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@article{J.Gauss39329, author = {Ariani Fitri Purba and Mustafid Mustafid and Puspita Kartikasari}, title = {PENERAPAN ALGORITMA k-PROTOTYPE UNTUK PENGELOMPOKAN DESA DI KABUPATEN BEKASI BERDASARKAN INFRASTRUKTUR DIGITAL}, journal = {Jurnal Gaussian}, volume = {13}, number = {2}, year = {2025}, keywords = {Digital Infrastructure; Mixed Type Data; Cluster Analysis; k-Prototype Algorithm; Average Silhouette Width}, abstract = {Grouping villages in Bekasi Regency is necessary as a planning and evaluation material for government program targets, especially in digital transformation efforts. The goal is to find out which villages are prioritized based on the characteristics of digital infrastructure. Thus, grouping villages in Bekasi Regency based on digital infrastructure needs to be done to support the success of digital transformation efforts. The analysis that can be used to group a village is cluster analysis. The clustering method used in this research is the k-Prototype algorithm using the value of = 1, 2, 3, ..., and 10. The k-Prototype algorithm is a clustering method that can handle mixed type data, namely numeric and categorical types and large data. The k-Prototype algorithm has the advantage that the algorithm is less complex and better than hierarchy-based algorithms. Based on the results of analysis, the optimal number of groups formed was four groups with an Average Silhouette Width value of 0,505. Group 3, which consists of 9 villages, is the best group based on digital infrastructure characteristics, while group 1, which consists of 41 villages, has the lowest average cellular phone communication service operator and is dominated by villages that do not have internet access and internet facilities at the village office. In addition, group 1 has the most villages with weak cellular phone signals compared to the other groups.}, issn = {2339-2541}, pages = {479--489} doi = {10.14710/j.gauss.13.2.479-489}, url = {https://ejournal3.undip.ac.id/index.php/gaussian/article/view/39329} }
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