Sistem Deteksi Nyamuk Berbasis IoT dan Machine Learning
Abstract
Abstrak — Penyakit yang ditularkan nyamuk, seperti demam berdarah dengue, malaria, dan Zika, terus menjadi masalah kesehatan global terutama di negara tropis. Upaya pengendalian konvensional sering kali menghadapi keterbatasan dalam efektivitas jangka panjang dan keamanan lingkungan. Penelitian ini mengembangkan sistem deteksi nyamuk berbasis Internet of Things (IoT) dan machine learning untuk mendeteksi serta memprediksi tren populasi secara realtime. Sistem memanfaatkan sensor suara, suhu, kelembapan, dan karbon dioksida yang terintegrasi dengan perangkap nyamuk elektrik dan mikrokontroler ESP32. Data dari sensor dikirim ke cloud dan dianalisis dengan algoritma machine learning untuk menghasilkan prediksi potensi lonjakan populasi. Hasil uji coba menunjukkan sistem mampu memberikan informasi akurat, cepat, dan dapat diakses dari jarak jauh melalui dashboard berbasis web. Dengan sifatnya yang portabel dan ramah lingkungan, sistem ini memiliki potensi besar untuk diterapkan di rumah tangga, fasilitas kesehatan, dan area publik sebagai alat mitigasi dini risiko wabah. Kata kunci— deteksi nyamuk, Internet of Things, machine learning, ESP32, prediksi wabah.
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