<![CDATA[ABSTRAK Kecelakaan lalu lintas di Indonesia masih didominasi oleh faktor kesalahan manusia (human error), yang berkontribusi pada lebih dari 70% dari total kejadian kecelakaan. Pasal 90 Undang-Undang Nomor 22 Tahun 2009 tentang Lalu Lintas dan Angkutan Jalan (UU LLAJ), yang dijabarkan lebih lanjut melalui Peraturan Pemerintah Nomor 27, 28, dan 29 Tahun 2015, mewajibkan pemasangan perangkat pembatas kecepatan dan sistem monitoring kelelahan pengemudi pada kendaraan angkutan penumpang dan barang. Namun, implementasi teknologi monitoring yang efektif dan terjangkau di lapangan masih terbatas. Program pengabdian kepada masyarakat (PkM) ini bertujuan mengimplementasikan dan menguji coba purwarupa SLIFA Connect — sistem pemantau perilaku pengemudi berbasis kecerdasan buatan (AI) dan Internet of Things (IoT) dengan deteksi multivariabel (indikasi mengantuk, penggunaan handphone, merokok, dan rem mendadak) — pada armada transportasi mitra industri. Kegiatan dilaksanakan melalui fabrikasi 20 unit purwarupa, uji laboratorium (Electromagnetic Compatibility/EMC dan Power Quality Monitoring/PQM), serta uji lapangan pada 10 unit armada truk dan bus milik PT Anugerah Sarana Dinamika (ASD), hasil kolaborasi dengan Universitas Mercu Buana. Hasil menunjukkan seluruh purwarupa lolos uji emisi elektromagnetik dan mampu mendeteksi serta mengirimkan notifikasi pelanggaran (event) secara real-time ke server slifa.io, meliputi penggunaan ponsel, indikasi mengantuk melalui analisis frekuensi menguap, aktivitas merokok, dan pengereman mendadak. Implementasi SLIFA Connect terbukti memberikan solusi monitoring yang objektif, real-time, dan terdokumentasi bagi manajemen armada mitra, sehingga diharapkan dapat mendukung penurunan risiko kecelakaan sekaligus kepatuhan terhadap regulasi keselamatan transportasi jalan. Kata Kunci: Sistem Monitoring Pengemudi, Kecerdasan Buatan, Internet of Things, Keselamatan Transportasi, Pengabdian Masyarakat. ABSTRACT Traffic accidents in Indonesia are still dominated by human error factors, which contribute to more than 70% of total accidents. Article 90 of Traffic Law No. 22/2009, further elaborated through Government Regulations No. 27, 28, and 29 of 2015, mandates the installation of speed-limiting devices and driver fatigue monitoring systems on passenger and freight vehicles. However, effective and affordable field implementation of such technology remains limited. This community service program aims to implement and field-test the SLIFA Connect prototype — an AI- and Internet of Things (IoT)-based driver behavior monitoring system with multivariable detection (drowsiness, mobile phone use, smoking, and sudden braking) — on the fleet of an industry partner. Activities were conducted through the fabrication of 20 prototype units, laboratory testing (Electromagnetic Compatibility/EMC and Power Quality Monitoring/PQM), and field trials on 10 truck and bus units belonging to PT Anugerah Sarana Dinamika (ASD), in collaboration with Universitas Mercu Buana. Results show that all prototypes passed electromagnetic emission testing and successfully detected and transmitted real-time violation notifications to the slifa.io server, including mobile phone use, drowsiness indication through yawning frequency analysis, smoking activity, and sudden braking. The SLIFA Connect implementation provides an objective, real-time, and well-documented monitoring solution for partner fleet management, supporting both accident-risk reduction and compliance with road transport safety regulations. Keywords: Driver Monitoring System, Artificial Intelligence, Internet of Things, Transportation Safety, Community Service.]]>
