Abstract:
Floods in Banjarbaru have mostly been studied from the perspective of natural and physical causes,
such as rainfall and the region's topography. Meanwhile, the association between household conditions and
community behavior during floods is rarely explored quantitatively. This research aims to fill that gap by
applying the Apriori algorithm to questionnaire data from flood-affected householdsto find association rules.
The study found that disruptions in livelihoods during floods tend to be followed by a decrease in income,
while floods lasting more than one day generally trigger the evacuation of family members and prompt the
government to provide temporary shelters. These key rules imply that flood mitigation policies should
prioritize early warning systems, pre-positioning of shelter facilities, and targeted economic assistance to
enhance the resilience of affected households
