ANALISIS IMPLEMENTASI MANAJEMEN PELAYANAN PUBLIK DALAM PENINGKATAN KUALITAS DATA POKOK PENDIDIKAN (DAPODIK) DI DINAS PENDIDIKAN KOTA TANGERANG (STUDI KASUS SMPN 27 KOTA TANGERANG)

Abstract

This study aims to determine and analyze how the Implementation of Public Service Management in Improving the Quality of Basic Education Data at SMPN 27 Tangerang City and recommendations or suggestions that can be given. This study uses a qualitative descriptive method. The qualitative approach was chosen because this study focuses on an in-depth analysis of the impact of the accuracy of teacher and student data on Dapodik on the planning of educational staff needs. The qualitative approach allows researchers to dig deeper into the phenomena that occur in the field by examining data in a certain context and understanding the meaning behind the interactions between the actors involved. Data collection techniques in this study used several methods, namely in-depth interviews, observations, and document analysis. The results of the study in indicator (1) Planning (Planning) The school have had quite good planning, such as a routine data update schedule and coordination with the Education Office. However, the socialization of the importance of Dapodik to all stakeholders (teachers, students, parents) is still lacking, resulting in delays in reporting data changes. (2) Organizing, The Dapodik team structure is clear with the appointment of special operators and division of tasks. Obstacles arise due to the lack of synergy between operators and teachers/staff in delivering change data (eg: student transfers). (3) Actuating, Dapodik operators have carried out their duties well thanks to training from the office, but there are still input errors due to lack of re-verification. The operator's time constraints (who also have other tasks) affect the consistency of data input. (4) Controlling, Internal monitoring by the school IT team and external validation by the office have been running, but the frequency is not optimal. There is no reward and punishment system to motivate data accuracy