STUDI AWAL PEMODELAN SPASIAL IDENTIFIKASI ALIH FUNGSI HUTAN BERPOTENSI TERDAMPAK KORUPSI BERBASIS DATA PENGINDERAAN JAUH

• Main Author: Fadhil Muhammad, Miqdad
• Format: Final Project
• Language: Indonesia
• Subjects: Karya Umum
• Online Access: https://digilib.itb.ac.id/gdl/view/56813
• Institution: Institut Teknologi Bandung

Indonesia still has problems with corrupt behavior in the country. In 2020, Indonesia got an anti-corruption behavior index of 3.84. This condition explains the need to design a strategy to suppress corruption behavior and reduce the significant impact it produces. This corruption behavior has harmed the management of various state assets, including tropical rainforest resources, which are strategic assets in tackling global climate change. There is no way to calculate Indonesia's potential losses from damage to its natural resources accurately because the absence of spatial model analysis of the analysis of forest function conversion caused by corrupt practices has resulted. This study aims to make a breakthrough in modeling the deforestation index in Indonesia, which indicates the impact of corrupt practices. Corruption cases of land use in the forestry sector were identified as the initial basis for the analysis of deforestation targets based on the years of corruption. The LandTrendr algorithm on the Google Earth Engine is used in the Landsat vegetation index time series to determine the period for gain to occur in a forest to secondary forest. This conversion process speed is analyzed to obtain deforestation anomaly as the primary indicator for the deforestation development index due to corruption. There is an expectation that the initiation of a geospatial study on the corruption issue will be the first step towards the clean government realization with an environmental perspective to fight the common enemy of corruption.