Notification: Our email services are now fully restored after a brief, temporary outage caused by a denial-of-service (DoS) attack. If you sent an email on Dec 6 and haven't received a response, please resend your email.
CFP last date
20 December 2024
Reseach Article

Method of Holt-Winters and Back Propagation FOR Prediction of Rice Production by Considering Rat Pest Attack

by Hamid Wijaya, Vincencius Gunawan, Jatmiko Endro Suseno
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 179 - Number 51
Year of Publication: 2018
Authors: Hamid Wijaya, Vincencius Gunawan, Jatmiko Endro Suseno
10.5120/ijca2018917328

Hamid Wijaya, Vincencius Gunawan, Jatmiko Endro Suseno . Method of Holt-Winters and Back Propagation FOR Prediction of Rice Production by Considering Rat Pest Attack. International Journal of Computer Applications. 179, 51 ( Jun 2018), 34-38. DOI=10.5120/ijca2018917328

@article{ 10.5120/ijca2018917328,
author = { Hamid Wijaya, Vincencius Gunawan, Jatmiko Endro Suseno },
title = { Method of Holt-Winters and Back Propagation FOR Prediction of Rice Production by Considering Rat Pest Attack },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2018 },
volume = { 179 },
number = { 51 },
month = { Jun },
year = { 2018 },
issn = { 0975-8887 },
pages = { 34-38 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume179/number51/29526-2018917328/ },
doi = { 10.5120/ijca2018917328 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:58:58.377235+05:30
%A Hamid Wijaya
%A Vincencius Gunawan
%A Jatmiko Endro Suseno
%T Method of Holt-Winters and Back Propagation FOR Prediction of Rice Production by Considering Rat Pest Attack
%J International Journal of Computer Applications
%@ 0975-8887
%V 179
%N 51
%P 34-38
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Pest attack especially rodent can impact of reducing the production rice’s crop and also triggering harvest failure. Therefore, forecasting system which is able to be used as monitoring tools for the production of rice is considered to be needed. This research is aim to provide solutions of prediction and area’s mapping information of production using the Holt-Winters and Backpropagation methods. Utilized data are planting area, rainfall, rat attack area, intensity of rat attack, harvested area and production of rice for 4 years since 2014 to 2017 which each year has 3 periods. The application of Holt-Winters and Backpropagation methods resulted in the smallest MSE value of 0.02 with an accuracy of 99.8%. Based on these accuracy values, Holt-Winters and Backpropagation method calculations give the appropriate result as it approaches the actual value.

References
  1. S. Kaboodvandpour and L. K. P. Leung, “Modelling density thresholds for managing mouse damage to maturing wheat,” Crop Prot., vol. 42, pp. 134–140, 2012.
  2. Y. G. Lou, G. R. Zhang, W. Q. Zhang, Y. Hu, and J. Zhang, “Reprint of: Biological control of rice insect pests in China,” Biol. Control, vol. 68, no. 1, pp. 103–116, 2014.
  3. A. Walters and Q. Cai, “Investigating the Use of Holt-Winters Time Series Model for Forecasting Population at the State and Sub-State Levels,” J. Demogr. Work. Sect., vol. 2, pp. 7–8, 2008.
  4. A. Ganatra, Y. P. Kosta, G. Panchal, and C. Gajjar, “Initial Classification Through Back Propagation In a Neural Network Following Optimization Through GA to Evaluate the Fitness of an Algorithm,” Int. J. Comput. Sci. Inf. Technol., vol. 3, no. 1, pp. 98–116, 2011.
  5. J. Tarigan, Nadia, R. Diedan, and Y. Suryana, “Plate Recognition Using Backpropagation Neural Network and Genetic Algorithm,” Procedia Comput. Sci., vol. 116, pp. 365–372, 2017.
  6. P. Kalekar, “Time series forecasting using Holt-Winters exponential smoothing,” Kanwal Rekhi Sch. Inf. Technol., no. 04329008, pp. 1–13, 2004.
  7. S. . Kosbatwar and S. . Pathan, “Pattern Association for Character Recognition by Back Propagation Algorithm Using Neural Network Approach,” Int. Comput. Sci. Eng. Surv., vol. 3, no. 1, pp. 127–34, 2012.
  8. R. Tripathi et al., “Forecasting Rice Productivity and Production of Odisha , India , Using Autoregressive Integrated Moving Average Models,” Adv. Agric., vol. 1, pp. 1–9, 2014.
  9. C. Chatfield and M. Yar, “Holt-Winters Forecasting: Some Practical Issues,” Source J. R. Stat. Soc. Ser. D (The Stat. J. R. Stat. Soc. Ser. D Stat., vol. 37, no. 2, pp. 129–140, 1988.
  10. L. Ferbar Tratar and E. Strmčnik, “The comparison of Holt-Winters method and Multiple regression method: A case study,” Energy, vol. 109, pp. 266–276, 2016.
  11. N. A. Elmunim, M. Abdullah, A. M. Hasbi, and S. A. Bahari, “Comparison of GPS TEC variations with Holt-Winter method and IRI-2012 over Langkawi, Malaysia,” Adv. Sp. Res., vol. 60, no. 2, pp. 276–285, 2017.
  12. G. Tirkeş, C. Güray, and N. Çelebi, “Demand forecasting: a comparison between the Holt-Winters, trend analysis and decomposition models,” Teh. Vjesn. - Tech. Gaz., vol. 24, no. Supplement 2, pp. 503–509, 2017.
  13. U. Khair, H. Fahmi, S. Al Hakim, and R. Rahim, “Forecasting Error Calculation with Mean Absolute Deviation and Mean Absolute Percentage Error,” J. Phys. Conf. Ser., vol. 930, no. 1, pp. 1–6, 2017.
  14. W. N. Networks, W. Now, H. Are, and N. Networks, Fundamental of Neural Network:: Architecture, Algorithm, and Application. New Jarsey: Prentice-Hall, 1994.
  15. T. Baldigara, “Forecasting Tourism Demand in Croatia: A Comparison of Different Extrapolative Methods,” J. Bus. Adm. Res., vol. 2, no. 1, pp. 84–92, 2013.
Index Terms

Computer Science
Information Sciences

Keywords

Holt-Winters Backpropagation prediction rice rat.