PREDIKSI HARGA CABAI MERAH KERITING MENGGUNAKAN METODE RECURRENT NEURAL NETWORK
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Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
ALMUSANDI, FADRI
Sikumbang, Hengki
Haris, Abdul
Sikumbang, Hengki
Haris, Abdul
Subject
Teknik Informatika
Datestamp
2023-05-30 06:59:58
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%.
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%.
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