Ardiani, Ardia Eva and Arif, Farah Yusnaida (2024) Analisis Geospasial dan Pengelompokan Wilayah Kabupaten/Kota di Jawa Timur Berdasarkan Indikator Sosial-Ekonomi dan Pendidikan. Project Report (Praktek Kerja Lapang dan Magang). UPN Veteran Jawa Timur.
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Abstract
High poverty levels and low educational attainment present significant challenges that affect the quality of life for the people of East Java. According to BPS data, the poverty rate is 10.35%, while nearly half of the population aged 10 years and above has only completed education up to elementary school or lower. This condition highlights the close relationship between socio-economic indicators and education, which exacerbates social inequality. Therefore, a deeper analysis of the distribution patterns and regional characteristics is needed to formulate more effective policies. This study uses the Hierarchical Clustering method, specifically Agglomerative Hierarchical Clustering, to group districts and cities in East Java based on socio-economic and education indicators. This method clusters regions based on similar characteristics, forming a hierarchical structure that allows for more in-depth analysis of patterns and relationships among regions. The results of this analysis aim to provide a clearer picture of the socio-economic and educational conditions, as well as support evidence-based policy-making. Additionally, geospatial analysis is used to visualize the distribution of socio-economic and educational indicators in thematic maps. This visualization is expected to provide a more comprehensive understanding of the spread of socio-economic and educational factors across the region. The research results are expected to offer a better understanding of the characteristics of each region and provide strategic recommendations that can be used in development planning in East Java.
| Item Type: | Monograph (Project Report (Praktek Kerja Lapang dan Magang)) | ||||||||
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| Subjects: | H Social Sciences > HA Statistics | ||||||||
| Divisions: | Faculty of Computer Science > Departemen of Data Science | ||||||||
| Depositing User: | Ardia Eva Ardiani | ||||||||
| Date Deposited: | 08 Jul 2026 07:50 | ||||||||
| Last Modified: | 08 Jul 2026 07:50 | ||||||||
| URI: | https://repository.upnjatim.ac.id/id/eprint/54825 |
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