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All Journal Jurnal Sustainable: Jurnal Hasil Penelitian dan Industri Terapan Jurnal Pengabdian Masyarakat Khatulistiwa Society: Jurnal Pengabdian Masyarakat Journal International Inspire Education Technology (JIIET) Jurnal Keperawatan dan Kesehatan (JKK) Jurnal Psikologi dan Konseling West Science Indonesian Journal of Multidisciplinary on Social and Technology Jurnal Kajian Pendidikan dan Psikologi Jurnal Pengabdian Masyarakat dan Riset Pendidikan Jurnal Inovasi Global Digulis: Jurnal Pengabdian Pada Masyarakat
Sujatmiko, Wandi
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Arts Humanities Astronomy Computer Science & IT Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Neuroscience Nursing Public Health Social Sciences Other

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Penggunaan Blog Sebagai Manfaat Teknologi Untuk Media Promosi UMKM Kota Pontianak Wulandari, Mira; Faqih, Muhammad; Sujatmiko, Wandi; Hermanto, Hermanto; Prasetya , Irwan Adhi
Jurnal Inovasi Global Vol. 4 No. 4 (2026): Jurnal Inovasi Global
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/jig.v4i4.531

Abstract

Advances in digital technolgy require Micro, Small, and Medium Enterprise (UMKM) in Pontianak City to adspt to online marketing strategies to remain competitive, particularly in expanding market reach and increasing sales. This study aims to analyze the use of blogsas an effective, effcient, and low-cost digital promotional medium for UMKM. The method used is mentoring and training in blog content creation for UMKM in Pontianak City. The results show that blogs offer advantages in the form of flexibility in presenting in-depth product information, building brand identity, and increasing visiility in search engines (SEO) compared to conventional social media. Through the use of blogs, UMKM can overcome limited promotional budgets while still reaching a wider audience in a professional manner. This mentoring has been proven to help business actors in digitalizing the marketing of Pontianak’s culnary products.
IMPLEMENTASI DEEP LEARNING DALAM SISTEM DETEKSI MANDIRI BERBASIS MOBILE UNTUK LUKA DIABETIK GUNA MENDUKUNG KESEHATAN MASYARAKAT Hermanto, Hermanto; Adhi Prasetya, Irwan; Faqih Dzulqarnain, Muhammad; Wulandari, Mira; Sujatmiko, Wandi; Habibi, Muhammad
Jurnal Keperawatan dan Kesehatan Vol 17 No 1 (2026): Jurnal Riset Keperawatan dan Kesehatan
Publisher : Institut Teknologi dan Kesehatan Muhammadiyah Kalimantan Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54630/jk2.v17i1.586

Abstract

Diabetic foot ulcers affect 15-25% of diabetic patients globally, causing significant morbidity, healthcare costs, and amputation risks. Early detection is crucial for preventing severe complications, yet limited access to specialized healthcare services, especially in remote areas, creates substantial barriers to timely wound management. This study developed a mobile-based self-detection system using deep learning technology to enable early diabetic wound identification and improve healthcare accessibility for patients in resource-limited settings. A Convolutional Neural Network with MobileNetV2 architecture was trained on over 5,000 diabetic wound images categorized into five classes: healthy skin and Wagner grades 1-4 ulcers. The cross-platform mobile application features AI-based wound detection, diagnosis history tracking, educational content, and integrated telemedicine consultation. Clinical validation compared AI predictions with three certified wound care specialists across 500 cases, while usability testing involved 100 diabetic patients.The model achieved 92.4% accuracy with 94.2% sensitivity and 91.7% specificity. For high-grade ulcers, performance improved to 96.8% sensitivity with 1.8-second processing time per image. Clinical validation showed substantial agreement with specialists (Cohen's kappa = 0.89). The application scored 82.5/100 on System Usability Scale with 88.5% user satisfaction and 91.2% willing to recommend it. This mobile-based deep learning system demonstrates high accuracy and clinical reliability for diabetic wound self-detection, successfully bridging healthcare gaps for underserved populations and showing significant potential for early intervention and healthcare cost reduction.
Co-Authors Adhi Prasetya, Irwan Adriansyah , Herry Arianti, Tia Assabana, Mohammad Syahru Faqih Dzulqarnain, Muhammad Farawowan, Fauziah F Hariansyah Haribowo, Rio Hermanto Hermanto Irwan Adhi Prasetya, Irwan Adhi Isfauzi Hadi Nugroho Judijanto, Loso Muhammad Faqih Muhammad Habibi Muhammad Rusdi Nastiti, Arum Eki Otong Sulaeman, Otong Pattiasina, Petrus Jacob Prasetya , Irwan Adhi Raden Firman Nurbudi Prijambodo Ramli, Akhmad Saputra, Fiolan Rangga Siswahyudianto Subroto, Desty Endrawati Sukini, Sukini Sularno Sularno, Sularno Wariunsora, Marlen Wulandari, Mira Yuanyuan Wang, Yuanyuan Zou, Guijiao