OPTIMALISASI KINERJA MIKROKOMPUTER RASPBERRY Pi PADA SMART GREENHOUSE BERBASIS INTERNET OF THINGS (IoT) DENGAN ALGORITMA FORECASTING MOVING AVERAGE
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Abstract
Smart Greenhouse merupakan sebuah terminologi konsep pertanian di era revolusi 4.0 yang sedang marak saat ini untuk membangun rumah kaca system cerdas. Kecerdasan yang dapat diimplementasikan adalah pemantauan dan pengendalian secara mudah dengan Mikrokomputernya yaitu Raspberry Pi sebagai running program dan parameternya adalah Suhu Udara, Kelembaban Udara, Sinar UV dan Kelembaban Tanah. Penelitian ini bertujuan untuk mengetahui optimalisasi parameter-parameter tersebut pada smart greenhouse dengan menggunakan metode forecasting moving average sehingga dalam penerapannya melalui pengamatan dan pengendalian ketiga sensor tersebut pada Smart Greenhouse agar dapat digunakan seefektif mungkin. Ketiga parameter tersebut yang dipelajari selama 3 bulan, diambil melalui alat dengan jangkauan waktu dari 08:00-16:00 WITA. Total dataset adalah 500 deret dengan 4 variabel. Peramalan ini menggunakan metode moving average. Evaluasi yang digunakan adalah MSE dan RMSE dengan hasil sensor suhu dan kelembaban udara (DHT22) sebesar 0,466, sensor uv (GUVA-S112SD) sebesar 56,198, dan sensor kelembaban tanah (Capital Soil Moisture) sebesar 65025,0.
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