Implementation of K-Means and DBSCAN algorithms: A Bibliometric Review

DOI

10.2991/978-94-6463-618-5_21How to use a DOI?

Keywords

DBSCAN; K-Means; Scopus; BIBLIOMETRIC

Abstract

K-Means and DBSCAN algorithms belong to Supervised Learning, they are one of the popular clustering algorithms used in Machine Learning/Data mining that do not need to be labeled. Both algorithms are always compared with other algorithms to find superior clusters. Bibliometric was used as a research methodology with stages using the Prisma framework, namely identification, screening, eligibility, included. The focus of this research is to find scientific articles related to the K-Means and DBSCAN algorithms. Units of analysis collected through Scopus. All articles were downloaded from 2014 to 2024, resulting in 170 scientific articles. The inspection was conducted in several stages, and the overall result was 104 articles. After careful consideration, the total number of articles considered eligible was 65. There are at least four major themes that discuss the use of K-Means and DBSCAN algorithms, namely the infrastructure, transportation, health, and education sectors. Of the four fields, health and transportation are most suitable for the implementation of the K-Means and DBSCAN algorithms. In addition, researchers use K-Means and/or DBSCAN algorithms to compare with other algorithms, the goal is to find the best clustering algorithm.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

TY  - CONF
AU  - Fahmi Reza Ferdiansyah
AU  - Rikky Wisnu Nugraha
AU  - Rudy Sofian
AU  - Heri Purwanto
AU  - Didin Saepudin
AU  - Edi Andriansyah
PY  - 2024
DA  - 2024/12/29
TI  - Implementation of K-Means and DBSCAN algorithms: A Bibliometric Review
BT  - Proceedings of the Widyatama International Conference on Engineering 2024 (WICOENG 2024)
PB  - Atlantis Press
SP  - 192
EP  - 202
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-618-5_21
DO  - 10.2991/978-94-6463-618-5_21
ID  - Ferdiansyah2024
ER  -