### Analysis of Solar Flux and Sunspot Correlation Case Study: A Statistical Perspective

#### Abstract

*This analysis examines the relationship between the number of solar flares and the number of sunspots in 2005 using 11 observations in months 2 to 12. The number of solar currents measures the intensity of the radiation emitted by the Sun, while the number of sunspots measures the number of sunspots on the surface of the Sun. Multivariate linear regression analysis was used to analyze the relationship between Solar Current Rate and Number of Sunspots. The results of the analysis show that the coefficient of the Amount of Solar Current is 1.1239 with a significant t value of 2.510 (probability that there is no effect on the Number of Sunspots is 3.33%). The linear regression model has good results with an F-statistic value of 6.301 and a p-value of 0.0333, with an R-squared value of 0.4118 which indicates that 41.18% of the variation in the number of sunspots is influenced by variations in the amount of solar currents. The corrected R-squared value is 0.3464 indicating that there are still variations in the number of sunspots that cannot be explained by variations in the number of solar currents. ARIMA analysis results show an MA coefficient of 0.7351 with an average value of 45.9542 and a s.e value of 0.2590 and 6.1550 respectively. The AIC, AICc, and BIC values are 92.97, 96.4, and 94.16. The error results in the training set show that the ME value is 0.2615561, the RMSE value is 12.16969, the MAE value is 9.03306, the MPE value is -15.14689, the MAPE value is 30.42013, and the MASE value is 0.674109. The ACF1 value in the exercise set is 0.0808969.*

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DOI: https://doi.org/10.29408/kpj.v7i1.12238

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