District-Level Geospatial and Socioeconomic Dataset for Renewable-Energy Access Prioritization Across Indonesia's 514 Regencies

Description

This data article describes a district-level dataset covering all 514 Indonesian regencies (kabupaten/kota), assembled to support renewable-energy access prioritization and to reproduce the models reported in a companion study on land suitability for renewable energy development. The dataset merges eleven public data sources spanning administrative boundaries, the official tertinggal (underdeveloped) designation, socioeconomic indicators, nighttime-lights radiance, elevation, land cover, solar and weather variables, wind speed, and road infrastructure into a single table of 514 rows and 45 columns, with no missing values after zonal-statistics extraction and district-name matching. Building the dataset required resolving three verified name-matching problems across sources: a "Kota" stripping bug that had silently merged 26 kabupaten/kota pairs, 26 districts carrying two Statistics Indonesia (BPS) codes after Papua's 2022 administrative split, and letter-spaced district names in raw BPS records. Every non-exact name match is retained as an explicit column so downstream users can audit or filter the crosswalk themselves. The dataset supports research on energy poverty, renewable-resource suitability, and explainable machine learning for sub-national development policy, and the boundary-crosswalk methodology is reusable for any project joining Indonesian administrative data across sources.

Institutions

• Multimedia Nusantara University

  Banten, Tangerang

Categories

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