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Penyusunan Indeks Resiliensi Ekonomi Kecamatan Berbasis Official Statistics dengan Metode Composite Indeks untuk Mendukung Perencanaan Pembangunan di Kabupaten Madiun Eka Della Faradisa
Seminar Nasional Official Statistics Vol 2026 No 1 (2026): Seminar Nasional Official Statistics 2026
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2026i1.2665

Abstract

Economic resilience is an important indicator for assessing the ability of a region to withstand, adapt to, and recover from various economic pressures. Therefore, measuring economic resilience is essential for supporting more targeted development policy formulation. This study aims to develop an economic resilience index at the subdistrict level based on official statistics using the composite index method in Madiun Regency. The study covers 15 subdistricts and nine indicators grouped into three dimensions: economic, human resource, and demographic. All indicators were normalized using the min- max method and aggregated using equal weighting to obtain dimension scores and a composite index. Resilience categories were determined using the quartile method (Q1–Q3) as category thresholds. The results show that the economic resilience index ranges from 0.274 to 0.878, with Mejayan Subdistrict having the highest index value of 0.878 and Balerejo Subdistrict having the lowest index value of 0.274. The index classifies the 15 subdistricts into four categories: low, with 4 subdistricts; moderate, with 4 subdistricts; high, with 3 subdistricts; and very high, with 4 subdistricts. These findings indicate disparities in economic, human resource, and demographic capacities across subdistricts. Subdistricts with low resilience should be prioritized for development interventions through strengthening economic activities, improving human resource quality, and expanding supporting facilities according to local characteristics. The resulting index can serve as a supporting instrument for mapping regional conditions and determining data-driven development priorities in Madiun Regency.