Shofiana, Dewi Asiah and Sitanggang, Imas Sukaesih (2021) Confidence Analysis of Hotspot as Peat Forest Fire Indicator. Journal of Physics: Conference Series, 1751. 012035. ISSN 17426596

Preview

Text Shofiana_2021_J._Phys.__Conf._Ser._1751_012035 (2).pdf Download (1MB) | Preview

Abstract

Indonesia has recorded 14.9 million hectares of peat forest that continue to be deforested due to fire across Sumatra and Kalimantan. To operate a successful firefight, fast detection is a key element. Hotspot that appeared consecutively in more than two days is a strong indicator of fire existence. As the interest in data mining arose, an advanced technique can be implemented toward hotspot dataset into finding solutions. Many previous works have been carried out to mine sequence patterns and succeeded in determining as well as predicting areas with high occurrence of fire. However, none of the studies analyses the outliers, such as several hotspots which confidence decrease significantly in an adjacent interval of time. Confidence determines the quality of hotspot, with a value above 70 strongly indicates that fire spot exist. This study generated sequence patterns using the SPADE algorithm and analyses 21 hotspots considered as outliers using the Landsat-8 image. The result shows that 85.71 of hotspots have decreased confidence due to haze cover.

Item Type:	Article
Uncontrolled Keywords:	confidence, hotspot, Landsat 8, peatland fire, sequential pattern mining, SPADE
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science S Agriculture > SD Forestry
Divisions:	Fakultas Matematika dan Ilmu Pengetahuan Alam (FMIPA) > Prodi Ilmu Komputer
Depositing User:	M.Kom. Dewi Asiah Shofiana
Date Deposited:	07 May 2021 03:45
Last Modified:	07 May 2021 03:45
URI:	http://repository.lppm.unila.ac.id/id/eprint/30056

Actions (login required)

View Item