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Lambok Franciskus Simangunsong
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Agriculture, Biological Sciences & Forestry Chemistry Education Mathematics Physics

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A Hybrid Regression–Fuzzy Framework for Climate Impact Assessment Using Primary energy consumption and CO₂ Emissions Asido Saragih; Lambok Franciskus Simangunsong
EduMatSains : Jurnal Pendidikan, Matematika dan Sains Vol 11 No 2 (2026): October
Publisher : Fakultas Keguruan dan Ilmu Pendidikan, Universitas Kristen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33541/edumatsains.v11i2.8769

Abstract

This research aims to establish a relationship between primary energy consumption and CO₂ emissions and classify countries by their potential climate impact applying hybrid regression and Mamdani fuzzy logic. Data of 178 countries were analyzed using cross-sectional data of 2022, where primary energy consumption and CO₂ emissions were measured per capita. The system involved two inputs with three triangular and shoulder-shaped membership functions (Low, Moderate, High) and nine fuzzy rules. The results indicated that 96 (53.9%) countries belonged to High, 27 (15.2%) to Moderate, and 55 (30.9%) to Low potential climate impact categories. A bivariate linear regression model was estimated to analyze the relationship between primary energy consumption and CO₂ emissions by setting the former as an independent variable and the latter as a dependent variable. The results found a very weak positive association r = 0.0721 and p = 0.3385. The regression results demonstrated that 0.52% of the changes in CO₂ emissions per capita could be predicted by primary energy consumption per capita. The results suggest that potential climate impact is influenced by various factors, including energy sources, economic activities, industrialization, and energy efficiency. Therefore, the analysis employed a hybrid approach which combined statistical and fuzzy logic methodologies to address the climate change problem.
Co-Authors Asido Saragih