A Car Booking Method Using K-Means
Case Study: Car Rental
DOI:
https://doi.org/10.61132/neptunus.v3i3.1055Keywords:
Booking System, Business Intelligence, Car Rental, Clustering, K-MeansAbstract
This study discusses the application of the K-Means Clustering algorithm in the car rental ordering system. The objective is to help group booking data based on certain patterns such as car type, booking frequency, and rental duration. The clustering results are expected to improve service efficiency and help companies better understand customer preferences. The research was conducted using historical car rental booking data from a rental company. The results show that the K-Means method can successfully cluster booking data into several useful clusters for business decision-making. This extended paper also explores theoretical concepts of clustering, related studies, limitations of the method, and potential future enhancements such as integrating predictive analytics. It highlights the importance of transforming large volumes of raw booking data into actionable business intelligence to support marketing strategies, fleet management, and customer segmentation.
References
Fitriani, S., & Sari, R. F. (2020). Clustering pelanggan penyewaan kendaraan menggunakan metode K-Means. Jurnal Sains dan Teknologi, 11(4), 312-318.
Gunawan, H., & Rahmawati, R. (2020). Pengelompokan data pelanggan rental mobil menggunakan K-Means. Jurnal Sistem Informasi, 8(1), 10-16.
Han, J., Pei, J., & Kamber, M. (2012). Data mining: Concepts and techniques (3rd ed.). Elsevier.
Hidayat, T., & Kurniawan, R. (2021). Optimalisasi strategi pemasaran dengan data clustering. Jurnal Bisnis dan Teknologi, 14(1), 55-61.
Jain, A. K. (2010). Data clustering: 50 years beyond K-Means. Pattern Recognition Letters, 31(8), 651-666. https://doi.org/10.1016/j.patrec.2009.09.011
Lestari, T., & Nugraha, R. (2018). Analisis segmentasi konsumen rental mobil dengan K-Means. Jurnal Informatika, 12(1), 21-26.
Maulana, A., & Saputra, H. (2022). Penerapan algoritma K-Means untuk segmentasi data penjualan kendaraan. Jurnal Teknologi Informasi, 17(1), 101-106.
Nugroho, S. P., & Putra, A. (2021). Analisis pola penyewaan mobil menggunakan K-Means clustering. Jurnal Teknologi dan Sistem Komputer, 9(3), 234-240.
Nurhayati, D. A., & Prasetyo, E. (2019). Penerapan algoritma K-Means dalam segmentasi data penjualan. Jurnal Informatika, 13(2), 123-130.
Putri, M. P., & Hidayat, R. (2017). Customer segmentation pada perusahaan rental mobil menggunakan K-Means clustering. Jurnal Teknologi Informasi, 9(2), 67-72.
Sari, A. P., & Prabowo, H. (2023). Implementasi K-Means clustering dalam sistem pemesanan online. Jurnal Sistem Informasi dan Teknologi, 15(2), 77-83. https://doi.org/10.55583/jtisi.v2i2.901
Setiawan, I., et al. (2020). Implementasi algoritma K-Means untuk segmentasi pelanggan. Jurnal Teknologi Informasi dan Ilmu Komputer, 7(2), 145-150.
Susanti, N., & Wijaya, R. (2016). Aplikasi data mining untuk prediksi penyewaan mobil dengan K-Means. Jurnal Ilmu Komputer, 14(2), 88-93.
Tan, P. N., Steinbach, M., Karpatne, A., & Kumar, V. (2018). Introduction to data mining (2nd ed.). Pearson.
Xu, R., & Wunsch, D. (2005). Survey of clustering algorithms. IEEE Transactions on Neural Networks, 16(3), 645-678. https://doi.org/10.1109/TNN.2005.845141
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