Efektifitas Penggunaan Aplikasi Pintar Berbasis Android dan Machine Learning untuk Pengkajian Diabetic Foot Ulcer di Rsud Dr. Dradjat Prawiranegara Serang
DOI:
https://doi.org/10.55606/jurritek.v3i2.6007Keywords:
Android, Diabetic Foot Ulcer, Machine Learning, AssessmentAbstract
Diabetic wounds have quite serious impacts on sufferers, so a comprehensive wound assessment must be carried out. However, currently there are still many nurses who carry out wound assessments only relying on the nurse's experience in assessing wound characteristics. The use of a digital application (Dicafoler) is a solution to be used as a tool to comprehensively assess diabetes wounds so that it can minimize the impact of the risk of infection and amputation. The aim of this research is to describe the use of the dicafoler application as a tool to assess diabetes wounds among nurses at RSUD Dr. Dradjat Prawiranegara Serang. The research design used in this research is Quantitative Description. Sampling technique with a total sampling of 24 respondents. The results of this research were that the age of the executive nurses was young adults (25-35 years), the dominant sex was that the executive nurses were female, the educational level of the executive nurses was at most D3 nursing, the length of service of the executive nurses was >5 years. Bivariate results show that the use of Dicafoler is effective in assessing wounds more accurately. The conclusion of this research is that the Dicafoler application can be easily used to assist in the process of assessing diabetic wounds, but it requires further development through further research to add incomplete features so that a comprehensive assessment can be carried out.
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