Penerapan Algoritma Backpropagation untuk Prediksi Hasil Panen Padi di Kabupaten Labuhan Batu Utara - Tbn, Ahmad Fauza Anshori; R., Rakhmat Kurniawan (Program Studi Teknik Informatika Universitas Pamulang, 2024)
Rice is a food crop that has vital benefits and important benefits for human survival. Rice plants are often found in the surrounding environment, especially those living in rural areas. Farmers use various methods to continue to increase rice yields. However, in reality the rice harvest results are not stable from year to year, this is because farmers' businesses still depend on natural factors which have a risk of causing a high chance of crop failure, thus accumulating the risk of low income received by farmers, including in the Regency. North Labauhanbatu so a prediction is needed to find out the future picture of the rice harvest. Predictions are also made so that lowland rice production remains stable. One way that is often used to make predictions is to use artificial neural networks. Artificial Neural Networks (ANN) are designed based on the structure and function of the human brain as a model of intuitive imitation. In an artificial neural network there are a number of neurons. One network can connect to many other networks, and each connection (link) has a weight (weight). Prediction of rice harvest results in Kabuipatein Labuihan Batui Uitara using the backpropagation algorithm. The results of trials carried out with the Rapid Mineir architectural model software with an RMSEi amount of 0.403 +/- 0.000 in the implementation of backpropagation. The smaller the RMSEi (Root Meian Squiareid Eirror) the better the teirseibuit model.