Determining Growing Season of Potatoes Based on Rainfall Prediction Result Using System Dynamics

Ida Wahyuni, Philip Faster Eka Adipraja, Wayan Firdaus Mahmudy


Potato has been and is a basic food for many countries. However, because of the uncertainty in rainfall patterns that have occurred since the existence of climate change make a significant impact on the outcome of potatoes production from year to year. Therefore, it needs the determination of new growing season period according to climate change. The determination of growing season is based on the result of rainfall prediction data using system dynamics ever done in previous studies to predictions of rainfall during the next five years starting in 2017-2021. Based on the modeling that has been done shows that early dry season ranges in mid-April to mid-May by the length of days in the growing season ranges from 162-192 days. The growing season prediction model has small error only about two dasarian. By the middle of the dry season, rainfall is expected to be very low which will make the potatoes into water deficit and will affect the harvest of potatoes plants which can be overcome with the irrigation system.


Growing season, Potatoes, Rainfall prediction, System dynamics, Tengger

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Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
ISSN 2089-3272

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This work is licensed under a Creative Commons Attribution 4.0 International License.

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