Pengelompokan Kebutuhan Anggaran Negara Berdasarkan Indikator Ekonomi dan Kesehatan Menggunakan Fuzzy C-Means dan PCA - Fachrurrozi, Muhammad; Muhammad, Fadzli; Sitepu, Delvi Nur Ropiq; Pratama, Reksi Hendra (Universitas Bengkulu, 2024)
Clustering the national budgets based on the economic and health indicators is another strategic approach that has been used to improve the effective planning of budget allocation. In this study, FCM will be applied for clustering budget data based on economic and health indicators across the regions. To reduce high-dimensional data complexity, in this paper, pre-processing data analysis will be done using PCA. Basically, PCA works by reducing data dimensions through the extraction of major factors that provide the greatest contribution to the variance of the data, thereby making the process of clustering using FCM feasible. The results derived from the analysis will indicate that the integration of PCA into FCM derives more accurate and informative clustering results and helps policymakers in devising appropriate strategies for budget allocations. Consequently, such findings are envisioned as adding to the positive development of enhancing efficiency and effectiveness in national budget allocation.