Estimasi Evapotranspirasi Potensial Menggunakan Algoritma Random Forest di Daerah Irigasi Tungkub, Bali

Authors

  • Luh Made Putri Apriliani Program Studi Teknik Pertanian dan Biosistem, Fakultas Teknologi Pertanian, Universitas Udayana, Badung, Bali, Indonesia
  • Ni Nyoman Sulastri Program Studi Teknik Pertanian dan Biosistem, Fakultas Teknologi Pertanian, Universitas Udayana, Badung, Bali, Indonesia
  • I Wayan Widia Program Studi Teknik Pertanian dan Biosistem, Fakultas Teknologi Pertanian, Universitas Udayana, Badung, Bali, Indonesia
  • I Putu Gede Budisanjaya Program Studi Teknik Pertanian dan Biosistem, Fakultas Teknologi Pertanian, Universitas Udayana, Badung, Bali, Indonesia

DOI:

https://doi.org/10.24843/j.beta.2025.v13.i01.p16

Keywords:

machine learning, potential evapotranspiration, random forest, weather variabel

Abstract

The estimation of Potential Evapotranspiration (ETp) is crucial for water distribution planning and
cropping patterns. Generally, ETp calculation is obtained from empirical models such as the PenmanMonteith (PM) model recommended by the Food and Agriculture Organization (FAO). However,
implementing this model requires numerous weather variables and adequate weather data availability. This
research aims to develop an ETp estimation model using the Random Forest (RF) algorithm The weather
variables used in this research as inputs for ETp modeling are solar radiation (Rs); air temperature (T); air
humidity (RH); and a combination of Rs and T. Weather variable data were obtained from an automatic
weather station (AWS) in the Tungkub Irrigation Area, Bali. The research results indicate that the weather
variable Rs is the best estimation model input, while the weather variable RH is the weakest. In model
calibration, three evaluation metrics were used to assess model performance, R2, MSE, and RMSE.
Meanwhile, for model validation, three techniques were employed, prediction error plot, residuals plot,
and k-fold cross-validation. The research results indicate that the average ETp estimation value with the
scenario of input Rs using the RF algorithm in the Tungkub Irrigation Area is 0,14 mm/hour (R2 = 1,00,
MSE = 0,00, RMSE = 0,01). Meanwhile, the average ETp PM value is 0,15 mm/hour. The scenario of
input Rs using the RF algorithm shows estimation values close to the PM ETp value.

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Published

2025-04-30

How to Cite

Apriliani, L. M. P., Sulastri, N. N., Widia, I. W., & Budisanjaya, I. P. G. (2025). Estimasi Evapotranspirasi Potensial Menggunakan Algoritma Random Forest di Daerah Irigasi Tungkub, Bali. Jurnal BETA (Biosistem Dan Teknik Pertanian), 13(1), 142–150. https://doi.org/10.24843/j.beta.2025.v13.i01.p16

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Vol. 13 No. 1 (2025): April

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