Iqbal Kharisudin, Putri Dea Al Arista Sari, Putriaji Hendikawati
Spatial clustering, a subset of clustering influenced by spatial location, utilizes the Spatial 'K'luster Analysis by Tree Edge Removal (SKATER) method to transform spatial data into partitioned graphs. Indonesia's development challenges, marked by uneven growth and inequality, manifest in regions with limited access to infrastructure and basic services. Semarang Regency's Village Development Index (IPD) stands at 69.33, indicating a developmental phase. The IPD for basic health services mirrors this figure, while the infrastructure condition scores 53.08, both below the threshold of 75 and thus considered low. This study aims to categorize villages within Semarang Regency based on the dimensions of basic health services and infrastructure conditions, employing village potential data. Findings reveal spatial autocorrelation among the villages. In terms of health services, the optimal clustering yields three groups: Cluster 1 encompasses 231 villages with inadequate health services; Cluster 2 includes two villages rated as good; and Cluster 3 comprises two villages deemed fairly good. Economic infrastructure clustering also results in three groups: Cluster 1 contains 232 villages with deficient economic infrastructure; Cluster 2 has two villages with moderately good infrastructure; and Cluster 3 consists of 1 village with good infrastructure. Energy infrastructure analysis identifies three clusters as well, with Cluster 1 including 221 villages with robust energy infrastructure, Cluster 2 with eight villages categorized as poor, and Cluster 3 with six villages classified as good. Information and communication infrastructure clustering discern two groups: Cluster 1, with 177 villages in the poor category, and Cluster 2, with 58 villages in the good category. Lastly, public housing infrastructure clustering forms two groups: Cluster 1, with 234 villages rated as good, and Cluster 2, with one village rated as below average. © 2025 Author(s).
Statistics and Data Science, Faculty of Mathematics and Natural Sciences, Universitas Negeri Semarang, Semarang, Indonesia; Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Negeri Semarang, Semarang, Indonesia; Applied Statistics and Computation, Faculty of Mathematics and Natural Sciences, Universitas Negeri Semarang, Semarang, Indonesia
