Pola Sekuensial Kemunculan Titik Panas Berdasarkan Data Cuaca di Provinsi Riau

Abstract

Weather is one of some contributing factors causing forest fires. A hotspot is an indicator of forest fires. Weather and hotspots data can generate sequential pattern occurences of hotspots based on weather data. The sequential pattern can be used to help in making right decisions or policies to prevent forest fires. This research applied the Closed Sequential Pattern Mining (Clospan) algorithm that avaliable in Sequential Pattern Mining Framework program (SPMF) to generate sequential patterns. The data used are hotspots, precipitation and temperature that are grouped by year of events starting from the year 2001 to 2010. The sequential patterns were discovered with minimum supports from 1% to 20%. The results show that the sequential patterns generated from hotspot and precipitation data indicate the first hotspot occurence in a location with precipitation 0.03 inch per 6 hours followed by precipitation 0.20 inches per 6 hours at different times. Sequential patterns of hotspot and temperature data indicate the first hotspot occurence in a location with temperature 28.33 °C followed by temperature 28.89 °C and temperature 29.44 °C at different times. Areas where most commonly found hotspot occurrences are those with precipitation 0.03 inch per 6 hours and temperature 29.44 °C.