Forecasting Palawija Harvest Results In North Aceh Using Multiple Linear Regression Method

Abstract

The agricultural sector is one sector that is very dominant in people's income in Indonesia because most Indonesians work as farmers. One of the plants that play the most crucial role is the palawija plant. An increase in the amount of production and the harvested area will also increase the amount of harvest produced; therefore, to find out which areas have the potential to become producers of productive secondary crops in North Aceh, one of them is by predicting crop yields using the multiple linear regression method. The dataset used for this research is data on the development of palawija crop intensification in North Aceh Regency from 2017 to 2021, taken from the Department of Agriculture and Food Crops, North Aceh Regency. The multiple linear regression method is implemented by entering actual data. Then the data will be calculated in various stages, starting from determining the value of constants and coefficients using a table helper. After getting the result value, then converted into matrix form A and H to find the determinants A1, A2, A3, and A4. After that, enter it into a linear regression pattern and produce a predictive value of crop yield data for the coming year. Calculations in the linear regression method are taken on soybean yields in the Tanah Jambu Aye sub-district in 2022, ranging from 61.00 tons.