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All Journal International Journal of Advances in Data and Information Systems
Hanna Arini Parhusip
Department of Data Science, Satya Wacana Christian University, Indonesia
Computer Science & IT Electrical & Electronics Engineering

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­Forecasting and Spatial Analysis of Sustainable Development Goals 1 and 4 Using TabNet Harfely Leipary; Suryasatria Trihandaru; Hanna Arini Parhusip
International Journal of Advances in Data and Information Systems Vol. 7 No. 2 (2026): August 2026 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v7i2.1535

Abstract

This study applies the Tabular Neural Network (TabNet) to forecast and spatially analyze Sustainable Development Goals (SDGs) 1 and 4, providing evidence-based support for policymaking aligned with the United Nations 2030 Agenda. The dataset includes 3,841 observations from 167 countries, combining World Bank socio-economic indicators as predictors with SDG index scores as targets. A country-based split allocated 80% of countries for training and 20% for testing, ensuring cross-country generalization. Future projections for 2025–2030 use a persistence-based scenario in which socio-economic covariates remain at their most recent values, and lagged SDG scores are recursively updated, producing conditional simulations rather than purely autoregressive forecasts. The TabNet model demonstrates strong predictive performance: SDG 1 achieves RMSE of 4.22 (train) and 3.99 (test) with R² of 0.89 and 0.92, while SDG 4 achieves RMSE of 3.89 and 3.76 with R² of 0.95 and 0.93. Choropleth mapping highlights regional disparities, with higher predicted scores in Europe and North America compared to Sub-Saharan Africa. These results indicate that TabNet, combined with spatial visualization, provides an interpretable, robust, and policy-relevant framework for monitoring global SDG progress.
Co-Authors Harfely Leipary Suryasatria Trihandaru