Comparison of Sugarcane Drought Stress Based on Climatology Data using Machine Learning Regression Model in East Java

Comparison of Sugarcane Drought Stress Based on Climatology Data using Machine Learning Regression Model in East Java

Crop Water Stress Index (CWSI), derived from vegetation features (NDVI) and canopy thermal temperature (LST), is an effective method to evaluate sugarcane sensitivity to drought using satellite data. However, obtaining CWSI values ​​is complicated. This study introduces a novel approach to estimate...

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Bibliographic Details
Main Authors: Aries Suharso, Yeni Herdiyeni, Suria Darma Tarigan, Yandra Arkeman
Format: Article
Language:English
Published: Ikatan Ahli Informatika Indonesia 2025-03-01
Series:Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Subjects:
climatological data
crop water stress index
machine learning regression
sugarcane
Online Access:https://jurnal.iaii.or.id/index.php/RESTI/article/view/6159
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