<![CDATA[This study employs a qualitative descriptive approach to evaluate the performance of the Regional Inspectorate in Agam Regency, focusing on achieving quality human resources. The research aims to understand the complexities and dynamics of the investigated issues by obtaining naturalistic data from the field. The post-positivist philosophy underpins this qualitative research, which seeks to explore, discover, explain, and understand social phenomena that are not easily measured or explained using quantitative methods. Drawing on the five qualitative research approaches proposed by John W. Creswell (narrative, phenomenological, grounded theory, ethnographic, and case study), the case study approach is adopted to delve deeper into the evaluation of the Regional Inspectorate's performance in nurturing quality human resources. The study's primary data sources consist of personnel within the Regional Inspectorate, including Inspectors, Secretaries, Assistant Regional Inspectors, Auditor and PPUPD Functional Officers, as well as employees in the Inspectorate's Secretariat. Secondary data sources encompass educational backgrounds of the personnel and the types of training or workshops they have participated in. Data collection techniques involve interviews, observations, and document analysis. Data analysis commences before entering the field and continues throughout the data collection process. Miles and Huberman's qualitative data analysis method is employed, involving data reduction, data display, and conclusion drawing/verification. The evaluation of the Regional Inspectorate's performance to achieve quality human resources should consider effectiveness in attaining defined objectives, efficient utilization of available resources, adequate provision of services and support for staff development, fairness in treatment and access to development opportunities, responsiveness to staff needs and aspirations, and informed policy and program implementation. Keywords: Evaluation, Performance, HR, Effectiveness, Efficiency]]>
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