APPLICATION OF K-MEANS ALGORITHM FOR CLASSIFICATION OF BENINESE MUNICIPALITIES ACCORDING TO THEIR DIGITAL DEVELOPMENT PROFILE
- Doctoral School of Engineering Sciences (EDSI), University of Abomey-Calavi (UAC), Benin.
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Background: Optimizing digital territorial development policies requires a thorough understanding of municipal digital profiles and their heterogeneity. This study explores the application of the K-Means clustering algorithm to categorize the 77 Beninese municipalities according to their digital development profile using comprehensive data from the foundational Decision Support System (DSS)described in our companion study.
Objective: To develop an innovative methodological approach for analyzing territorial digital disparities and establish municipal typologies to optimize digital territorial planning policies.
Methods: Based on a standardized 45-indicator framework across multiple thematic domains collected through our Decision Support System, this research applies K-Means clustering with optimal cluster determination through silhouette analysis. The dataset comprises 20,790 data points providing robust foundation for unsupervised learning analysis.
[Narcisse Arsene Dagba, Aziz Saibou and Theophile Aballo (2025); APPLICATION OF K-MEANS ALGORITHM FOR CLASSIFICATION OF BENINESE MUNICIPALITIES ACCORDING TO THEIR DIGITAL DEVELOPMENT PROFILE Int. J. of Adv. Res. (Aug). 969-976] (ISSN 2320-5407). www.journalijar.com
Doctorant, École Doctorale des Sciences de l’Ingénieur, Université d’Abomey-Calavi, Bénin
Benin
