Pemodelan Indeks Kualitas Lingkungan Hidup di Indonesia dengan Spline Truncated dan MARS
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https://doi.org/10.32665/statkom.v4i1.4394Keywords:
IKLH, Spline Truncated, MARS, Nonparametric RegressionAbstract
Background: Indonesia, endowed with abundant natural resources, faces substantial challenges in maintaining environmental quality amid rapid urbanization and economic growth. The 2022 Environmental Performance Index ranked Indonesia 164th out of 180 countries with a score of 28.2. Regionally, Indonesia ranked 22nd among 25 Asia-Pacific countries. The Environmental Quality Index (EQI), crucial for achieving the Sustainable Development Goals (SDGs), was recorded at 72.42 in 2022, classified as "fair." This condition underscores the need for in-depth analysis of key factors influencing environmental quality.
Objective: This study aims to examine significant factors affecting the Environmental Quality Index (EQI) across Indonesian provinces using appropriate nonparametric statistical methods.
Methods: A nonparametric regression approach, specifically the Multivariate Adaptive Regression Spline (MARS) and the truncated spline multipredictor model, was applied. Predictor variables included the Human Development Index (HDI), population density, access to proper sanitation, poverty rate, and Gross Regional Domestic Product (GRDP). Secondary data for 34 provinces in 2022 were sourced from the Central Bureau of Statistics and the Ministry of Environment.
Results: The truncated spline model demonstrated superior performance, achieving a minimal MSE of 5.63308, minimal GCV of 10.42, and R2 of 82.63%, outperforming MARS, which yielded a minimal MSE of 7.685, GCV of 16.014, and R2 of 79.3%. All predictor variables significantly influenced EQI.
Conclusion: Social and economic factors were found to significantly affect environmental quality. The truncated spline approach offers an effective modeling alternative, providing critical insights to support environmental policy development at the provincial level.
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