Pengembangan Aplikasi Android untuk Rekomendasi Penyiraman Cerdas Berbasis IoT dengan Metode Fuzzy C-Means dan Jaringan Saraf Tiruan
DOI:
https://doi.org/10.30736/jti.v11i02.1657Keywords:
Fuzzy C-Means, Jaringan Saraf Tiruan, TensorFlow, Internet of Things (IoT), AndroidAbstract
Pengelolaan irigasi yang efisien sangat penting untuk mengoptimalkan penggunaan air dan menjaga kondisi tanah yang mendukung pertumbuhan tanaman. Meskipun banyak model kecerdasan buatan telah dikembangkan, sistem konvensional kerap kesulitan menggeneralisasi rekomendasi karena mengabaikan ambiguitas dan tumpang tindih (overlapping) pola data lingkungan. Penelitian ini secara eksplisit berkontribusi pada pengembangan sistem rekomendasi penyiraman hibrida (hybrid) berbasis edge-computing, yang mengintegrasikan pelabelan otomatis Fuzzy C-Means (FCM) dengan prediksi Jaringan Saraf Tiruan (JST) pada aplikasi Android. Sistem ini memproses kumpulan dataset berjumlah 96.547 sampel yang diperoleh dari empat parameter sensor yaitu intensitas cahaya, suhu udara, kelembapan udara, dan kelembapan tanah. Melalui metode FCM, data lingkungan tersebut diurai secara objektif ke dalam empat kelas kondisi, yaitu: 0, 1, 2, dan 3. Untuk memastikan keandalan model, tahap evaluasi dilakukan menggunakan metode Confusion Matrix dalam skema pengujian 5-Fold Cross Validation (k=5). Pada setiap iterasi pengujiannya, dataset dibagi menjadi 80% data latih dan 20% data uji. Hasil eksperimen menunjukkan performa model yang luar biasa stabil dengan rata-rata akurasi sebesar 98,85%, presisi 98,23%, recall 97,48%, dan F1-Score 97,78%. Setelah hasil pengujian model, model JST dikonversi menjadi TensorFlow Lite (TFLite) dan diintegrasikan secara real-time ke dalam aplikasi perangkat seluler Android. Secara praktis, sistem ini memetakan keempat prediksi kelas lingkungan tersebut ke dalam tiga perilaku penyiraman: tanpa penyiraman (menggabungkan kelas 0 dan 3 yang memiliki karakteristik kebutuhan air serupa), penyiraman volume sedang, dan penyiraman volume tinggi. Hasil penelitian ini membuktikan bahwa pendekatan hibrida FCM dan JST yang diusulkan sangat efisien sebagai sistem pendukung keputusan irigasi dalam pertanian presisi. Penelitian lanjutan dapat difokuskan pada perluasan volume dataset serta integrasi langsung terhadap perangkat keras penyiraman berbasis Internet of Things (IoT).
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