The COVID-19 pandemic at 2020 resulted in the collecting process of the KSA Padi survey not running optimally. Alternative sources are needed that do not require officers to go to the field, one of solution is remote sensing. KSA-Hybrid is a new term in the combination of the KSA Padi method and remote sensing. Research with KSA-Hybrid is still rarely carried out and produces a significant difference to the actual situation. This study focuses on the best percentage of the combination between both. The research locus in Lamongan Regency with a coverage period of 2018-2020. The satellite imagery feature sourced from the Landsat-8 satellite. The machine learning model used a random forest with evaluation indicators by accuracy and kappa statistics. The research results obtained accuracy and kappa evaluation values of 72.62 and 64.85 percent. The percentage of the best combination by KSA-Hybrid is 3% because the relative change impact is below 1%..
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