Prediksi konsumsi beras menggunakan metode regresi linear pada sistem kotak beras cerdas

Rice consumption prediction using linear regression method for smart rice box system

Mulia Hanif  -  Department of Informatics, Universitas Telkom, Indonesia
Maman Abdurohman scopus  -  Department of Informatics, Universitas Telkom, Indonesia
*Aji Gautama Putrada scopus  -  Department of Informatics, Universitas Telkom, Indonesia
Received: 7 May 2019; Revised: 13 May 2020; Accepted: 25 May 2020; Published: 31 Oct 2020; Available online: 19 Oct 2020.
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Section: Original Research Articles
Language: ID
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Currently, the smart rice box has applied the Internet of Things (IoT) but without prediction of rice runs out which shows the amount of rice consumption. This study applies linear regression to predict the rice runs out in an IoT-based smart rice box and analyzes its performance. The prediction used the dataset obtained by measuring a smart rice box equipped with a load cell weight sensor and Hx711 module. The weight sensor accuracy was an RMSE of between 56 and 170 grams. The linear regression method applied to the smart rice box to predict rice running out has an MSE value of 0.2588 with a prediction window of 43 days. An R-squared value of less than one is obtained with a predictive threshold of 24 days.
Keywords: ricebox; internet of things; linear regression; rice prediction
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