Customer Clustering Using the K-Means Clustering Algorithm in the Top 5 Online Marketplaces in Indonesia

Andara Rahma Danurisa, Jerry Heikal

Abstract


Tokopedia, Shopee, Lazada, Bukalapak and Orami are 5 marketplaces in Indonesia that focus on shopping activities using applications. The number of customer visits is very volatile so it is difficult to determine customer interest in purchasing a product. The purpose of this study is to identify the characteristics, product categories and merchant in the top 5 online marketplaces in Indonesia using the K-Means Clustering algorithm. There are three variables, namely customer characteristics, product categories, and merchant. Data processing is assisted by the application of SPSS V.25. Loyal customers of marketplace are cluster 10. In addition, the marketplace also has loyal customers in cluster 5. Loyal customers of marketplace the Shopee cluster 8. Then, marketplace also has loyal customers in 6 clusters, including cluster 2, cluster 3, cluster 4, cluster 6, cluster 7, and cluster 9. Loyal customers of marketplace the Lazada cluster 6. However, in cluster 6, the marketplace still excels as marketplace that is often used in cluster 6. The loyal customers of marketplace the Bukalapak cluster 7 However, in cluster 7, marketplace still excels as marketplace that is often used in cluster 7. Orami marketplace loyal customers are cluster 1.


Keywords


marketplace; data mining; customer clasterization; clustering, K-Means.

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References


Agrawal, A., & Gupta, H. (2013). Global K-Means (GKM) Clustering Algorithm: A Survey. International Journal of Computer Applications, 79(2), 20-24.

Ahmar, A.S., Napitupulu, D., Rahim, R., Hidayat, R., Sonatha, Y., & Azmi, M. (2018). Using K-Means Clustering to Cluster Provinces in Indonesia. Journal of Physics: Conference Series, 1(1), 1-7.

Alfina, T., Santosas, B., & Barakbah, A.R. (2012). Analisa Perbandingan Metode Hierarchical Clustering, K-Means dan Gabungan Keduanya dalam Cluster Data (Studi Kasus: Problem Kerja Praktek Jurusan Teknik Industri ITS). Jurnal Teknik, 1(9), 521-525.

Arikunto, S. (2002). Prosedur Penelitian Suatu Pendekatan Praktik. Jakarta. Rineka Cipta.

------------. (2010). Prosedur Penelitian Suatu Pendekatan Praktik. Jakarta. Rineka Cipta.

Asnawi, N., & Masyhuri. (2009). Metodologi Riset Dan Pemasaran. Malang. UIN Malang Press Anggota IKAPI.

Badan Pusat Statistik. (2022). Jumlah Penduduk Hasil Proyeksi Menurut Provinsi dan Jenis Kelamin. https://www.bps.go.id/indicator/12/1886/1/jumlah-penduduk-hasil-proyeksi-menurut-provinsi-dan-jenis-kelamin.html.

Bang, J., Cho, Y., & Kim, M.S. (2020). Getting Business Insights through Clustering Online Behaviors. Hindawi Publishing Coporation, 16(11), 1-8.

Bangoria, B., Mankad, N., & Pambhar, V. (2013). A survey on Efficient Enhanced K-Means Clustering Algorithm. International Journal for Scientific Research & Development (IJSRD), 1(9), 1756-1758.

Berahmana, R.W.B.S., Mohammed, F.A., & Chairuang, K. (2020). Customer Segmentation Based on RFM Model Using K-Means, K-Medoids, and DBSCAN Methods. Lontar Komputer, 11(1), 32-43.

Cholid, N., & Achmadi, A. (2017). Metodologi Penelitian. Jakarta. Bumi Aksara.

Dash, R., Mishra, D., Rath, A.K., & Acharya, M. (2010). A Hybridizied K-Means Clustering Approach For High Dimensional Dataset. International Journal of Engineering, Science and Technology, 2(2), 59-66.

Evanita, F.M., Cholisodin, I., Adinugroho, S. (2021). Pengelompokan Toko E-commerce Shopee berdasarkan Reputasi Toko menggunakan Metode Clustering K-Medoids. Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 5(3), 1230-1236.

Ezenkwu, C.P., Ozuomba, S., & Kalu, C. (2015). Application of K-Means Algorithm for Efficient Customer Segmentation: A Strategy for Targeted Customer Services. International Journal of Advanced Research in Artificial Intelligence (IJARAI), 4(10), 40-44.

Ghozali, I. (2011). Aplikasi Analisis Multivariate Dengan Program IBM SPSS19 Cet.-5. Semarang. Badan Penerbit Universitas Diponegoro.

Haraty, R.A., Dimishkieh, M., & Masud, M. (2015). An Enhanced k-means Clustering Algorithm for Pattern Discovery in Healthcare Data. International Journal of Distributed Sensor Networks, 20(15), 1-11.

Iprice Insights. (2022). Peta E-Commerce Indonesia. https://iprice.co.id/insights/mapofecommerce.

Kawa, A., & Walesiak, M. (2019). Marketplace As A Key Actor In E-Commerce Value Networks. Scientific Journal of Logistics, 15(4), 521-529.

Kotler, P. & Armstrong, G. (2007). Dasar-dasar Pemasaran Edisi Ke-9. Jakarta.PT Indeks.

Kurniawan, A.R. (2014). Total Marketing. Yogyakarta. Kobis.

Larose, D.T. (2005). Discovering Knowledge In Data: An Introduction to Data Mining. New Jersey. John Willey & Sons. Inc.

Madhulatha, Sonny T. (2012). An Overview On Clustering Methods. IOSR Journal of Engineering, 2(4), 719-725.

Mahmudan, A. (2020). Clustering of District or City in Central Java Based Covid-19 Case Using K-Means Clustering. Jurnal Matematika, Statistika, & Komputasi (JMSK), 17(1), 1-13.

Marwanto, A. (2015). Marketing Sukses. Yogyakarta. Kobis.

Matz, A. (2020). Customer Loyalty Clustering Model Using K-Means Algorithm with LRIFMQ Parameters. Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi, 5(2), 54-61.

Nagari, S.S., & Inayati, L. (2020). Implementation of Clustering Using K-Means Method to Determine Nutritional Status. Jurnal Biometrika dan Kependudukan, 9(1), 62-68.

Nainggolan, R., & Purba, E. (2020). Cluster Analysis of Online Shop Product Reviews Using K-Means Clustering. International Journal of Entrepreneurship and Business Development (IJEBD), 3(2), 142-150.

Nainggolan, R., & Tobing, F.A.T. (2020). Analisis Cluster dengan Menggunakan K-Mean untuk Pengelompokkan Online Customer Reviews (OCR) pada Online Marketplace. Jurnal Methodika, 6(1), 1-5.

Nasron, U.A., & Habibi, M. (2020). Analysis of Marketplace Conversation Trends On Twitter Platform Using K-Means. E-journal STTA, 9(1), 50-61.

Ndehedehe, C., Simeon, O., & Ekpa, A. (2013). Spatial Data Mining Using K-Means Analysis: A Case Study of Uyo Capital City, Nigeria. International Journal of Advanced Research, 1(7), 6-15.

Ningrum, P. A., et al. (2020). The Potential of Poverty in the City of Palangka Raya: Study SMIs Affected Pandemic Covid 19. Budapest International Research and Critics Institute-Journal (BIRCI-Journal) Volume 3, No 3, Page: 1626-1634

Nugraha, S.M. (2013). Pengaruh Fasilitas Wisata Terhadap Kepuasan Berkunjung di Kawasan Wisata Situ Gede Kota Tasikmalaya. Sripsi. Bandung. Universitas Telkom.

Nurmalasari, Mukhayaroh, Marlina, dkk. (2020). Implementation of Clustering Algorithm Method for Customer Segmentation. Journal of Computational and Theoretical Nanoscience, 17(2-3), 1-9.

Ong, J.O. (2013). Implementasi Algoritma K-Means Clustering Untuk Menentukan Strategi Marketing President University. Jurnal Ilmiah Teknik Industri, 12(1), 10-20.

Priati & Fauzi, A. (2017). Data Mining dengan Teknik Clustering Menggunakan Algoritma K-Means pada Data Transaksi Superstore. Seminar Nasional Informatika dan Aplikasinya (SNIA), 27(9), 15-19.

Prihastomo, Y., Meyliana, Hidayanto, A.N., & Prabowo, H. (2018). The Key Success Factors In E-Marketplace Implementation: A Systematic Literature Review. International Conference on Information Management and Technology (ICIMTech), 1(1), 443-448.

Priyatno, D. (2014). SPSS 22 Pengolahan Data Terpraktis. Yogyakarta. CV. Andi Offset.

Rahmadi, Y., P.Y.A., & H.M.A. (2015). Pengembangan Modul Freemium Aplikasi Tel-US (Telkom University Store) Menggunakan Metode Iterative Incremental dan Framework Laravel. E-Proceeding of Engineering, 2(2), 5437-5444.

Rahman, A., Suroyo, H. (2021). Analisis Data Produk Elektronik di E-Commerce dengan Metode Algoritma K-Means Menggunakan Python. Journal of Advances in Information and Industrial Technology (JAIIT), 3(2), 11-18.

Rahmawati, L., Sihwi, S.W., & Suryani, E. (2016). Analisa Clustering Menggunakan Metode K-Means dan Hierarchical Clustering (Studi Kasus: Dokumen Skripsi Jurusan Kimia, FMIPA, Universitas Sebelas Maret). Jurnal Teknologi Informasi ITSmart, 3(2), 66.

Rezaeian, A., Shokouhyar, S., & Dehghan, F. (2016). Measuring Customers Satisfaction of E-Commerce Sites Using Clustering Techniques: Case Study of Nyazco Website. International Journal of Management, Accounting and Economics, 3(1), 61-74.

Ridwan. (2008). Belajar Mudah Penelitian Untuk Guru, Karyawan, dan Penelitian Terbuka. Bandung. Alfabeta.

Saleh, A., Mujahiddin. (2020). Challenges and Opportunities for Community Empowerment Practices in Indonesia during the Covid-19 Pandemic through Strengthening the Role of Higher Education. Budapest International Research and Critics Institute-Journal (BIRCI-Journal). Volume 3, No 2, Page: 1105-1113.

Santosa, B. (2007). Data Mining Teknik Pemanfaatan Data untuk Keperluan Bisnis. Yogyakarta. Graha Ilmu.

Santoso, D.R., Handayani, P.W., & Azzahro, F. (2022). The Resistance to Adopting Online Marketplace: The Influence of Perceived Risk and Behavioral Control of Small and Medium Enterprises in Indonesia. CommIT Journal, 16(1), 53-68.

Sarwono, J. (2006). Analisis Data Penelitian Menggunakkan SPSS. Yogyakarta. Andi Offset.

Setiawan, R. (2021). Flowchart Adalah: Fungsi, Jenis, Simbol, dan Contohnya. https://www.dicoding.com/blog/flowchart-adalah/

Siagian, R., Sirait, P., & Halima, A. (2021). E-Commerce Customer Segmentation Using K-Means Algorithm and Length, Recency, Frequency, Monetary Model. JITE, 5(1), 21-30.

Sihombing, E. H., Nasib. (2020). The Decision of Choosing Course in the Era of Covid 19 through the Telemarketing Program, Personal Selling and College Image. Budapest International Research and Critics Institute-Journal (BIRCI-Journal) Volume 3, No. 4, Page: 2843-2850.

Sipayung, E.M., Maharani, H., & Paskhadira, B.A. (2017). Designing Customer Target Recommendation System Using K-Means Clustering Method. IJITEE, 1(1), 1-7.

Soleman, C.D.O., Pramaita, N., & Sudarma, M. (2020). Classification of Loyality Customer Using K-Means Clustering, Studi Case: PT. Sucofindo (Persero) Denpasar Branch. International Journal of Engineering and Emerging TECHNOLOGY, 5(2), 160-167.

Sugiyono. (2012). Metode Penelitian Kuantitatif, Kualitatif, dan R&D. Bandung. Alfabeta.

------------. (2013). Metode Penelitian Bisnis (Pendekatan Kuantitatif, Kualitatif, dan R & D). Bandung. Alfabeta.

------------. (2015). Metode Penelitian Kuantitatif, Kualitatif, dan R&D. Bandung. Alfabeta.

------------. (2019). Metode Penelitian Kuantitatif, Kualitatif, dan R&D. Bandung. Alfabeta.

Sujarweni, V., & Endrayanto, P. (2012). Statistika Untuk Penelitian. Yogyakarta. Graha Ilmu.

Sunyoto, D. (2014). Dasar-dasar Manejemen Pemasaran. Yogyakarta. CAPS.

Tan, P.N., Steinbach, M., & Kumar, V. (2006). Introduction to Data Mining, Cluster Analysis: Basic Concepts and Algorithms. Boston. Addison Wesley.

Umar. (2011). Metode Penelitian Untuk Skripsi dan Tesis Bisnis. Jakarta. PT. Raja Grafindo Persada.

Yaumi, A.S., Zulfiqkar, Z., & Nugroho, A. (2020). Klasterisasi Karakter Konsumen Terhadap Kecenderungan Pemilihan Produk Menggunakan K-Means. Journal of Information Technology and Computer Science (JOINTECS), 5(3), 195-202.




DOI: https://doi.org/10.33258/birci.v5i3.6450

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