• Sri Sulistijowati Handajani Statistics Study Program FMIPA Universitas Sebelas Maret, Indonesia
  • Hasih Pratiwi Statistics Study Program FMIPA Universitas Sebelas Maret, Indonesia
  • Respatiwulan Respatiwulan Statistics Study Program FMIPA Universitas Sebelas Maret, Indonesia
  • Niswatul Qona’ah Statistics Study Program FMIPA Universitas Sebelas Maret, Indonesia
  • Monica Ramadhania Statistics Study Program FMIPA Universitas Sebelas Maret, Indonesia
  • Niken Evitasi Statistics Study Program FMIPA Universitas Sebelas Maret, Indonesia
  • Nindya Eka Apsari Statistics Study Program FMIPA Universitas Sebelas Maret, Indonesia
Keywords: GCV, B-Spline Regression Model Spline Truncated, temperature, R2


The spline regression model is a nonparametric model and it is applied to data that do not have a certain curve shape and do not have information about it. In this study, the results of the analysis of the B-Spline regression model and the Spline Truncated model were compared on temperature data at several stations on Java Island to obtain the best model that can be used to forecast the temperature for the next few days. Daily temperature data were obtained from BMKG at Semarang, Juanda, Serang, Sleman, Bandung, and Kemayoran stations. The temperature data were modeled with the B-Spline and Spline Truncated regression using the optimal knot point of the GCV, and the best model was obtained. The analysis shows that the B-Spline regression models are better than the truncated Spline models with a fairly small MSE value and a greater coefficient of determination than the truncated Spline model.


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