%0 Thesis
%9 Skripsi
%A M Faruq Najib, NIM.: 16620033
%B FAKULTAS SAINS DAN TEKNOLOGI
%D 2020
%F digilib:43263
%I UIN SUNAN KALIJAGA YOGYAKARTA
%K Soil fertility detection, LED, Camera, Deep Learning.
%P 87
%T RANCANG BANGUN SISTEM DETEKSI  KESUBURAN TANAH BERBASIS LED, KAMERA   DAN DEEP LEARNING
%U https://digilib.uin-suka.ac.id/id/eprint/43263/
%X This research is motivated by the lack of an effective and efficient soil fertility detection system. This  study aimed to design, manufacture, and test a soil fertility detection system based on LED, camera,  and deep learning. This research was conducted in three stages, namely designing, manufacturing,  and testing the soil fertility detection system. Design of the tool was carried out using Paint 3D  software. Manufacturing of this detection system through 4 processes, namely preparation of tools  and materials, manufacturing hardware, taking datasets, and making software. Soil fertility  detection system testing was carried out by implementing a system was made using fertile and  infertile soil samples with dry and wet variations. The results is that it has been successfully designed  and developed of a soil fertility detection system based on LED, camera, and deep learning using  high power UV LED, USB camera, and deep learning. Meanwhile, the results of system  implementation show that percentage of success of the system in detecting fertile and infertile soil  is 100%.
%Z Pembimbing : Frida Agung Rakhmadi, S.Si., M.Sc