Penerapan Algoritma K-Means Clustering Dalam Mengelompokkan Smartphone Yang Rekomendasi Berdasarkan Spesifikasi
DOI:
https://doi.org/10.29408/jit.v7i2.26283Keywords:
Al-Afgani Cellular, K-Means Clustering, SmartphoneAbstract
Various types of smartphones come with different prices and specifications, causing sellers to sometimes struggle with providing recommendations to consumers who want to buy a smartphone that meets their desired specifications and price range. This challenge arises because it is difficult for sellers to remember the specifications of each smartphone for sale. K-Means Clustering aims to group existing specification data into several clusters, where the data in each cluster share similar characteristics. By forming these smartphone groups, it becomes easier for sellers to recommend appropriate smartphones to customers. The research results show that various smartphone brands are categorized into three groups: the Recommended Group, which includes 225 items; the Most Recommended Group, which includes 98 items; and the Less Recommended Group, which includes 27 items. This clustering is expected to help sellers easily increase the stock of recommended smartphones according to consumer needs in terms of price and specifications.
References
Merangin, “Sistem informasi geografis pencarian konter servis handphone di wilayah Yogyakarta,” Galang Tanjung, no. 2504, pp. 1–9, 2018.
A. M. Nur, M. F. Wazdi, B. Harianto, and M. F. Zaini, “Implementation of Naive Bayes Algorithm in Analyzing Acceptance of Poor Student Assistance,” J. Phys. Conf. Ser., vol. 1539, no. 1, 2020, doi: 10.1088/1742-6596/1539/1/012018.
A. M. Nur, N. Nurhidayati, and I. Fathurrahman, “Penerapan Metode Naïve Bayes Untuk Penentuan Penerima Beasiswa Program Indonesia Pintar (PIP).,” Infotek J. Inform. dan Teknol., vol. 7, no. 1, pp. 93–102, 2024.
Saverus, “Penggunaan Algoritma K-Means Untuk Menganalisis Pelanggan Potensial Pada Dealer SPS Motor Honda Lombok Timur Nusa Tenggara Barat,” J. Kaji. Pendidik. Ekon. dan Ilmu Ekon., vol. 2, no. 1, pp. 1–19, 2019.
I. M. Haryani, Dicky Nofriansyah, “Implementasi Data Mining Untuk Pengelompokan Buku Di Perpustakaan Yayasan Nurul Islam Indonesia Baru Dengan Metode K-Means Clustering,” J. Cyber TechTech, vol. 1, no. 1, pp. 1–12, 2021.
M. Yahya, “Penggunaan Algoritma K-Means Untuk Menganalisis Pelanggan Potensial Pada Dealer SPS Motor Honda Lombok Timur Nusa Tenggara Barat,” J. Inform. dan Teknol., vol. 2, no. 2, pp. 109–118, 2019.
J. Nasir, “Penerapan Data Mining Clustering Dalam Mengelompokan Buku Dengan Metode K-Means,” Simetris J. Tek. Mesin, Elektro dan Ilmu Komput., vol. 11, no. 2, pp. 690–703, 2021, doi: 10.24176/simet.v11i2.5482.
R. Adrianto and A. Fahmi, “Penerapan Metode Clustering Dengan Algoritma K-Means Untuk Rekomendasi Pemilihan Jalur Peminatan Sesuai Kemampuan Pada Progam Studi Teknik Informatika - S1 Universitas Dian Nuswantoro,” JOINS (Journal Inf. Syst., vol. 1, no. 2, pp. 101–116, 2019.
P. Trisnawati and A. I. Purnamasari, “Penerapan Pengelompokkan Produktivitas Hasil Pertanian Menggunakan Algoritma K-Means,” Infotek J. Inform. dan Teknol., vol. 6, no. 2, pp. 249–257, 2023.
D. Jollyta, W. Ramdhan, and M. Zarlis, Konsep data mining dan penerapan. Deepublish, 2020.
P. W. Rahayu et al., Buku Ajar Data Mining. PT. Sonpedia Publishing Indonesia, 2024.
B. T. Haji, “Pengertian Implementasi,” Lap. AKHIR, vol. 31.
A. Wicaksana and T. Rachman, “Implementasi Algoritma K-Means dalam Analisis Klasterisasi Penyebaran Penyakit Hiv/Aids,” Angew. Chemie Int. Ed. 6(11), 951–952., vol. 3, no. 1, pp. 10–27, 2018.
S. Handoko, F. Fauziah, and E. T. E. Handayani, “Implementasi Data Mining Untuk Menentukan Tingkat Penjualan Paket Data Telkomsel Menggunakan Metode K-Means Clustering,” J. Ilm. Teknol. dan Rekayasa, vol. 25, no. 1, pp. 76–88, 2020, doi: 10.35760/tr.2020.v25i1.2677.
Z. Setiawan et al., BUKU AJAR DATA MINING. PT. Sonpedia Publishing Indonesia, 2023
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Infotek: Jurnal Informatika dan Teknologi
This work is licensed under a Creative Commons Attribution 4.0 International License.
Semua tulisan pada jurnal ini menjadi tanggung jawab penuh penulis. Jurnal Infotek memberikan akses terbuka terhadap siapapun agar informasi dan temuan pada artikel tersebut bermanfaat bagi semua orang. Jurnal Infotek ini dapat diakses dan diunduh secara gratis, tanpa dipungut biaya sesuai dengan lisense creative commons yang digunakan.
Jurnal Infotek is licensed under a Creative Commons Attribution 4.0 International License.
Statistik Pengunjung
