Fertigation Management System Model Using Supervised Machine Learning and Time-Duration Method on Agricultural Industrial Land

DOI

10.2991/aer.k.201221.007How to use a DOI?

Keywords

Fertigation management system, supervised machine learning, time-duration method

Abstract

This paper contains an explanation of the fertigation management system model to deal with the water crisis and the efficient use of plant nutrients in the case of agricultural industrial land in Lembang, Indonesia. The method developed uses a time-duration method equipped with supervised machine learning. Machine throughout the year learns the schedule of agricultural expert operators in providing water and nutrition. At the same time, the machine records the microclimate of humidity, rain, and sunny around the agricultural land. The time-duration and microclimate relationships were plotted with a linear approach. Obtained three time-equation TON and three duration-equation DUR over 24 hours with an average of R2 0.5654, around 04:58 with duration 2 hours and 23 minutes, around 09:44 with duration 2 hours 43 minutes, and around 14:44 with duration 5 hours 19 minutes.

Copyright

© 2020, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Rida Hudaya
AU  - Dodi Budiman Margana
AU  - R. Wahyu Tri Hartono
AU  - Alli Nur Magribi
PY  - 2020
DA  - 2020/12/22
TI  - Fertigation Management System Model Using Supervised Machine Learning and Time-Duration Method on Agricultural Industrial Land
BT  - Proceedings of the International Seminar of Science and Applied Technology (ISSAT 2020)
PB  - Atlantis Press
SP  - 34
EP  - 38
SN  - 2352-5401
UR  - https://doi.org/10.2991/aer.k.201221.007
DO  - 10.2991/aer.k.201221.007
ID  - Hudaya2020
ER  -