Analysis of Deep Learning Cyclical order for Prediction of Fresh Milk Production in Sumatera

Abstract

Milk is one of the most preferred and most easily absorbed nutrients. This drink naturally contains important nutrients, such as vitamins A, D, B12, protein, calcium, magnesium, phosphorus, and zinc, and others. Milk is also beneficial for children and adults. Starting from maintaining healthy bones and teeth, as a source of energy, and so on. In Indonesia, especially on the island of Sumatra, fresh milk production is carried out by cattle and goat farmers in cooperation with milk companies. This research have a purpose is to predict the production of fresh milk on the island of Sumatra so that the local government, as well as cattle and goat breeders on the island of Sumatra, have benchmarks to further increase the production of fresh milk in their respective regions in the future. The method that will be used in this research is Deep Learning Cyclical order which is the development of ANN. The research data used were data on the production of fresh milk on the island of Sumatra in 2009-2018 sourced from the Indonesian Statistics Agency. This research will be analyzed using 3 network architecture models, namely 4-5-1, 4-10-1 and 4-5-10-1 with the best network model chosen is 4-5-10-1 with an accuracy level of 90% and MSE value of 0.0157179042. Based on this best model a prediction of fresh milk production in Sumatra will be carried out in 2019-2020.