Digital Training Recommendations for Enhancing Healthcare Human Resource Competence Using the Simple Additive Weighting Algorithm - Maulindar, Joni; Dewi, Nandita Sekar Sukma; Mustapha, Jawahir Che (Proceeding of the International Conference Health, Science And Technology (ICOHETECH), 2025)
The main challenge in digital transformation within the healthcare sector lies in the limited mapping of human resources’ (HR) readiness toward information technology. This study aims to evaluate the digital readiness level of healthcare human resources using a data-driven approach. The Simple Additive Weighting (SAW) method was applied, utilizing six variables whose weights were determined through expert discussions. The results show that respondents’ digital readiness scores range from 0.800 to 0.858. The highest score was achieved by R011 (Doctor, Outpatient Department) with a score of 0.858, indicating excellent digital literacy and effective utilization of information systems. A score of 0.828 was obtained by R032 (Medical Records Administration, ICU), R035 (Midwife, Polyclinic), and R025 (Doctor, Outpatient Department), suggesting relatively even readiness levels. The lowest score, 0.800, belonged to R026 (Laboratory Analyst, Polyclinic), which still falls within the high-readiness category but indicates the need for improvement in health data analysis skills. The overall average score was 0.828, confirming that the majority of healthcare personnel demonstrate good digital readiness. These findings highlight the effectiveness of the SAW method in providing data-driven recommendations for digital capacity development. Moreover, the results can serve as a foundation for designing more targeted and efficient training programs. Overall, this study demonstrates that SAW-based mapping can effectively support strategic decision-making in the digital transformation of healthcare services.