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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Indonesia Symposium on Computing Indonesian Journal on Computing (Indo-JC) IJoICT (International Journal on Information and Communication Technology) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) eProceedings of Engineering
Mahmud Imrona
Universitas Telkom
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering

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Implementation of K-Means++ Algorithm for Store Customers Segmentation Using Neo4J Chaerudin, Arief; Murdiansyah, Danang Triantoro; Imrona, Mahmud
Indonesian Journal on Computing (Indo-JC) Vol. 6 No. 1 (2021): April, 2021
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2021.6.1.547

Abstract

In the era of data and information, data has become one of the most useful and desirable things. Data can be useful information if the data is processed properly. One example of the results of data processing in business is by making customer segmentation. Customer segmentation is useful for identifying and filtering customers according to certain categories. Analysis of the resulting segmentation can produce information about more effective target market, more efficient budget, more accurate marketing or promotion strategies, and much more. Since segmentation aims to separate customers into several categories or clusters, a clustering algorithm can be used. In this research, customer segmentation is carried out based on the value of income and value of expenditure. The categorization method that will be used for this research is to use the K-Means ++ algorithm which is useful for determining clusters of the given data. In this study, the implementation of K-Means ++ is carried out using Neo4J. Then in this research, a comparison of K-Means ++ and K-Means is carried out. The result obtained in this study is that K-Means ++ has a better cluster than K-Means in term of silhouette score parameter.
Co-Authors Abdulloh Azzam Aditya Arif Budiutama Andhika Pakarti Annisa Aditsania Arian Nurrifqhi Arief Budiman Arief Chaerudin Arman Dwi Jatmiko Bagus Gigih Adisalam Bambang Gito Raharjo Bambang Pudjoatmodjo Chaerudin, Arief Danang Junaedi Danang Triantoro Murdiansyah Dawam Dwi Jatmiko Suwawi Dini Handayani Eko Cahyo Pramulanto Eko Darwiyanto Erwin Budi Setiawan Fathurahman Alhikmah Fathurahman Alhikmah Feby Ali Dzuhri Fhira Nhita Hetti Hidayati Irma Palupi Izzatul Ummah Krisna Febri Prastika Ludwika Hermawan Luqman Arif M. Hady Setiawan M. Sofyan Bahrum Juniardi Nicodemus Nelwan Nur Rahmawati Nurul Ikhsan Putu Harry Gunawan Rachmad Ryan Feryal Rachmat Fahmi Aziz Rahma Sarsetyaning Utami Retno Novi Dayawati Ridwan Syahrani Ridwan Syahrani Rifaldi Rizqi Pratama Rohidi Rohidi Rudericus Andika Pramudya Salwa Salsabila Mansur Shaufiah . Shinta Yulia Puspitasari Sri Widowati Teguh Anshari Nugraha Theresya Margharetha Panjaitan Yanuar Firdaus Arie Wibowo Yuliant Sibaroni Yuwantoro Mukhlisin ZK Abdurahman Baizal