Implementasi Smart Agriculture Berbasis IoT untuk Monitoring Lahan Pertanian
Kata Kunci:
Smart Agriculture, Internet of Things, Monitoring Lahan, Pertanian Digital, Sensor IoTAbstrak
Bidang agrikultur saat ini dihadapkan pada sejumlah kendala, mulai dari anomali iklim, krisis ketersediaan air, pengawasan lahan yang kurang efisien, hingga masih maraknya praktik tata kelola secara manual. Kemajuan teknologi Internet of Things (IoT) memberikan jalan bagi pemanfaatan Smart Agriculture guna mengoptimalkan pantauan kondisi lahan secara langsung (real-time). Kajian ini bertujuan untuk merancang bangun sekaligus menerapkan sistem Smart Agriculture berlandaskan IoT untuk memantau lahan pertanian, sehingga proses pengawasan dapat berjalan dengan lebih cepat, presisi, dan berdaya guna. Pendekatan yang diusung adalah Research and Development (R&D), yang mencakup tahapan identifikasi kebutuhan, perancangan sistem, perakitan purwarupa, uji coba perangkat, hingga evaluasi performa. Rangkaian sistem ini dikembangkan menggunakan mikrokontroler yang terintegrasi dengan sensor kelembapan tanah, sensor suhu dan kelembapan udara, serta pengukur pH tanah. Data yang diperoleh kemudian ditransmisikan via koneksi internet menuju server untuk disajikan pada antarmuka dashboard web. Hasil pengujian menunjukkan bahwa perangkat sukses membaca situasi lahan secara mandiri dan mentransfer data ke server dalam interval waktu tertentu. Komponen pembaca kelembapan tanah mampu melacak fluktuasi volume air, baik pada kondisi tanah kering maupun pasca-irigasi. Sensor suhu dan kelembapan udara menampilkan data yang konsisten mengikuti dinamika cuaca per hari, sementara sensor pH tanah menghasilkan tingkat akurasi yang berada pada rentang toleransi yang wajar. Dashboard terbukti mampu menyajikan informasi terkini, visualisasi grafik, dan notifikasi peringatan saat tingkat kelembapan tanah turun melewati batas minimal. Implementasi Smart Agriculture berteknologi IoT ini terbukti efektif sebagai jalan keluar bagi pemantauan lahan pertanian masa kini. Inovasi ini sanggup mendongkrak efisiensi pengawasan area tanam dan memfasilitasi penentuan keputusan budidaya secara sigap. Untuk penyempurnaan ke depannya, sistem dapat diarahkan pada penggabungan fitur irigasi otomatis serta analitik prediktif yang didukung oleh kecerdasan buatan (AI).
Unduhan
Referensi
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Hak Cipta (c) 2026 Mohammad Faisol, Syamsul Arifin (Penulis)
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