Main Article Content

Abstract

Climate models that are able to simulate rainfall in Indonesia so far have not been found. The highly complex topography and interaction of the sea, land and atmosphere adds to the complexity of simulations and predictions of rainfall in Indonesia, particularly in Central Sulawesi. This research focuses on utilizing the results of prediction or forecast rainfall. Rainfall forecasting results obtained are then modeled with data on the level of rice production, so we can predict the future supply of rice (rice). This study examines statistical downscaling modeling with a generalized additive model approach to describe the rainfall events that occur within a certain time period. The data used is rainfall data in Central Sulawesi Province, because this region is a supplier of rice in Sulawesi.

Article Details

Author Biography

L Handayani, Tadulako University

Statistics Department

How to Cite
Handayani, L., Amelia, R., & Putera, F. H. A. (2020). Rice Production Estimation In Central Sulawesi Through The Utilization Of Rainfall By Using Generalized Additive Model. JURNAL ILMIAH MATEMATIKA DAN TERAPAN, 16(2), 230 - 240. https://doi.org/10.22487/2540766X.2019.v16.i2.13997

References

  1. Beck N, Jackman S. 1997. Getting The Mean Right is a Good Thing: GAMs. San Diego: University of California.
  2. Brockwell, P.J. dan Davis, R.A. 2002. Introduction to Time Series and Forecasting. New York: Springer-Verlag.
  3. Busuioc A, Chen D, Hellstrom C. 2001. Performance of statistical downscaling models in GCM validation and regional climate change estimates (Application for Swedish precipitation). International Journal of Climate 21: 557-578.
  4. Draper NR, Smith H. 1981. Applied Regression Analysis, 2nd. John Wiley and Sons, Inc.
  5. Handayani, Lilies. 2014. Statistical Downscaling dengan Model Aditif Terampat untuk Pendugaan Curah Hujan Ekstrim [Tesis]. Bogor: Institut Pertanian Bogor.
  6. Haryoko U. 2004. Pendekatan Reduksi Dimensi Luaran GCM untuk Penyusunan Model SD [Tesis]. Bogor: Institut Pertanian Bogor.
  7. Hastie T, Tibshirani R. 1990. Generalized Additive Models. London: Chapman and Hall.
  8. Makridakis, S. dan Wheelwright, S.C. 1999, Metode dan Aplikasi Peramalan. Jakarta: Erlangga.
  9. Mondiana YQ. 2012. Pemodelan Statistical Downscaling dengan Regresi Kuantil untuk Pendugaan Curah Hujan Ekstrim [Tesis]. Bogor: Institut Pertanian Bogor.
  10. Prang JD. 2006. Sebaran Nilai Ekstrim Terampat dalam Fenomena Curah Hujan [Tesis]. Bogor: Institut Pertanian Bogor.
  11. Sutikno. 2008. Statistical Downscaling Luaran GCM dan Pemanfaatannya untuk Peramalan Produksi Padi [Disertasi]. Bogor: Institut Pertanian Bogor.
  12. Wigena AH. 2006. Pemodelan Statistical Downscaling dengan Regresi Projection Pursuit untuk Peramalan Curah Hujan Bulanan (Kasus Curah Hujan Bulanan di Indramayu) [Disertasi]. Bogor: Institut Pertanian Bogor.
  13. Wilby RL, Charles SP, Zorita E, Timbal B, Whetton P, Mearns LO. 2009. A review of climate risk information for adaptation and development planning. Journal of Climatology 29: 1193-1215.