Internet of Things Based Rainfall Monitoring System in Smart Agriculture

Changes in climatic conditions in an area have the potential to affect agricultural conditions. So that climate change and variability is a climate anomalous phenomenon that is a serious concern because it has a major impact, especially on the agricultural sector. The purpose of this study is to build an internet of things-based rainfall monitoring system on an intelligent agricultural system equipped with an effective monitoring system. This research resulted in an internet of things-based rainfall monitoring system that has been successfully designed with the help of raspberry devices, rainfall sensors, RTC, flashdisk and modems, so as to be able to present rainfall data and then process the prediction results using the moving average method, while the data grouping uses the oldeman classification. Based on the results of the analysis of the accuracy level of RMSE obtained 0.13 percent and MAPE 3.54 percent, then the results of the comparison of tools made by BMKG Indonesia for maros district obtained rmse accuracy rate of 0.04 percent and MAPE 3.71 percent, this shows very good results so that it can be a reference for farmers.