Pemetaan Kondisi Lingkungan Tanam menggunakan K-Means Clustering sebagai Dasar Sistem Rekomendasi Tindakan Pertanian
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Abstract
Objektif. Pemasangan alat IoT-Agri, sebagai sistem pemantauan kondisi lingkungan tanam berbasis Internet of Things, menghasilkan sejumlah besar data rekam kondisi lingkungan tanam. Melalui pendekatan data mining, data rekam yang terdiri dari waktu tanam, pH air, suhu air, suhu udara, dan nilai TDS dapat digunakan untuk memetakan kondisi lingkungan penanaman. Pemetaan selanjutnya dapat digunakan sebagai dasar sistem keputusan tindakan pertanian.
Material and Metode. Pemetaan kondisi lingkungan tanam menggunakan algoritma k-means clustering, diuji menggunakan elbow method dan dijadikan dasar sistem keputusan tindakan pertanian yang dikirimkan melalui telegram bot.
Hasil. Kondisi lingkungan tanam dipetakan dalam 3 (tiga) cluster. Masing-masing merupakan kondisi lingkungan tanam yang kurang nutrisi dan kurang air, cukup nutrisi tapi kurang air, serta cukup nutrisi dan cukup air. Pengujian clustering dengan elbow method menunjukkan bahwa pemetaan Kondisi lingkungan tanam bernilai optimal ditunjukkan dengan nilai inersia sebesar 199,065. Keputusan tindakan pertanian dikirimkan melalui telegram bot berupa instruksi penambahan unsur hara, penambahan air, dan penambahan unsur hara serta air.
Kesimpulan. Data yang diperoleh dari pemasangan alat IoT-Agri dikelola menggunakan pendekatan data mining, dipetakan berdasarkan kecukupan dan/atau kebutuhan lingkungan tanam terhadap nutrisi dan air. Secara efektif, keputusan tindakan pertanian dapat diberikan kepada petani sesuai dengan kondisi lingkungan tanam saat ini.
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