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All Journal Infokes : Jurnal Ilmiah Rekam Medis dan Informasi Kesehatan SEJAGAT : Jurnal Pengabdian Masyarakat
Muhammad Ifantara Putra
Politeknik Negeri Jember
Agriculture, Biological Sciences & Forestry Computer Science & IT Engineering Health Professions Medicine & Pharmacology Nursing Public Health Veterinary Other

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Pemberdayaan TEFA Inovasi Kesehatan (V-Kes) melalui Pelatihan Rekam Medis Elektronik bagi Tenaga Kesehatan di Kabupaten Jember Dony Setiawan Hendyca Putra; Mochammad Choirur Roziqin; Sabran; Tegar Wahyu Yudha Pratama; Ihwan Huda Al Mujib; Assyifa Itsnainia Mustika; Muhammad Ifantara Putra; Anggi Maulidya; Moh Lutfi Rizalul Hakim
SEJAGAT : Jurnal Pengabdian Masyarakat Vol. 2 No. 3 (2025): Desember
Publisher : P3M Politeknik Negeri Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25047/sejagat.v2i3.6731

Abstract

The uneven understanding and skills of health workers in the use of Electronic Medical Records (EMR) at the primary care level, especially in the Jember Regency, is a fundamental problem that hinders the acceleration of digital transformation in the health sector. This condition is further complicated by the mandatory implementation of EMR in accordance with Ministry of Health regulations, which also covers independent health worker practices, which are not yet fully understood and optimally responded to in the field. Additionally, access to practical and applicable EMR training remains limited, while the role of the Teaching Factory for Health Innovation (V-KES) as a digital health training center has not been fully utilized. The lack of post-training assistance has contributed to difficulties in implementing RME in daily practice, compounded by a low level of understanding of the urgency of transitioning from manual to digital systems, which affects the mental and technical readiness of health workers. Therefore, the solutions offered include 1) Conducting RME training based on hands-on practice, 2) Provision of modules or pocket books, dissemination of regulations in infographic or short video formats, 3) Utilization of the V-KES Teaching Factory as a simulation training center with Ministry of Health standard software, involvement of academic facilitators and health IT practitioners, as well as continuous online and offline assistance. This program will also be accompanied by strengthening the V-KES curriculum and promoting a digital mindset shift to support the full readiness of independent healthcare practitioners in implementing a nationally integrated RME system.
Medical Record-Based Prediction of Type 2 Diabetes Mellitus Risk Using the Naïve Bayes Algorithm Mochammad Choirur Roziqin; Nabila Ersa Wulandari; Bakhtiyar Hadi Prakoso; Dony Setiawan Hendyca Putra; Muhammad Ifantara Putra; Gamasiano Alfiansyah
Jurnal Infokes Vol 16 No 2 (2026): Jurnal Ilmiah Rekam Medis dan Informatika Kesehatan
Publisher : Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47701/gjtc0v25

Abstract

Background: Type 2 diabetes mellitus is a non-communicable disease with a high prevalence and the potential to cause serious complications if not properly managed. Identifying risk factors is an essential step in the prevention and control of this disease. Objective: This study aimed to develop and evaluate a medical record-based prediction model for type 2 diabetes mellitus risk using the Naïve Bayes algorithm and to identify the most influential risk factors among hospitalized patients at Bhayangkara Bondowoso Hospital in 2024. Methods: A descriptive quantitative research design was employed, with data processing conducted using the Naïve Bayes algorithm and RapidMiner software. The sampling technique used was total sampling, resulting in 630 medical records, consisting of 315 patients diagnosed with type 2 diabetes mellitus and 315 non-type 2 diabetes mellitus patients. The analyzed variables included age, sex, body mass index (BMI), hypertension, smoking history, cardiovascular disease history, and family history. Results: The results indicated that the most influential risk factors for type 2 diabetes mellitus were age ?45 years, obesity-level BMI, and a history of hypertension. Conclusion: The Confusion Matrix evaluation with a 95%:5% split ratio produced an accuracy of 90.62%, a precision of 100%, and a recall of 81.25%. Suggestion: Hospitals are encouraged to strengthen health promotion programs regarding type 2 diabetes mellitus risk factors and involve patients’ families in educational interventions to help prevent disease-related complications.
Co-Authors Anggi Maulidya Assyifa Itsnainia Mustika Bakhtiyar Hadi Prakoso dony setiawan hendyca putra Gamasiano Alfiansyah Ihwan Huda Al Mujib Mochammad Choirur Roziqin Moh Lutfi Rizalul Hakim Nabila Ersa Wulandari Tegar Wahyu Yudha Pratama