Application of Lagrange interpolation and Newton’s interpolation to predict the rate of Malaysian’s unemployment in 2023 / Muhammad Syahruddin Mohd Hilmy

• Main Author: Mohd Hilmy, Muhammad Syahruddin
• Format: Thesis
• Language: English
• Published: 2023
• Subjects: Prediction analysis
• Online Access: https://ir.uitm.edu.my/id/eprint/97157/1/97157.pdf; https://ir.uitm.edu.my/id/eprint/97157/
• Institution: Universiti Teknologi Mara

Unemployment rates are critical economic indicators that reflect the health and stability of a nation's labour market. Accurate predictions of future unemployment rates are essential for policymakers, researchers, and businesses to formulate effective strategies and make informed decisions. This project focuses on the application of Lagrange interpolation and the Newton’s Interpolation to predict the rate of Malaysian unemployment in 2023. Additionally, we apply the Newton’s Interpolation to refine the predictions and assess its effectiveness in enhancing the accuracy of the forecasts. The results obtained from both the Lagrange interpolation and Newton’s Interpolation will be compared and evaluated. By examining the performance of these methods, we can gain insights into their applicability and suitability for predicting the rate of Malaysian unemployment in 2023. Overall, this project contributes to the field of numerical analysis by demonstrating the practical application of Lagrange interpolation and the Newton’s Interpolation in forecasting economic indicators. The findings and methodologies presented here can assist policymakers, economists, and researchers in making informed decisions, formulating policies, and designing strategies to address unemployment challenges in Malaysia and potentially in other countries as well.