Open AccessPlant recommendation using Triple Exponential Smoothing and K-Nearest Neighbor based on Internet of Things
Author(s) -
M. J. Habbibie,
Y Yaddarabullah,
Ade Syahputra
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1098/6/062010
Subject(s) - wind speed , exponential smoothing , meteorology , computer science , process (computing) , k nearest neighbors algorithm , environmental science , smoothing , intensity (physics) , agricultural engineering , mathematics , geography , statistics , machine learning , engineering , physics , quantum mechanics , operating system
Nutritious Garden Trilogy University is an agricultural land managed by urban farmers as well as students who are also lecturers to practice teaching and learn in the cultivation of types of plant commodities. Cultivation of plant species done by examining the climatic factors of plants on the land. The sustainability reason is one of the obstacles to make sure the results of cultivation in the teaching and learning process. The changing climate makes urban farmers get trouble to determine types of plants to be planted. This study will develop a system to forgive the recommendation of the type of plant according to the change of climate. The climate changes recorded using the internet of things sensors which consist of temperature, humidity, light intensity, and wind speed. The data entered will be processed using the triple exponential smoothing method as a forecast to predict future weather, then classified using the k-nearest neighbor to get the types of plants. The results of forecasting testing from sensors using the mean absolute percentage error obtained values of 9.53% temperature, 16.44% humidity, 3.73% light intensity, 19.42% wind speed.