The Implementation Of The Fletcher-Reeves Algorithm In Predicting The Growth Of Forest Plant Cultures

Abstract

Forest protection and development are essential because forests are the world's lungs. In addition, the HTI organization (modern manor backwoods) began to hide again. However, due to the great interest in wood to be used as raw material for material and property production lines, large organizations started to develop hamlet wood which was then marketed abroad, such as pressed wood, rattan, sawn timber, and done jobs for individuals in the area around the hamlet. By making a prediction, knowledge about the growth of forest plants can be known so that they can anticipate or minimize the risks that may arise. They can assist in determining policies and making decisions. This study aims to predict the growth of forest plants in the following year using an Artificial Neural Network Algorithm. The information used in this study is from the Central Bureau of Statistics from 2011 to 2022. The method of implementing this research uses the Fletcher-Reeves Algorithm, one of the Artificial Neural Network methods using 5 models, including 7-10-1, 7-15- 1, 7-20-1, 7-25-1, and 7-30-1. Of the five models, the structural model is 7-20-1 with an MSE value of 0.00037397. It can be said that this model can be used because it produces a fast combination and a short period of time.