إطار مقترح لتحقيق التكامل بين أسلوب تحليل النظم وتقنيات التنقيب عن البيانات بهدف دعم المراجع الخارجي لاكتشاف الأخطاء الجوهرية بالقوائم المالية والتقرير عن استمرارية المنشأة : دراسة ميدانية

Abstract EN

The study aimed to suggest a framework for achieving complementarity between the method of systems analysis and data mining techniques represented in neural networks in order to support the external auditor to discover the fundamental errors in the financial statements, and the report on the continuity of the facility when conducting the review process.

To achieve this goal, a set of sub-goals was derived.

The main hypothesis of the study was formulated as follows: There is no statistically significant relationship between the use of the proposed framework for achieving complementarity between the method of systems analysis and the style of neural networks as one of the data mining techniques and supporting the references to discover the fundamental errors in the financial statements, and the report on the continuity of the facility.

The study used the inductive and deductive approaches.

To achieve the goals of the study, the researchers built a questionnaire consisting of three axes, the first axis (20) statements, the second axis (20) statements, and the third axis (22) statements, and the study sample consisted of 93 statements from academics, systems analysts, auditors, internal auditors and financial analysts.

Among the most important results of the study: that the use of the systems analysis method individually did not lead to support the external auditor, while the use of the neural networks method individually led to the references support at an average rate.

The use of the proposed framework to achieve complementarity between the system analysis method and the neural network method as one of the data mining techniques resulted in the references support to discover the fundamental errors in the financial statements and helped in giving a report on the continuity of the facility.