@thesis{thesis,
		author={Agtriadi  Herman Bedi and Cahyaningtyas  Rizqia and Shaputra  Irwan},
		title ={IMPLEMENTASI METODE CONVOLUTIONAL NEURAL NETWORK UNTUK IDENTIFIKASI PENYAKIT PADA TANAMAN POHPOHAN},
		year={2022},
		url={http://156.67.221.169/4912/},
		abstract={Pohpohan plant or called in scientific language Pilea trinervia Wight is a wild plant
that lives in wild forests. And includes one of the indigenous vegetable plants or plants
that are cultivated in a certain area that can be consumed as vegetables. Pohpohan plants
can also be used as traditional or herbal medicines, and pohpohan plants are often also
used in certain communities as traditional or herbal medicines. Convolutional Neural
Network (CNN) is a method that can be used to detect and recognize an object in an
image. CNN is also a type of neural network that can work well on an image. In this
study, the classification class used by the author consisted of four classes of disease types,
which included four (4) classes of disease types, namely healthy leaves, Budug disease,
Blonde disease, Perforated Leaf disease. The amount of data processed is 387 images
with testing data and 310 images for validation with a total of 15 epochs. Furthermore,
the image data will be used to form a model or model fitting that will be used for the
testing process. The parameters used in this study to measure the success rate. In this
system model, the highest accuracy and lowest loss are the 15th diepoch, which is 0.9406
with a loss of 0.2112, for the highest val_accuracy and the lowest val_loss there is the
15th diepoch, namely val_accuracy 0.9836 with a val_loss of 0.0989.}
		}