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All Journal Jurnal SOLMA Jurnal Pustaka AI : Pusat Akses Kajian Teknologi Artificial Intelligence
Surgiwe, Surgiwe
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Mathematics Other

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Implementasi Solusi Teknologi untuk Pelayanan Kesehatan Lansia: Desain Tongkat Arduino dan Aplikasi Rekam Medis Lawi, Ansarullah; Hernando, Luki; Putera, Dimas Akmarul; Salimah, Nora; Surgiwe, Surgiwe
Jurnal SOLMA Vol. 13 No. 3 (2024)
Publisher : Universitas Muhammadiyah Prof. DR. Hamka (UHAMKA Press)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22236/solma.v13i3.16646

Abstract

Background: As the number of elderly individuals in Indonesia increases, the challenges in providing effective and efficient healthcare services become increasingly complex. One of the main issues faced by the elderly is the risk of falls due to limited mobility and declining physical performance. Additionally, the lack of integrated medical record management often hinders the timely and accurate delivery of medical services. This Community Service program aims to implement technological solutions in elderly care through the development of a smart cane (LansiaTracker) and a medical record application (LansiaCare). The smart cane (LansiaTracker) is equipped with various sensors to detect the user's physical condition, provide early warnings of fall risks, and monitor daily activities. Furthermore, the integrated medical record application (LansiaCare) allows for real-time management of the elderly's health data, making relevant health information easily accessible to family members and medical staff. Method: Socialization, training, and assistance for the elderly at Puskesmas Tiban Baru, aiming to enhance their quality of life and reduce health risks. Results: The use of the smart cane (LansiaTracker) and the medical record application (LansiaCare) not only effectively supports the mobility of the elderly but also improves their overall health monitoring. Conclusion: The implementation of this technology provides practical and affordable solutions for various elderly communities, especially those with limited access to healthcare facilities, enhancing responsiveness in emergency situations and facilitating comprehensive medical data recording and management.
Perancangan Sistem Pendeteksi Penyakit Pada Rumput Laut Dengan Menggunakan Metode Convolutional Neural Network Aritonang, Mhd Adi Setiawan; Abrar Masril, Muhammad; Chaniago, Deosa; Marshall Al Karim, Muhammad; Mahani Cunis, Viriya; Surgiwe, Surgiwe
Jurnal Pustaka AI (Pusat Akses Kajian Teknologi Artificial Intelligence) Vol 5 No 2 (2025): Pustaka AI (Pusat Akses Kajian Teknologi Artificial Intelligence)
Publisher : Pustaka Galeri Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55382/jurnalpustakaai.v5i2.1160

Abstract

Penelitian ini mengembangkan sistem deteksi penyakit pada rumput laut menggunakan metode Convolutional Neural Network (CNN) dengan YOLO v11. Sistem dilatih menggunakan data yang terdiri dari Healthy Seaweed, Kerak Bryozoan, dan ice-ice dari dataset Roboflow. Model YOLO v11m dengan 20 juta parameter dievaluasi menggunakan metrik presisi, recall, F1-Score, dan mAP. Hasil menunjukkan kinerja yang baik dalam deteksi penyakit dengan mAP50 sekitar 0.84 pada data validasi dan implementasi dalam aplikasi Web menggunakan Flask
Co-Authors Abrar Masril, Muhammad Chaniago, Deosa Dimas Akmarul Putera Hernando, Luki Lawi, Ansarullah Mahani Cunis, Viriya Marshall Al Karim, Muhammad Mhd Adi Setiawan Aritonang Salimah, Nora