TY  - THES
N1  - Pembimbing : Frida Agung Rakhmadi, S.Si., M.Sc
ID  - digilib43263
UR  - https://digilib.uin-suka.ac.id/id/eprint/43263/
A1  - M Faruq Najib, NIM.: 16620033
Y1  - 2020/12/18/
N2  - 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%.
PB  - UIN SUNAN KALIJAGA YOGYAKARTA
KW  - Soil fertility detection
KW  -  LED
KW  -  Camera
KW  -  Deep Learning.
M1  - skripsi
TI  - RANCANG BANGUN SISTEM DETEKSI
KESUBURAN TANAH BERBASIS LED, KAMERA 
DAN DEEP LEARNING
AV  - restricted
EP  - 87
ER  -