<![CDATA[Basic ingredients are something that must be fulfilled in order to support the survival of all humans, one of the main ingredients is rice. Rice is a major commodity of staples needed by humans in several countries in the world. As a result, if the price of the staple food of rice experiences erratic price fluctuations (fluctuations) which can cause a reduction in the purchasing power of people with low incomes, the rice mills stop operating to avoid losses. Therefore, to avoid and reduce the risk of food security problems in the future, we need a system that can be able to predict the prices of rice so that it can help reduce the risk of loss and can ensure that rice prices can be reached by the wider community. In making this system, of course, a periodic data method (time series) is needed that can process real data in order to predict the price of rice staples correctly. In this study the method used is the Least Square method. This method can predict rice prices by using data in the past to be used as forecasting guidelines in the future. From the prediction results, the smallest error search calculation (error) is carried out using MAPE (Mean Absolute Percentage Error). The data used in this study were 132 data. Which consists of 132 training data and 12 test data the latest data. After the prediction process is carried out the result from the prediction prices of rice for 12 months in 2021 are obtained. The results of the prediction of rice prices for 12 months in 2021 are obtained. The test results from this prediction are in the form of the smallest error value (error) which is considered very good in accuracy to predict rice prices using the least square method, which is 5%.]]>
Copyrights © 2022
