在林波托街道总行哥伦塔洛区实施指纹电子考勤政策

Rahmat Manguleta, Arifin Tahir, Sukarman Kamuli
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引用次数: 1

摘要

我们对Limboto街道总部Gorontalo区指纹电子考勤政策的实施进行了分析,并分析了其成功的因素。我们采用描述性定性方法,通过访谈、观察和文献三种方式收集数据。数据分析采用Mills和Huberman的分析模型,通过该模型对数据进行简化、呈现、验证并得出结论。研究结果表明:1)指纹电子考勤政策在林波托街道总行Gorontalo区得到了很好的实施,政策规划、实施和监督都很到位;2)决定Limboto街道总行Gorontalo区实施指纹电子考勤政策的因素有:沟通、资源、配置、官僚结构、不可抗力。实施成功地提高了PNS的纪律和性能。我们可以从以下方面看出这一点:他们是多么有纪律,按时到达办公室和回家;当手工考勤系统转换为电子考勤系统时,他们是如何准备的;以及在政策实施方面,领导和员工之间的沟通是多么良好。此外,他们的纪律在2020年11月的电子考勤报告中得到了定量证明,考勤率达到94%。然而,我们也发现了一些挑战,例如设施限制,几个边缘村庄的养殖问题,以及COVID-19大流行造成的不可抗力。
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IMPLEMENTING THE FINGERPRINT ELECTRONIC ATTENDANCE POLICY IN THE LIMBOTO SUBDISTRICT HEAD OFFICE GORONTALO DISTRICT
We confer an analysis of the implementation of fingerprint electronic attendance policy in the Limboto subdistrict head office Gorontalo District and factors contributing to its success. We used a descriptive qualitative method and collected data in three manners, i.e., interview, observation, and documentation. Data were analyzed using Mills and Huberman’s analysis model, through which we reduced, presented, and verified data as well as drew conclusions. Findings demonstrate that 1) The fingerprint electronic attendance policy had been well implemented in the Limboto subdistrict head office Gorontalo District, attested by well-convened policy planning, implementation, and supervision; 2) Factors determining the implementation of fingerprint electronic attendance policy in the Limboto subdistrict head office Gorontalo District were communication, resources, disposition, bureaucratic structure, and force majeure. The implementation had succeeded in elevating PNS discipline and performances. We could see this in how discipline they were to arrive in the office and go home by schedule, how prepared they were when the manual attendance system was converted to the electronic one, and how good the communication between the head and staff as regards the policy implementation was. Additionally, their discipline was quantitatively proven by the report of electronic attendance in November 2020, which reached 94%. However, we also found some challenges, e.g., facility constraints, breeding problems in several marginalized sub-villages, and force majeure because of the COVID-19 pandemic.
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