Estimation of Exponential Smoothing Parameter on Pesticide Characteristic Forecast using Ant Colony Optimization (ACO)

Dinita Rahmalia


Pest in agriculture can raise plant disease and fail to harvest. The pest problem in agriculture can be solved by using pesticide. Pesticide usage must be done proportionally. So, the manufacturer should fix standard pesticide active ingredient in pesticide production. Forecast is a prediction of some future evens. In forecast problem, there are any parameters which should be determined. Parameters can be estimated by exact method or heuristic method. Ant Colony Optimization (ACO) is inspired from the cooperative behavior of ant colonies, which can find the shortest path from their nest to a food source. In this research, we use heuristic method like ACO to estimate exponential smoothing parameter on pesticide active ingredient forecast and pesticide sample weight forecast. From the simulation, on the first iteration, all ants choose parameter randomly. At the optimization process, we update pheromone until all ants choose the similar parameter so that process converges and variance approaches to zero. The optimal exponential smoothing parameter can be applied in forecasting with minimum sum of squared error (SSE).


Parameter estimation; Ant Colony Optimization; Exponential Smoothing

Full Text:



Elvural, B.C., Beyca, O.F., Zaim, S., 2016,

Model Estimation of ARMA using Genetic Algorithms : A Case Study of Forecasting Natural Gas Consumption, Procedia-Social and Behavioral Sciences, 235, 537– 545

Rahmalia, D., Herlambang, T., 2017, Application Ant Colony Optimization on Weight Selection of Optimal Control SEIR Epidemic Model, Proceeding the 7th Annual Basic Science International Conference 2017, ISSN : 2338-0128, diselenggarakan oleh

Fakultas MIPA Universitas Brawijaya,


Anderson, D.R., Sweeney, D.J., 2012, An Introduction to Management Science, Cengage Learning, USA, ISBN: 978-1-111-53224-6

Dorigo, M., Stutzle, T., 2004, Ant Colony Optimization, The MIT Press, London, ISBN: 0-262-04219-3

Montgomery, D.C., Jennings, C.L., Kulahci, M., 2015, Introduction to Time Series Analysis and Forecasting, John Wiley and Sons, New Jersey

Rahmalia, D., 2010, Pengendalian Kualitas Kadar Bahan Aktif dan Alumunium Foil pada Produksi Pestisida, Laporan Kerja Praktek Matematika ITS, Surabaya

Rao, S.S, 2009, Engineering Optimization Theory and Practice, John Wiley and Sons, New Jersey, ISBN: 978-0-470-18352-6

Article Metrics

Metrics Loading ...

Metrics powered by PLOS ALM

Eksakta: Jurnal Ilmu-Ilmu MIPA
Journal of Mathematics and Natural Sciences

ISSN 1411-1047 (print), ISSN 2503-2364 (online)
Published by: 
Faculty of Mathematics and Natural Sciences
Universitas Islam Indonesia, Yogyakarta

Creative Commons License

Jurnal EKSAKTA is licensed under a Creative Commons Attribution ShareAlike 4.0