EXPLORING REGIONAL DISPARITIES IN INTERNET SPEEDS: A K-MEANS CLUSTERING APPROACH FOR INDONESIA CITIES
Keywords:
Regional disparities in internet speeds, digital divide, urban-rural infrastructure, K-Means clustering analysisAbstract
This study aims to explore regional disparities in internet speeds across Indonesian cities using a K-Means clustering approach. Internet speed data, encompassing mobile and fixed broadband, were analyzed to identify patterns of internet speed distribution across regions. Using the elbow method, the optimal number of clusters was determined to be k=3, resulting in three clusters with distinct internet speed characteristics. Cluster 0 includes cities with high fixed broadband speeds but moderate mobile speeds, typically found in urban areas with well-established network infrastructure. Cluster 1 groups cities with low speeds in both mobile and fixed broadband, reflecting rural or remote areas with limited digital infrastructure. Cluster 2 comprises cities with high mobile internet speeds but low fixed broadband speeds, highlighting reliance on mobile networks due to limited fixed broadband infrastructure. These findings underscore the critical role of digital infrastructure, particularly Base Transceiver Station (BTS) density and fiber-optic network deployment, in shaping internet speeds. Internet speed disparities also have implications for unequal access to digital services, education, and economic opportunities. This analysis provides strategic insights for policymakers to prioritize investments in BTS and fixed broadband networks, especially in regions with low internet speeds, to support equitable connectivity and reduce the digital divide in Indonesia.
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Copyright (c) 2024 Qurrotul Ainia J.A, I Gede Suta Winaya, Achmad Dandi Firmansyah, Anak Agung Made Prayoga Ariswara, Emilianus Damar, Putu Sugiartawan
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