Implementasi Algoritma K-Means Clustering untuk Identifikasi Lokasi Strategis Coffee Shop
DOI:
https://doi.org/10.47065/bulletincsr.v5i4.600Keywords:
K-Means Clustering; Strategic Location; Spasial; Coffee ShopAbstract
The rapid growth of coffee shops in Bandung City has led to increasingly fierce competition among business owners, particularly in choosing strategic locations. Inappropriate location selection can negatively impact customer attraction and business sustainability. This study aims to identify strategic areas for coffee shop development in Bandung City using the spatial-based K-Means Clustering algorithm. The data used consists of active food establishment locations obtained from the Open Data Kota Bandung portal, which includes latitude and longitude information. The K-Means algorithm with K-Means++ initialization was used to group the restaurant locations into three clusters based on geographical proximity. The clustering process was carried out in two iterations, beginning with the initial centroid determination, distance calculation using the Euclidean formula, and centroid updates until convergence. Final results show that the areas of Jl. Aceh Cluster 0 at coordinates (-6.911431, 107.622713), Jl. Setiabudi Cluster 1 at coordinates (-6.879891, 107.600774), and Jl. Kebon Jati Cluster 2 at coordinates (-6.917228, 107.598990) have different strategic potentials suited to specific coffee shop concepts. Evaluation was conducted through spatial distribution visualization, minimum distance analysis, and cluster stability. This study confirms that the K-Means method is effective in supporting spatial-based decision-making for business development.
Downloads
References
D. Hermansyah, A. R. Natasya, I. R. Mukhlis, S. A. Laga, and G. Suprianto, “Sistem Pendukung Keputusan Dalam Menentukan Pemilihan Lokasi Perumahan Strategis Di Sidoarjo Dengan Metode Weighted Product,” INTEGER J. Inf. Technol., vol. 8, no. 2, 2023.
R. R. Oprasto, “Penerapan Metode TOPSIS Dalam Pemilihan Lokasi Usaha Strategis,” J. Data Sci. Inf. Syst., vol. 1, no. 3, pp. 109–116, 2023.
A. M. Ikotun, A. E. Ezugwu, L. Abualigah, B. Abuhaija, and J. Heming, “K-means clustering algorithms: A comprehensive review, variants analysis, and advances in the era of big data,” Inf. Sci. (Ny)., vol. 622, pp. 178–210, 2023.
E. F. L. Awalina and W. I. Rahayu, “Optimalisasi strategi pemasaran dengan segmentasi pelanggan menggunakan penerapan K-means clustering pada transaksi online retail,” J. Teknol. Dan Inf., vol. 13, no. 2, pp. 122–137, 2023.
D. Prasetiyo, W. Lestari, and V. Atima, “Penerapan Clustering Dengan K-Means Untuk Pemilihan Menu Favorit Di Tetra Coffeeshop,” JATISI (Jurnal Tek. Inform. dan Sist. Informasi), vol. 11, no. 3, 2024.
D. K. dan P. K. Bandung, “Data Rumah Makan, Restoran, Cafe di Kota Bandung Tahun 2017-2020,” Dinas Kebudayaan dan Pariwisata Kota Bandung. [Online]. Available: http://data.bandung.go.id/beta/index.php/portal/detail_data/33e36752-e5f1-429f-829b-745f4dfe3d17
R. S. Hamid et al., MANAJEMEN PEMASARAN MODERN: Strategi dan Taktik Untuk Kesuksesan Bisnis. PT. Sonpedia Publishing Indonesia, 2023.
M. A. Fathurrohman, “Penentuan Strategi Pengelolaan Coffee Shop di Yogyakarta dengan Mengidentifikasi Perilaku dan Karakteristik Konsumen Menggunakan Metode Association Rules dan Clustering (Studi Kasus Pada Mahasiswa Yogyakarta),” Repositori Universitas Islam Indonesia, 2022.
S. Alexander, M. Mukhsin, and W. Susanti, “Sistem Rekomendasi Cafe di Kota Pekanbaru Menggunakan Metode SAW Terintegrasi Google Maps Berbasis Website,” J. Mhs. Apl. Teknol. Komput. dan Inf., vol. 6, no. 3, pp. 104–114, 2025.
F. Nuraeni, D. Tresnawati, Y. H. Agustin, and G. Fauzi, “Optimization of market basket analysis using centroid-based clustering algorithm and fp-growth algorithm,” J. Tek. Inform., vol. 3, no. 6, pp. 1581–1590, 2022.
A. Qur’ani and F. Nindha, “Perencanaan Strategi Pengelolaan Sewa Kendaran Share Car Berdasarkan Karakteristik Konsumen menggunakan Metode Clustering dan Association Rules.” Universitas Islam Indonesia, 2024.
H. Fadholi, “Pengelompokan Usaha Mikro, Kecil, dan Menengah (UMKM) Berdasarkan Kesiapan Sertifikasi Halal menggunakan Metode Clustering Terbobot.” Universitas Islam Indonesia, 2024.
J. M. P. Sibarani, Y. Akbar, and K. Setiawan, “Implementation of RFM Analysis to Enhance Sales Patterns of Food and Beverages at Bonjour Café and Resto Using the Apriori Algorithm,” Int. J. Softw. Eng. Comput. Sci., vol. 4, no. 3, pp. 1261–1279, 2024.
V. E. Putri and H. D. Purnomo, “Integrasi Algoritma Apriori Dan K-Means Dalam Analisis Pola Pembelian Untuk Meningkatkan Strategi Pemasaran,” JIPI (Jurnal Ilm. Penelit. dan Pembelajaran Inform., vol. 10, no. 1, pp. 409–423, 2025.
F. M. Fauzi, M. E. H. Rosad, and I. Y. Arini, “Perancangan Strategi Positioning pada UMKM AD_Barber Berdasarkan Perseptual Mapping,” eProceedings Eng., vol. 10, no. 3, 2023.
A. M. Hazelia and P. F. Belgiawan, “Proposed Marketing Strategy to Increase Café Sales (Case Study: Café Sembilan Bintaro),” Int. Res. J. Econ. Manag. Stud. IRJEMS, vol. 3, no. 7, 2024.
P. R. Maulida, F. Agustina, and B. K. Khotimah, “Penentuan Segmentation, Targeting, dan Positioning pada wisatawan desa wisata Lon Malang Madura menggunakan K-means Clustering,” in Prosiding Seminar Nasional Waluyo Jatmiko, 2023, pp. 111–120.
N. A. Maori and E. Evanita, “Metode elbow dalam optimasi jumlah cluster pada k-means clustering,” Simetris J. Tek. Mesin, Elektro dan Ilmu Komput., vol. 14, no. 2, pp. 277–288, 2023.
D. Arthur and S. Vassilvitskii, “k-means++: The advantages of careful seeding,” Stanford, 2006.
Kharisma Dharma Putra, “Random State Di Machine Learning,” Bengkel TI. Accessed: Jul. 05, 2025. [Online]. Available: https://www.bengkelti.com/blog/apa-itu-random-state-di-machine-learning-dan-cara-kerjanya/
I. A. Sulasiyah, “Analisis clustering e-learning readiness di pulau jawa menggunakan k-means dan principal component analysis (pca) dengan visualisasi gi.” Fakultas Sains dan Teknologi UIN Syarif Hidayatullah Jakarta.
E. Allen et al., “Spatial quantification of microstructural degradation during fast charge in 18650 lithium-ion batteries through operando X-ray microtomography and Euclidean distance mapping,” ACS Appl. Energy Mater., vol. 5, no. 10, pp. 12798–12808, 2022.
Y. Gunawan, A. S. Firmansyah, A. Mubarok, B. Subaeki, and K. Manaf, “Implementasi Algoritma Decision Tree untuk Klasifikasi Kemampuan Membaca Al-Qur’an dengan Metode Tahsin,” Journal of Informatics, vol. 10, no. 1, 2025.
Bila bermanfaat silahkan share artikel ini
Berikan Komentar Anda terhadap artikel Implementasi Algoritma K-Means Clustering untuk Identifikasi Lokasi Strategis Coffee Shop
ARTICLE HISTORY
How to Cite
Issue
Section
Copyright (c) 2025 Lahuri Gofarana Rohman, Cecep Nurul Alam, Beki Subaeki
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (Refer to The Effect of Open Access).
