Work place: Department of Computer Science, Bogor Agricultural University, Bogor, 16680, Indonesia
E-mail: sergi.roseli@yahoo.com
Website:
Research Interests: Computer systems and computational processes, Data Mining, Data Structures and Algorithms
Biography
Sergi Roseli is a master student in Computer Science, Bogor Agricultural University, Indonesia. Her main research interests include data mining and spatial data processing.
By Imas S. Sitanggang Sergi Roseli Lailan Syaufina
DOI: https://doi.org/10.5815/ijitcs.2018.09.02, Pub. Date: 8 Sep. 2018
One of problems that can increase the risk of forest fire occurrences in Indonesia is drought which is affected by weather conditions. Therefore, weather conditions and forest fire are strongly related. Spatial co-location pattern can be applied to identify the weather conditions that are vulnerable to fires based on the distance between weather observation points and hotspot occurrences. The purpose of this study is to apply the co-location miner algorithm on the weather and hotspot data in Rokan Hilir Riau Indonesia and to analyze the generated co-location patterns. Experimental results show that precipitation which co-located with hotspot occurrences are 0.08–6.69 mm/day. In addition, the temperature which co-located with hotspot occurrences are 22°C–29.17°C. Inside the intervals, hotspots will occur in the radius of 9.724 km from the precipitation and temperature observation points. In 2008, many hotspots were found on the three areas in the study area with the average of precipitation around 3.65–3.71 mm/day and temperature around 24.44°C–25.23°C.
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