A Predictive Model for Urban Agglomeration Development in East Kalimantan Province Using Cluster Analysis
DOI:
https://doi.org/10.32493/jtsi.v8i2.54092Keywords:
Urban Agglomerations, DBSCAN Algorithm, Geographic Information Systems, Urban GrowthAbstract
The development of the new capital in East Kalimantan Province is guided by agglomeration as a strategic
framework, aiming to reduce regional disparities and maintain a balance between the central area and its
surrounding regions. This strategy is reinforced by the development of the transportation sector, which
provides the foundation for both geographic and administrative connectivity across regions. The
concentration of activities, including industry, trade, government, and infrastructure, is a key driver of
economic growth and regional development. This study employs a quantitative approach supported by
Geographic Information Systems (GIS), specifically the DBSCAN algorithm, using a road network
shapefile (.shp) as the primary data. The results of the analysis show that Bontang, Balikpapan, and
Samarinda City function as the trigger nodes driving regional activity concentration and growth, with
development trends expanding towards the north and west. Predictive analysis using DBSCAN at distances
of 1,600–2,400 meters indicates that 9 out of 10 regions in East Kalimantan Province have formed new
growth centers, except that Mahakam Ulu Regency has not yet shown signs of urban agglomeration.
References
Afrianto, F. (2023). Fractal Dimensions Analysis of Urban Agglomeration at Road Intersections in Metropolitan Malang Raya. IOP Conference Series: Earth and Environmental Science, 1186(1). https://doi.org/10.1088/1755-1315/1186/1/012010
Aini, A. F. (2022). Analisis Analisis Dampak Urbanisasi Terhadap Pertumbuhan Ekonomi Kota Surabaya. Journal Economics and Strategy, 3(2), 60–67. https://doi.org/10.36490/jes.v3i2.425
Alexander, H. B. (2024). Transportasi Berkelanjutan IKN Diwacanakan Tiru Aglomerasi Jadebotabek. Www.Kompas.Com.
Badan Perencanaan Pembangunan Nasional. (2021). Handbook of the Relocation of Indonesia’s Capital City. Kementrian PPN/Bappenas, 1–29.
Birant, D., & Kut, A. (2007). ST-DBSCAN: An algorithm for clustering spatial-temporal data. Data and Knowledge Engineering, 60(1), 208–221. https://doi.org/10.1016/j.datak.2006.01.013
Budiman, S. A. D., Safitri, D., & Ispriyanti, D. (2016). Perbandingan Metode K-Means Dan Metode Dbscan Pada Pengelompokan Rumah Kost Mahasiswa Di Kelurahan Tembalang Semarang. Jurnal Gaussian, 5, 757–762. http://ejournal-s1.undip.ac.id/index.php/gaussian
Clark, P. J., & Evans, F. C. (1954). Distance to Nearest Neighbor as a Measure of Spatial Relationships in Populations. Ecology, 35(4), 445–453. https://doi.org/10.2307/1931034
ESRI. (n.d.). What is a z-score? What is a p-value? Retrieved November 25, 2025, from https://pro.arcgis.com/en/pro-app/latest/tool-reference/spatial-statistics/what-is-a-z-score-what-is-a-p-value.htm
Ester, M., Kriegel, H., Xu, X., & Miinchen, D.-. (1996). A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise.
Kalpana, L. D. C. H. N., Abenayake, C., Jayasinghe, A., Mahanama, P. K. S., & Sanjaya, N. (2021). A novel approach to measure the pattern of urban agglomeration based on the road network. International Journal of Sustainable Development and Planning, 16(2), 251–262. https://doi.org/10.18280/IJSDP.160205
Kharitonov, S. (2015). Nearest-neighbor distance method for the evaluation of distribution of different biological objects in plane or in line. https://doi.org/10.13140/RG.2.1.1733.0643
Kurniati, S. A., Rahayu, P., & Istanabi, T. (2022). Peri-Urbanisasi Dan Dinamika Perkembangan Kawasan Perkotaan Sekunder (Studi Kasus: Bosukawonosraten). Desa-Kota, 4(2), 167. https://doi.org/10.20961/desa-kota.v4i2.55247.167-180
Larasati, A. P., Rahman, B., & Kautsary, J. (2022). Pengaruh Perkembangan Perkotaan Terhadap Fenomena Pulau Panas (Urban Heat Island). Jurnal Kajian Ruang, 2(1), 35. https://doi.org/10.30659/jkr.v2i1.20469
Lavenia, R. (2024). 10 Tahun Jadi Daerah Otonom Baru, Pengamat Unmul Menilai Mahakam Ulu Kaltim Masih Dianaktirikan. Tribun Kaltim. https://kaltim.tribunnews.com/2024/07/17/10-tahun-jadi-daerah-otonom-baru-pengamat-unmul-menilai-mahakam-ulu-kaltim-masih-dianaktirikan
Muta’ali, L. (2025). Teori dan Konsep Economic Geography.
Qibti, M. H. M., & Hendarto, R. M. (2020). Analisis Spillover Effect Pertumbuhan Ekonomi antar Kabupaten / Kota Di Kawasan. Diponegoro Journal Of Economics, 9(4).
Riadhi, A. R., Aidid, M. K., & Ahmar, A. S. (2020). Analisis Penyebaran Hunian dengan Menggunakan Metode Nearest Neighbor Analysis. VARIANSI: Journal of Statistics and Its Application on Teaching and Research, 2(1), 46. https://doi.org/10.35580/variansiunm12901
Rijal, S., & Tahir, T. (2022). Analisis Faktor Pendorong Terjadinya Urbanisasi di Wilayah Perkotaan (Studi Kasus Wilayah Kota Makassar). Journal of Economic Education and Entrepreneurship Studies, 3(1), 262–276.
Surya, B., Salim, A., Hernita, H., Suriani, S., Menne, F., & Rasyidi, E. S. (2021). Land Use Change, Urban Agglomeration, and Urban Sprawl: A Sustainable Development Perspective of Makassar City, Indonesia. In Land (Vol. 10, Issue 6, p. 556). https://doi.org/10.3390/land10060556
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