Fertigation Management System Model Using Supervised Machine Learning and Time-Duration Method on Agricultural Industrial Land
Rida Hudaya, Dodi Budiman Margana, R. Wahyu Tri Hartono, Alli Nur Magribi
Available Online 22 December 2020.
- https://doi.org/10.2991/aer.k.201221.007How to use a DOI?
- Fertigation management system, supervised machine learning, time-duration method
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
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 - https://doi.org/10.2991/aer.k.201221.007 ID - Hudaya2020 ER -