Pemetaan Ketimpangan Digital Antarprovinsi di Indonesia Berdasarkan Indikator Akses dan Penggunaan Teknologi Menggunakan Algoritma K-Means
DOI:
https://doi.org/10.63822/xaz20569Keywords:
digital inequality; K-Means; internet access; digital divide; provincial clusteringAbstract
Digital inequality remains a challenge in ensuring equitable access to and use of information and communication technology across regions in Indonesia. This study aimed to map digital inequality among 38 Indonesian provinces in 2024 using the K-Means clustering algorithm. Secondary data obtained from Statistics Indonesia (BPS) were analyzed using three indicators: the percentage of the population accessing the internet, owning or controlling mobile phones, and using computers. The data were standardized using Z-score transformation, while the optimal number of clusters was evaluated using the Elbow Method and Silhouette Score. The results showed that two clusters provided the optimal configuration, with a Silhouette Score of 0.7457. Cluster 0 consisted of 36 provinces, with average internet access, mobile phone ownership or control, and computer use of 70.84%, 69.08%, and 12.09%, respectively. Cluster 1 consisted of Central Papua and Highland Papua, with substantially lower averages of 17.74%, 24.73%, and 2.98%, respectively. Principal Component Analysis further supported the clustering structure, with two principal components explaining 98.89% of the total variance. These findings demonstrate a pronounced multidimensional digital gap and highlight the need for more targeted digital development policies in disadvantaged regions.
References
Azizah, F., Pramesti, W., & Fitriani, F. (2022). Analisis Education Mapping Terkait Pengelompokkan Kesenjangan Pembangunan Pendidikan Menurut Provinsi di Indonesia. MUST : Journal of Mathematics Education, Science and Technology, 7(2), 130–138. https://doi.org/10.30651/must.v7i2.11097
Hanna, N. K. (2010). An ICT-Transformed Government and Society (pp. 1–25). Springer, New York, NY. https://doi.org/10.1007/978-1-4419-1506-1_1
Kartiasih, F., Nachrowi, N. D., Wisana, I. D. G. K., & Handayani, D. (2022). Inequalities of Indonesia’s regional digital development and its association with socioeconomic characteristics: a spatial and multivariate analysis. Information Technology for Development, 1–30. https://doi.org/10.1080/02681102.2022.2110556
Koswara, A., & Koswara, A. (2025). Digital Inequality: E-Commerce Access and Its Implications for Underdeveloped Regions in Indonesia. 2(1), 1–14. https://doi.org/10.65119/jspds.v2i1.20
Liu, H., Chen, J.-C., Dy, J. G., & Fu, Y. (2023). Transforming Complex Problems Into K-Means Solutions. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45, 9149–9168. https://doi.org/10.1109/TPAMI.2023.3237667
Liu, H., Fang, C., & Sun, S. (2017). Digital inequality in provincial China. Environment and Planning A, 49(10), 2179–2182. https://doi.org/10.1177/0308518X17711946
Loyola, V. F., & García, J. R. (2025). Spatial Patterns of ICT Access in Argentine Households: Regional and Departmental Analysis (2022). Urban Science. https://doi.org/10.3390/urbansci9120537
Novianto, M. D., Sumantri, G., & Prihastuti, P. P. (2023). Clustering Provinsi di Indonesia Berdasarkan Indeks Pembangunan Teknologi Informasi dan Komunikasi Menggunakan K-Medoids. Emerging Statistics and Data Science Journal, 1(3), 320–331. https://doi.org/10.20885/esds.vol1.iss.3.art39
Parera, N. M., Dewi, C., & Purnomo, H. D. (2025). Mapping The Digital Divide: A Spatial Clustering Analysis of E-Money Adoption and Regional Poverty in Indonesia. 1–4. https://doi.org/10.1109/icast68191.2025.11300019
Pick, J. B., Ren, F., & Sarkar, A. (2024). Digital Inequalities in China in 2020: Spatial and Multivariate Analysis. Applied Sciences, 14(13), 5385. https://doi.org/10.3390/app14135385
Shaw, K. (2025). Levels of digital divide: A Review Literature. https://doi.org/10.5281/zenodo.17227871
Yudistira, M. R., & Maulana, R. I. (2025). Pengelompokan Kabupaten/Kota di Indonesia Berdasarkan Indikator Teknologi Informasi dan Komunikasi Menggunakan Metode K-Means. Prosiding Seminar Nasional Official Statistics. https://doi.org/10.34123/semnasoffstat.v2025i1.2424
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Ulfa Pauziah (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
