Sistem Pengering Daun Kelor Berbasis Internet of Things dan Artificial Intteligence

Abstract

Drying Moringa leaves is needed to reduce the water content so that the Moringa leaves become fresh and can be used for the following process. Drying Moringa leaves to change the water content from 80% to 9.2% requires ideal heating conditions because the heating speed must not damage the nutritional content in the leaves. Developing an existing drying system using IoT to monitor humidity and temperature to increase the drought stability of the Moringa leaves produced. By using IoT, it is hoped that drying conditions can be watched from anywhere and recorded so that if undesirable things happen, it will be easier to track the history of the drying process that has taken place. This system is also connected to a recommendation system using an Artificial Neural Network (ANN). This system will provide recommendations for the best conditions for Moringa flour production because various external factors influence the drying of Moringa leaves. Utilization of the ANN model can recognize data patterns in seasonal time series. The results of implementing the Moringa leaf drying machine can reduce the time by 120 minutes faster than the previous tool