Pelatihan Deteksi Diabetic Foot Ulcer (DFU) Berbasis Citra Digital Menggunakan Deep Learning untuk Tenaga Kesehatan di Puskesmas
Keywords:
Deep Learning, Deteksi DFU, Puskesmas, Tenaga Kesehatan, Ulkus Kaki DiabetikAbstract
Diabetic Foot Ulcer (DFU) merupakan komplikasi serius Diabetes Melitus yang seringkali terlambat dideteksi di Fasilitas Kesehatan Tingkat Pertama (FKTP), seperti Puskesmas, akibat keterbatasan objektivitas dan akurasi tenaga kesehatan (nakes). Keterlambatan ini berujung pada peningkatan risiko amputasi dan beban biaya kesehatan. Kegiatan pengabdian ini bertujuan untuk mentransformasi kompetensi nakes di Puskesmas Jatiuwung, Kota Tangerang, dalam deteksi DFU melalui implementasi dan pelatihan sistem berbasis Deep Learning (Jaringan Saraf Tiruan Konvolusional/CNN) untuk analisis citra digital luka. Metode pengabdian yang digunakan meliputi survei awal (pre-test), pengembangan prototipe aplikasi deteksi, sesi pelatihan teoretis dan praktik intensif, serta evaluasi keberhasilan menggunakan post-test dan kuesioner kepercayaan diri (skala Likert). Hasil kegiatan menunjukkan peningkatan pengetahuan teoretis nakes secara signifikan, dengan rata-rata skor meningkat dari 48,3% menjadi 85,1% (p < 0.001). Selain itu, hasil kuesioner menunjukkan bahwa 96% peserta merasa Yakin atau Sangat Yakin untuk mengoperasikan sistem prototipe dalam alur kerja harian. Pelatihan ini berhasil mentransfer inovasi teknologi, secara efektif meningkatkan pengetahuan dan keterampilan praktis nakes, sekaligus menyediakan solusi deteksi dini yang objektif dan siap diintegrasikan ke dalam alur pemeriksaan Puskesmas untuk pencegahan amputasi dini.
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