优化中小微型企业的信息系统管理:提高质量的 COBIT 5 框架方法

Ramadhan Syaeful Bahri, Yeffry Handoko Putra
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引用次数: 0

摘要

本研究旨在为中小微型企业(MSMEs)的信息系统管理建立一个框架,重点关注先进和新兴中小微型企业集群的决策过程。COBIT 5 用于确定变量和指导研究阶段。研究将特别考察位于万隆区的微小中型企业。对每个目标(包括培育型中小微企业和先进型中小微企业)的治理质量进行评估时,将使用 COBIT 5 衍生的流程评估模型 (PAM)。除了通过在万隆区进行的访谈和调查收集初步数据外,这项初步调查还包括对以往研究中使用的有关研究主题的各种方法进行比较分析。研究结果表明,万隆地区中小微企业的数据处理程序涉及到计算机/笔记本电脑设备的使用。然而,某些中小微企业在充分管理所获得的数据方面面临挑战,这强调了更有效的数据管理的必要性,以确保所生成的数据达到构建先进中小微企业模型所需的质量。相反,万隆地区的其他一些中小微企业则表现出熟练的数据管理实践,对数据和信息进行定期评估,并根据分析数据做出决策。这两种情况可作为了解新兴和先进中小微企业数据决策过程的基准。我们希望这项研究的成果能够成为一个基准,为中小微企业提供最佳实践,以提高决策质量,实现卓越的业务运营。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimizing Information System Management in Micro, Small, and Medium Enterprises: A COBIT 5 Framework Approach for Enhanced Quality
This study aims to establish a framework for governing information systems in Micro, Small, and Medium Enterprises (MSMEs), focusing on decision-making processes in advanced and emerging MSME clusters. COBIT 5 is employed to identify variables and guide the research stages. The research will specifically examine MSMEs located in Bandung District. The evaluation of governance quality for each target, which includes Nurtured MSMEs and Advanced MSMEs, involves utilizing the Process Assessment Model (PAM) derived from COBIT 5. In addition to gathering preliminary data through interviews and surveys conducted in Bandung District, this initial investigation also involved a comparative analysis of various methods employed in prior research about the study's subject matter. The findings from this study reveal that the data processing procedures for MSMEs in the Bandung Regency involve the use of computer/laptop devices. However, certain MSMEs face challenges in adequately managing the acquired data, emphasizing the necessity for more effective data management to ensure the produced data attains the quality required for constructing a model for advanced MSMEs. On the contrary, some other MSMEs in the Bandung Regency exhibit proficient data management practices, conducting regular evaluations of data and information, and basing their decisions on the analyzed data. These two scenarios serve as benchmarks for understanding the decision-making processes of both emerging and advanced MSMEs about data. The aspiration is that the outcomes of this study can serve as a benchmark, offering best practices for MSMEs to enhance the quality of their Decision-Making and achieve excellence in their business operations.
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