Association patterns of hotspot sequence with socio-economic aspects in peatland in Sumatra

Abstract

Every year forests degrade because of illegal logging and forest fires. The worst forest and land fires are also found on peatlands. This research aims to identify hotspot sequences as fire indicator on Sumatra peatlands on the year 2014 using SPADE algorithm. There are 28 sequences generated with a minimal of two days occurrences with minimum support of 0.01. The sequence patterns showed that majority hotspot consecutively occurred on March and April of 2014. Association between hotspot sequences and social economy aspects is then analyzed using Apriori algorithm. This research results 1632 rules associated with location of hotspot sequences. According to the association rules, we could conclude that hotspot sequence occurrences generally found on locations with plantation as the source income of the community, has forest fire history within 2011 until 2013, no history of drought within the same year, and has 0 to 9 schools.