SMART FORECASTING MODELS (SFM) MENGGUNAKAN METODE RECURRENT NEURAL NETWORK UNTUK PREDIKSI MUSIM TANAM PADA KOMODITAS CABAI MERAH
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Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
MAKMUR, NUR ATHIFAH MARWA
Haris, Abdul
Sikumbang, Hengki
Haris, Abdul
Sikumbang, Hengki
Subject
Teknik Informatika
Datestamp
2023-05-31 07:07:16
Abstract :
There are still many red chili farmers who have difficulty determining when is the right time to plant red chilies. Because there are several factors that must be considered before starting to loosen red chilies. The factors that farmers pay the most attention to are not only cleanliness and plant needs such as fertilizer, but also external aspects such as rainfall. With the development of technology, now we can predict when the right time to plant red chilies. Weather forecasting is done to determine the time of coverage of this red chili can use the recurrent neural network method. The recurrent neural network method in this study uses sequentially patterned daily rainfall data. There are 3 stages in the recurrent neural network method, namely data preprocessing, calculations using the RNN method and model evaluation. The data used in the study were 3926 daily rainfall data. From this data, the results of the prediction of the correct planting season are from January to March and July to September 2023. The level of accuracy in this study uses 2 (two) methods, namely Mean Absolute Error (MAE) which produces an error value of 0.2528, and Root Mean Squared Error (RMSE) which produces an error of 0.44.
There are still many red chili farmers who have difficulty determining when is the right time to plant red chilies. Because there are several factors that must be considered before starting to loosen red chilies. The factors that farmers pay the most attention to are not only cleanliness and plant needs such as fertilizer, but also external aspects such as rainfall. With the development of technology, now we can predict when the right time to plant red chilies. Weather forecasting is done to determine the time of coverage of this red chili can use the recurrent neural network method. The recurrent neural network method in this study uses sequentially patterned daily rainfall data. There are 3 stages in the recurrent neural network method, namely data preprocessing, calculations using the RNN method and model evaluation. The data used in the study were 3926 daily rainfall data. From this data, the results of the prediction of the correct planting season are from January to March and July to September 2023. The level of accuracy in this study uses 2 (two) methods, namely Mean Absolute Error (MAE) which produces an error value of 0.2528, and Root Mean Squared Error (RMSE) which produces an error of 0.44.
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