The Application of Apriori Algorithm in Predicting Flood Areas

Nur Ashikin Harun, Mokhairi Makhtar, Azwa Abd Aziz, Zahrahtul Amani Zakaria, Fadzli Syed Abdullah, Julaily Aida Jusoh


The changing of physical characteristics of the hydrological system have caused a lot of natural phenomenon, which leads to flooding as one of the major problems that cause economic damages and affect people’s life. Therefore, the need for a systematic and comprehensive approach to flood area prediction is needed. This research proposed a flood area prediction model with the application of Apriori algorithm towards hydrological data sets. Department of Irrigation and Drainage Malaysia supply the data sets and flood report from year 2009 to 2015 (November until January) which consist of 7 district. The research begins with the data selection, pre-process the data, and data transformation, then the cleaned data will be tested with the Apriori algorithm. The rules will be evaluating using support, confidence and lift value to rank either it is best rules or not. The results show that each district generates best and crucial rules which consist the association of the villages and water level. Thus, hopefully the result can be use in flood management and can give early an early warning to the villagers at flood risk area.


data mining; Apriori algorithm; association rule; flood disaster; knowledge discovery in database.

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Published by INSIGHT - Indonesian Society for Knowledge and Human Development