کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6901023 1446492 2017 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
NUSANTARA: A New Model of Knowledge Management in Government Human Capital Management
ترجمه فارسی عنوان
ناسانتارا: مدل جدید مدیریت دانش در مدیریت سرمایه انسانی دولت
کلمات کلیدی
مدیریت دانش، مدل مدیریت دانش، مدیریت سرمایه انسانی دولت، سرمایه انسانی دولت، راه حل مدیریت دانش، پایه،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر علوم کامپیوتر (عمومی)
چکیده انگلیسی
Knowledge management is one of organizational strategy to improve the organizational competitive value. Align with presidential regulation No. 81 Year 2010 about bureaucratic reform and PERMENPAN&RB No. 20 year 2010 about bureaucratic reform roadmap declare that one bureaucratic reform objective are human capital development. This program is important to increase the public service. Three government ministries based on the UU No. 5 Year 2014 about Government Human Capital assigned to manage them. This research aims to develop the model of knowledge management for government human capital management. Research object implicate State Ministry for State Apparatus Reform (KEMENPAN & RB), National Civil Service Agencies (BKN) and National Institute of Public Administration (LAN). While the research stages are identify the strategic issue, develop the theoretical model, evaluate the theoretical model, identify the element model and knowledge and the last develop the model. Data analysis uses multiple methods in qualitative and quantitative technique. This model was developed using hybrid and synthesis method from the theoretical model of Indonesian knowledge management, knowledge management solution and foundation and the APO framework KMP. The model of government human capital knowledge management of Republic Indonesia (NUSANTARA) consist of eight component there are vision and mission, CSF, KM Mechanisms and Technologies, KMS, KM cycle, KM process, organizational core knowledge and outcome (government public services).
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Procedia Computer Science - Volume 124, 2017, Pages 61-68
نویسندگان
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