Comparison of CART Algorithm and Cropping Calendar in Estimating Paddy Growth Stage in Karawang Regency, West Java

Classification And Regression Trees (CART) is one of the classic and simple algorithm in predictive modeling machine learning. This study aims to compare the result of paddy growth stage estimates based on CART model of Sentinel-1A Synthetic Aperture Radar (SAR) data and Cropping Calendar (KATAM). The construction of the CART model utilises real data field from Area Frame Sampling (Kerangka Sampling Area or KSA) in Karawang Regency observed on 2020. The CART algorithm makes predictions using a tree structure or hierarchical structure. The CART algorithm focuses on finding a decision tree model that has a Gini impurities value = 0. The rules for classifying class based on the physical polarization spectrum which is represented by pixel digital number from Vertical-Vertical (VV), Vertical-Horizontal (VH), and VV/VH of SAR image properties. This study found that the initial planting time is different. The CART model estimates the initial planting time is on September, while the KATAM estimates on November-December.