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All Journal JURIKOM (Jurnal Riset Komputer) Journal of Computer System and Informatics (JoSYC) Jurnal Manajemen Informatika Jayakarta Jurnal Sains dan Teknologi Widyaloka (JSTekWid) Jurnal Informatika dan Teknologi Informasi Journal of Engineering, Technology and Computing (JETCom) Journal of Mathematics and Technology (MATECH) Sistem Komputer & Teknologi Intelegensi Artifisial (SIKOMTIA) Eksplorasi Teknologi Enterprise & Sistem Informasi (EKSTENSI) Jurnal Information System
Sharyanto Sharyanto
Univeristas Bung Karno
Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Transportation

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Journal : JURIKOM (Jurnal Riset Komputer)

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Penerapan Data Mining Untuk Menentukan Segmentasi Pelanggan Dengan Menggunakan Algoritma K-Means dan Model RFM Pada E-Commerce Sharyanto Sharyanto; Dwi Lestari
JURIKOM (Jurnal Riset Komputer) Vol 9, No 4 (2022): Agustus 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i4.4525

Abstract

The growth of technology has a big impact on life, one of which is the use of the internet. In Indonesia, internet usage has increased every year, this has an impact on changes in the buying and selling process carried out by the community. The basic reason caused by these changes is a wider market reach. So it can be said that the presence of the online market is a positive impact caused by the development of these technologies. E-Commerce is a process of buying and selling transactions and also leasing services that are carried out by utilizing internet technology that is already available on certain media. On this basis, business actors in E-Commerce should have their own characteristics that are easily recognized by consumers. It is necessary for business people to segment potential customers. However, the problem of customer segmentation has become a problem in itself for business actors, this is due to the lack of knowledge of how to segment the customers. Data mining is a process that can be done to solve problems. With data mining the process is carried out by processing the dataset and generating new information. In data mining itself, there are several completion processes, namely the K-Means algorithm for the clustering process and the RFM model for segmentation analysis. The results obtained are that there are 4 customer segments. This can be seen from the testing process carried out from K = 2 to K = 5, in the K = 4 test the most optimal BDI value is 0.6788
Co-Authors Achmad Rizki Susanto Alexius Ulan Bani Alya Azhar Fauziah Ari Tri Anggoro Bagas Rizky Perdana Beranadus Gunawan Sudarsono Bernadus Gunawan Sudarsono Bernadus Gunawan Sudarsono Bernandus Gunawan Sudarsono Caesar Ratu Atika Didik Sumarsono Dwi Lestari Erlin Yunus Duha Fani Eli Zebua Farhan Wahyu Fahrizal Fauziyah Febrian Saputra Fifto Nugroho Hany Maria Valentine Hifzillah Hifzillah Indah Lestari Ishak Alexander Iskandar Zulkarnain Joko Saputro Joseph Joseph Muhamad Edi Susanto Muhamad Firmansyah Muhammad Lutfi Muhammad Rizal Muhammad Sahroni Oki Sefiana Puja Lestari Putri Sari Raditya Galih Whendasmoro Raditya Galih Whendasmoro Rio Budi Firmansyah Samuel Ramos Shouqi Denanto Siti Soleka Theo Gregorius P Tika Dwi Tama Triyono Andik Priyanto Yazid Ramadhan Zelvi Zanuar