnal Ilmiah Manajemen Dan Bisnis, 2(1), 71–75. https://doi.org/10.30606/hjimb

Situmorang, A., Tukino, T., Novalia, E., & Ahmad, S. (2022). Klasifikasi Hasil Penjualan Minuman Ringan Pada Koperasi Berdasarkan Jenis Barang Menggunakan Algoritma K-Means Clustering. Tika, 7(2), 250–255. https://doi.org/10.51179/tika.v7i3.1565

Wijaya, A., & Susilo, S. R. (2021). How Family Business in SME Scale Alleviate Their Business Amid Pandemic. Proceedings of the Ninth International Conference on Entrepreneurship and Business Management (ICEBM 2020), 174, 119–123. https://doi.org/10.2991/AEBMR.K.210507.018

Downloads

Published

2024-03-11

How to Cite

Roja’ Putri Cintani, Shafa Aurelia Putri, & Desti Fitriati. (2024). Application of Data Mining Using Methods K-Means Clustering for Clustering Baby Goods Rental Patterns (Case Study: Baby Kha House Store). Jurnal Riset Informatika, 6(2), 85–94. https://doi.org/10.34288/jri.v6i2.265

Issue

Section

Articles