Manajemen Otomatisasi Pembibitan Tembakau
Kata Kunci:
Kata kunci: Internet of Things, Penyiraman Otomatis, Pembibitan Tembakau, Smart Agriculture, Efisiensi Sumber DayaAbstrak
Pembibitan tembakau merupakan tahap awal yang menentukan keberhasilan budidaya tembakau karena berpengaruh langsung terhadap kualitas bibit dan produktivitas tanaman pada fase berikutnya. Praktik pembibitan di tingkat petani umumnya masih dilakukan secara konvensional, dengan penyiraman manual dan pemantauan lingkungan yang tidak terukur, sehingga berpotensi menyebabkan pemborosan air, tingginya beban kerja, serta ketidaksesuaian kondisi media tanam. Perkembangan teknologi Internet of Things (IoT) menawarkan pendekatan berbasis data untuk mendukung otomatisasi dan efisiensi pengelolaan pertanian. Penelitian ini bertujuan menerapkan dan mengevaluasi sistem manajemen otomatisasi pembibitan tembakau berbasis IoT guna meningkatkan efisiensi penggunaan air dan waktu kerja petani. Penelitian menggunakan metode rancang bangun dan uji lapangan dengan pendekatan kuantitatif dan kualitatif. Sistem dikembangkan dengan mengintegrasikan sensor kelembapan tanah, sensor suhu dan kelembapan udara, sensor hujan, modul penjadwalan waktu, serta notifikasi berbasis aplikasi pesan instan. Evaluasi dilakukan melalui pengujian kinerja sistem, pengamatan respons penyiraman, serta perbandingan penggunaan air dan waktu kerja petani sebelum dan sesudah penerapan sistem. Hasil penelitian menunjukkan bahwa sistem mampu bekerja secara stabil dan responsif. Penyiraman dapat dilakukan secara adaptif berdasarkan kondisi kelembapan tanah dan dihentikan secara otomatis saat hujan terdeteksi. Penerapan sistem berhasil menurunkan penggunaan air secara signifikan dan mengurangi waktu kerja petani dari 420–595 menit per minggu menjadi 210–315 menit per minggu, atau berkurang sekitar 45%. Kesimpulannya, sistem manajemen otomatisasi pembibitan tembakau berbasis IoT efektif dalam meningkatkan efisiensi pengelolaan pembibitan dan mendukung praktik pertanian cerdas. Penelitian selanjutnya disarankan mengembangkan sistem pada skala lahan yang lebih luas serta memanfaatkan data historis untuk pengambilan keputusan yang lebih adaptif.
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REFERENSI
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