The Implementation of Fuzzy C-Means Algorithm to Analyze Based on Price and Sold Variables in Tokopedia

DOI

10.2991/978-94-6463-618-5_33How to use a DOI?

Keywords

Fuzzy C-Means; Clustering; Analyze

Abstract

Various studies suggest a correlation how much of the product has been sold and product price to make decisions about sales strategy. Tokopedia, an e-commerce corporation, maintains a sales database encompassing consumer behavior data. This data can be a valuable resource for vendors who wish to develop more effective sales strategies based on sales. Fuzzy C-Means (FCM) algorithms is frequently employed techniques to analyze with overlapping data such as dataset obtained from Tokopedia. The FCM method was implemented to analyze datasets from Tokopedia which is useful for making decisions related to sales strategies. FCM algorithms are regarded as good method in analyzing based on price and sold variables with evaluation score by Davies Bouldin Index is 0.8253028798553185.

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.

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TY  - CONF
AU  - Yuda Perwira
AU  - Viddi Mardiansyah
PY  - 2024
DA  - 2024/12/29
TI  - The Implementation of Fuzzy C-Means Algorithm to Analyze Based on Price and Sold Variables in Tokopedia
BT  - Proceedings of the Widyatama International Conference on Engineering 2024 (WICOENG 2024)
PB  - Atlantis Press
SP  - 309
EP  - 315
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-618-5_33
DO  - 10.2991/978-94-6463-618-5_33
ID  - Perwira2024
ER  -