| Autor: |
Bagus Kristomoyo Kristanto, Syntia Widyayuningtias Putri Listio, Mukhlis Amien, Panji Iman Baskoro |
| Jazyk: |
English<br />Indonesian |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Journal of Applied Informatics and Computing, Vol 8, Iss 1, Pp 221-225 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2548-6861 |
| DOI: |
10.30871/jaic.v8i1.8138 |
| Popis: |
In the context of retail distribution, this study employs recursive K-means clustering on retail sales data to optimize clusters of nearest-distance stores for salesperson route recommendations. This approach addresses the stochastic salesperson problem by generating effective routes, enhancing cost reduction, and improving service efficiency. The recursive K-means algorithm dynamically adjusts to continuous changes in store numbers, locations, and transaction data. Consequently, this research successfully developed a model that automatically re-clusters the data with each change, providing continuously updated and effective store recommendations. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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