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  • 标题:PEMODELAN DATA INFLASI INDONESIA PADA SEKTOR TRANSPORTASI, KOMUNIKASI, DAN JASA KEUANGAN MENGGUNAKAN METODE KERNEL DAN SPLINE
  • 本地全文:下载
  • 作者:Suparti Suparti ; Tarno Tarno
  • 期刊名称:MEDIA STATISTIKA
  • 印刷版ISSN:1979-3693
  • 电子版ISSN:2477-0647
  • 出版年度:2015
  • 卷号:8
  • 期号:2
  • 页码:103-110
  • DOI:10.14710/medstat.8.2.103-110
  • 语种:English
  • 出版社:MEDIA STATISTIKA
  • 摘要:In this research, we study data modeling of Indonesian inflation in the transportation, communication and financial services sector using the kernel and spline models. Determination of the optimal models based on the smallest of GCV value and determination of the best model based on the smallest out sampels of Mean Square Error (MSE) value. By modeling the yoy (year on year) inflation data in Indonesia in the transportation, communication and financial services sector In January 2007 to January 2015, shows that the kernel model using Gaussian kernel function obtained optimal model with a bandwidth 0.24 and the optimal spline model with order 5 and 4 points knots. Based on out sampels data in February to August 2015, obtained out sampels MSE value of the spline model is smaller than the kernel model. So that the spline model is better than the kernel model to analyze the inflation data of transportation, communication and financial services sector. Keywords: Inflation, Transportation, Communication and Financial Services Sector, Kernel, Spline, GCV, MSE.
  • 其他摘要:In this research, we study data modeling of Indonesian inflation in the  transportation, communication and financial services sector using the kernel and spline models. Determination of the optimal models based on the smallest of GCV  value and determination of the best model based on the smallest out sampels of Mean Square Error (MSE) value. By modeling the yoy (year on year) inflation data in Indonesia in the transportation, communication and financial services sector In January 2007 to January 2015, shows that the kernel model  using Gaussian kernel function obtained optimal model with a bandwidth  0.24 and the optimal spline model with order 5 and  4 points knots. Based on out sampels data  in February to August 2015, obtained out sampels  MSE value of the spline model is smaller than the kernel model. So that the spline model is better than the kernel model  to analyze  the inflation data  of transportation, communication and financial services sector. Keywords: Inflation, Transportation, Communication and Financial Services Sector, Kernel, Spline, GCV, MSE.
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