RANCANG BANGUN SISTEM PENGAMBILAN KEPUTUSAN PENDETEKSI KANTUK PENGEMUDI BERBASIS INTERNET OF THINGS DENGAN OUTPUT PERINGATAN MENGGUNAKAN ALGORITMA NAIVE BAYES
DOI:
https://doi.org/10.61722/jssr.v4i6.13037Keywords:
Internet of Things, kantuk pengemudi, Naive Bayes, ESP32, MPU6050, FirebaseAbstract
Kantuk saat mengemudi merupakan salah satu faktor yang dapat menurunkan konsentrasi dan kewaspadaan pengemudi sehingga meningkatkan risiko kecelakaan, khususnya pada operasional kendaraan berat di lingkungan proyek konstruksi. Penelitian ini bertujuan untuk merancang dan membangun sistem pendeteksi kantuk pengemudi berbasis Internet of Things (IoT) dengan menerapkan algoritma Naive Bayes sebagai metode klasifikasi serta buzzer sebagai perangkat peringatan. Penelitian ini menggunakan metode Research and Development (R&D) dengan pendekatan kuantitatif deskriptif. Sistem yang dikembangkan menggunakan mikrokontroler ESP32, sensor inframerah FC-51 untuk mendeteksi kondisi mata, serta sensor MPU6050 untuk memperoleh nilai kemiringan kepala berdasarkan parameter pitch dan roll. Data sensor dikirimkan melalui jaringan Wi-Fi ke server berbasis Python dan Flask untuk diproses menggunakan algoritma Naive Bayes. Hasil klasifikasi dibagi menjadi tiga kategori, yaitu normal, mengantuk, dan sangat mengantuk. Hasil prediksi dikirimkan kembali ke ESP32 untuk mengendalikan buzzer sebagai peringatan kepada pengemudi. Selain itu, data sensor dan hasil klasifikasi disimpan melalui Firebase Realtime Database dan ditampilkan pada website monitoring sehingga kondisi pengemudi dapat dipantau secara jarak jauh. Hasil penelitian menunjukkan bahwa sistem berhasil diimplementasikan dan mampu mengintegrasikan pembacaan sensor, pengiriman data, proses klasifikasi, pemberian peringatan suara, penyimpanan data, serta pemantauan melalui website. Sistem ini diharapkan dapat mendukung upaya peningkatan keselamatan pengemudi dan membantu proses pemantauan kondisi pengemudi oleh pengawas proyek.
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