The System Feature Identification for Accelerating Government Human Capital Knowledge Improvement

Dana Indra Sensuse, Elin Cahyaningsih, Wahyu Catur Wibowo, Handrie Noprisson, Vina Ayumi, Marissa Utami, Erwin Dwika Putra, Nur Ani


The knowledge management system is information technology to support knowledge management activities in an organization. Defining KMS features in government institutions can be conducted by identifying the KM process is represented by some indicators. Many studies have been done in developing the KM system in various sectors. However, research on the KM system in human capital management has not yet been much published. This research aims to define a priority order of knowledge management process and identify knowledge management system features for Government Human Capital Management. Data collection has been done by distributing questionnaires (253 respondents) and interviewing stakeholders (9 experts) of the institution for human capital management in Indonesia (KemenPAN&RB, BKN, and LAN. We used three analysis methods: the Analytical Hierarchy Process (AHP), Pearson Correlation (Pearson’s R), and the Expert Judgment method. As a result, we found major features of KM system for HCM in Indonesia, including electronic group discussion (best practice and lesson learn), work performance evaluation (daily activities and profile), communication tools (e-mail, chat and video conference), document management (digital document and physical document) and expertise management (decision support, expertise locator and expert knowledge). The limitation of this study is the topic of research specific to the KM system for government human capital management in Indonesia. The object research only three government ministries appointed to be government human capital management managers. Recommendation KM system in the government institution must be implemented to facilitate KM process align with the organizational strategy and objectives.


Knowledge management; analytical hierarchy process; human capital; Pearson correlation; government.

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