Prediction For Coffee Yield Production Using Simple Linear Regression With Geographical Information System (GIS)

Abstract

Coffee is one of the mainstay commodities in the Indonesia plantation sector. In addition, Indonesia is also one of the countries that have the fourth-largest coffee harvest in the world. At this time there are still many coffee farmers who are tracking and determining crop yield manually. Considering the present system are including the manual counting method,and the changing of climate crisis cannot be predicted.

This Final Project proposes an application to estimate and determine the coffee yield production. Also using a Geographical Information System to analyze and map the yield area. The dataset of coffee plantations is from Indonesia Central Bureau Statistics. The data set will be input minimum are from the last 5 years, then the data are trained and analyzed using the Linear Regression algorithm to get the estimated prediction result of coffee production for the next year.