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All Journal Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika
Jasmin Nur Hanifa
Universitas Islam Negeri Syarif Hidayatullah Jakarta
Decision Sciences, Operations Research & Management Education Mathematics

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PENERAPAN CROSS-VALIDATION PADA MODEL EFEK CAMPURAN: DAMPAK FAKTOR EKONOMI DAN KESEHATAN TERHADAP INDEKS KERENTANAN NEGARA-NEGARA DI ASIA TENGGARA Jasmin Nur Hanifa; Madona Yunita Wijaya; Suma’inna Suma’inna
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 5 No. 1 (2024): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v5i1.565

Abstract

This research aims to investigate the impact of economic growth on the stability of countries in Southeast Asia during the period 2010–2021. The research method involves the use of data from the International Monetary Fund (IMF), the World Health Organization (WHO), the World Bank, and the Fragile State Index (FSI). A mixed-effects model was used to analyze the relationship between these variables, and K-fold cross-validation was employed to determine the optimal subset model within the mixed-effects model framework. The research results indicate a model with quadratic nonlinear trend, produces lower root mean squared error (RMSE) and mean absolute error (MAE) values compared to other models, indicating a higher level of accuracy in predicting data. The conclusion of this research is that the mixed-effects model with a quadratic non-linear assumption, particularly the third model, exhibits superior predictive performance with an RMSE of 0.628 and MAE of 0.536. However, it should be highlighted that just a few variables, particularly life expectancy, GDP, and the square of GDP, contribute considerably to the variation in the mean FSI (Fragile States Index The findings provide insights into the model's ability to capture the complexity of relationships among predictor variables and mean FSI, as well as identify the variables influencing a country's vulnerability
Co-Authors Suma’inna Suma’inna Wijaya, Madona Yunita