@thesis{thesis,
		author={ALMUSANDI  FADRI and Haris  Abdul and Sikumbang  Hengki},
		title ={PREDIKSI HARGA CABAI MERAH KERITING MENGGUNAKAN METODE RECURRENT NEURAL NETWORK},
		year={2022},
		url={http://156.67.221.169/5663/},
		abstract={The agricultural production sector plays an important role in meeting the needs of the 
Indonesian economy. Because agricultural production is the main source of staple food 
for Indonesian people. The daily needs of the community cannot be separated from 
agricultural production, including curly red chili. Curly red chili is a plant that is 
categorized as a fruit and a member of the Capsiun genus. The fruit can be classified as 
either a vegetable or a spice, depending on how it is used. As a spice, curly red chili is 
not only a raw material, but also a raw material for today's industry. Per capita demand 
in Indonesia for curly red chili fluctuates from year to year. Consumption of curly red 
chilies increases every year along with the increasing population of Indonesia. 
Fluctuations and increases in the price of curly red chili can cause losses. One solution 
to overcome this problem is to make a price forecast that can predict the potential 
increase in the price of red chili. The method used in this study is the Recurrent Neural 
Network (RNN) method. Then a test is carried out, namely the data training process using 
the RNN algorithm, then predictions of the price of red curly chili for the next 24 months 
are carried out. so that the MAPE value is 11.05 with a test accuracy rate of 88.95%.}
		}