Double Exponential Smoothing Forecasting Food Crop Yields Using Geographic Information Systems

Abstract

Food is a source of basic needs for every living creature, so food security is an interesting issue for every country. This raises problems regarding food and land use, especially in Sungai Penuh City. Food problems arise due to a lack of information regarding appropriate land use and the productivity of the land itself. In the current industrial era 4.0, forecasting can be done using information technology tools that provide convenience and efficiency in forecasting times and can be integrated with geographic information systems. The forecasts made by the community are based on past experience without considering the factors that influence crop yields, so that they can cause losses both in terms of time and costs. Apart from that, less accurate predictions of food yields can lead to less than optimal development of food security which has an impact on meeting food needs. This research involved respondents from the Department of Agriculture and Food Security, namely agricultural and food experts. The method for collecting data in this research is observation and interviews. This research analyzes harvest data for the 2018-2023 period sourced from the Central Statistics Agency using the Double Exponential Smoothing method by considering error values with α = 0.1 and 0.5 and β = 0.1 and 0.5. The calculation of the smallest error value is: ME = 80.92, MAD = 5.58, MAPE = 11%, MSE = 52.69 by combining the value of α= 0.1 and the value of β = 0.1 to produce a prediction of the corn harvest in Kumun Debai District in 2024 of 45 tons and year 2025 as much as 40 tons.