Abstract
This research conducted by predicting soil moisture using Fuzzy Time Series (FTS) and soil moisture sensor technology on shallot farming. Well-controlled soil moisture affects the shallots and crops growth. It discusses soil moisture prediction and monitoring systems developed through Android-based mobile programming languages. Input data consists of sensor results obtained from automatic, online, and real-time acquisition using soil moisture sensor technology, then, sent to the server and stored in an online database. Furthermore, data acquisition is predicted using the FTS algorithm that applies a discourse universe to define and determine fuzzy sets. Fuzzy set results are continued to the process of sharing the discourse universe so that it becomes the final step. Prediction results are displayed on the information system dashboard developed. Using 24 data from soil moisture data, the predicted score is 760 at the beginning of 6:00. The results of the prediction are done by validating error deviations using the Mean Square Error of 1.5%. This proves that FTS is good enough in predicting soil moisture and safety to control soil moisture in shallots. For deeper analysis, researchers used various request data and U discourse universe at FTS to obtain various results based on the test data used.
Highlights
IntroductionSensor technology and methods/algorithms complement and assist in the research process
Sensors and fuzzy, sensor technology and methods/algorithms complement and assist in the research process
Soil moisture is of fundamental importance to many hydrological, biological and biogeochemical processes, plays an important role in the development and evolution of convective weather and precipitationand impacts precision agriculture, water resource management, and flood run off prediction [3]
Summary
Sensor technology and methods/algorithms complement and assist in the research process. The session used a soil moisture sensor and applied fuzzy time series (FTS) methods/algorithms. FTS is used to process numerical values/soil moisture data as a result of soil humidity sensors that have recorded/retrieved data at the specified time. Soil moisture is a variable from hydrology that connects between water, energy, and carbon cycles. Soil moisture is very important as a support for weather forecasting, flood forecasting, drought monitoring and climate modeling. The amount of moisture in the soil is an important variable to understand the coupling of the continental surface and the atmosphere. Soil moisture is of fundamental importance to many hydrological, biological and biogeochemical processes, plays an important role in the development and evolution of convective weather and precipitationand impacts precision agriculture, water resource management, and flood run off prediction [3]
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