Implementasi Teknik Computer Vision Untuk Deteksi Viridiplantae Pada Lahan Pasca Tambang
DOI:
https://doi.org/10.47065/bulletincsr.v3i1.193Keywords:
Objek Detection; Artificial Intelligence; Green MiningAbstract
The use of computers as producers of technology-based products is hugely impressive. Computer vision technology, which is a branch of artificial intelligence, is developing very quickly. This is what underlies the need for this research to be done to detect the number of green plants (Viridiplantae) that are located on critical post-mining land, where it is known that the area is land that has been damaged with the condition of the soil being shallow and a layer of remaining tailings until a layer of rock is visible that can inhibit plant growth. Thus developed an application for detecting green plants using computer vision as modern ways to improve the recognition of objects in images. Computer vision applications are implemented on desktop applications created with the Python aiming to balance modern technology with the concept of preserving the environment. The development method used Cross Industry Standard Process for Data Mining which is the most representative method for planning overall data extraction, the design of the experiment and evaluation. The results of the research proved that only a few green plants were detected on post-mining land, so it is necessary to increase public awareness that environmental preservation and maintenance is very important.
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