PENERAPAN ANALISIS REGRESI SPLINE UNTUK MENDUGA HARGA CABAI DI JAKARTA

Authors

  • Hestiani Wulandari PT PIKMIAP GLOBAL EKSPRESS, Indonesia
  • Anang Kurnia Department of Statistics, Bogor Agricultural University (IPB)
  • Bambang Sumantri Department of Statistics, Bogor Agricultural University (IPB)
  • Dian Kusumaningrum Business Mathematics, Universitas Prasetiya Mulya, Indonesia
  • Budi Waryanto Division Data Food Crops and Livestock, Ministry of Agriculture, Indonesia

DOI:

https://doi.org/10.29244/ijsa.v1i1.47

Abstract

The chili is an important commodity in Indonesia, which has a fairly large price fluctuations. Fluctuations in prices often raises the risk of loss even have contributed to inflation. Chili price data is time series data that is not independent between observations (autocorrelation) and do not spread to normal. In addition, chili price data does not have the diversity of homogeneous data. One method that can be used to predict the pattern of the data is spline regression. The data used in this study is data the average weekly price of chili in Jakarta from January, 2010 to October, 2015. The best spline model is a second order spline models with three knots. The model has a value of Mean Absolute Percentage Error (MAPE) of 9.57% and determination coefficient of 86.41%. The model obtained in this research is already well in predicting the pattern of the chili price, but it was only able to predict well for a period of one month. Prediction chili prices in Jakarta for November are in the range of Rp 35.565.

Keywords: chili price, regression, spline.

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Published

2017-10-31

How to Cite

Wulandari, H., Kurnia, A., Sumantri, B., Kusumaningrum, D., & Waryanto, B. (2017). PENERAPAN ANALISIS REGRESI SPLINE UNTUK MENDUGA HARGA CABAI DI JAKARTA. Indonesian Journal of Statistics and Its Applications, 1(1), 1–12. https://doi.org/10.29244/ijsa.v1i1.47

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