文章基本信息

标题：PEMODELAN DATA INFLASI INDONESIA PADA SEKTOR TRANSPORTASI, KOMUNIKASI, DAN JASA KEUANGAN MENGGUNAKAN METODE KERNEL DAN SPLINE
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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.