Analysis of temperature patterns in Pekanbaru City using fractals and artificial neural networks based on monthly temperature data - Reynal Nur Razzaq; Defrianto Defrianto (Indonesian Physics Communication, 2024)
Climate and global warming play a crucial role in the lives of living organisms on Earth. Temperature, varying in each region, is a vital aspect in climate observation. This study analyzed temperature fluctuations in Pekanbaru from 2016 to 2022 using fractal analysis and backpropagation artificial neural networks. The research findings revealed that temperature prediction with backpropagation artificial neural networks was quite accurate. However, errors during testing or validation could impact the comparison with the target values. Fractal analysis indicated a persistent tendency in temperature fluctuations in Pekanbaru, with a Hurst exponent of 0.7993 and a fractal dimension of 1.2007. Nevertheless, temperature fluctuations were also influenced by other factors, leading to varying levels of stability over certain periods. Thus, the temperature in Pekanbaru can be considered a complex system with diverse fluctuation patterns and varying levels of complexity.