Abstract
Understanding the population data of a region is crucial for policy development and strategic planning. East Java Province, the second-largest province in Indonesia, has undergone significant population growth from 2021 to 2023. Uneven growth poses challenges in resource and infrastructure management. The K-Means algorithm clusters population data into several groups based on specific characteristics. The Elbow method is used to determine the optimal number of clusters, ensuring the accuracy of the analysis. This research aims to analyze and cluster the population distribution in each city in East Java Province, providing a more detailed and accurate depiction. The research findings reveal three significant clusters. Cluster 0 includes 21 towns, Cluster 1 comprises 4, and Cluster 2 encompasses 13. These findings have important implications for targeted development policy formulation at the city level in East Java Province. Additionally, this study contributes to the development of demographic analysis and population management, using valid methods and consistent results between RapidMiner and manual calculations. In conclusion, this research provides a solid foundation for more effective development policy formulation in East Java Province, offering essential information for sustainable population management.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
