Deep Learning Methods as a Detection Tools for Forest Fire Decision Making Process Fire Prevention in Indonesia

Suri, Dia Meirina and Nurmandi, Achmad (2021) Deep Learning Methods as a Detection Tools for Forest Fire Decision Making Process Fire Prevention in Indonesia. HCI international. pp. 177-182. ISSN 978-3-030-90176-9

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Abstract

This research examines the collaboration between agencies in policymaking based on hotspot monitoring from satellites. Valid data regarding the number of hotspots from the satellite is needed in decision making because it provides information used to control forest and land fires in Indonesia. For instance, the Ministry of Forestry uses data from the NOAA-18 satellite for analysis, while the BMKG utilizes those from the Agua/Terra. However, the data generated by each satellite has differences in the number of hotspots. Therefore, this research aims to determine the collaboration between the Ministry of Forestry and BMKG in the use of satellite data for decision-makers to determine disaster alert status. This research uses a qualitative approach to analyze secondary data from two popular media sources collected using the Nvivo 12 plus application. The result showed that agencies involved in fire prevention lack collaboration due to institutional designs that lead to a lack of communication and unclear roles for each institution during the decision making process.

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