Identifying and measuring information content of financial statements in audit reporting adjustment

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

Bakhshi Ali; Yazdani Shohreh; Khanmohammadi Mohammadhamed; Maleki Ali

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: INTERNATIONAL JOURNAL OF NONLINEAR ANALYSIS AND APPLICATIONS Year:2023 | Volume:14 | Issue:8 Page(s): 119-127

Download Full-Text

View:

Download:

Cites:

Information Journal Paper

Title

Identifying and measuring information content of financial statements in audit reporting adjustment

Author(s)

Bakhshi Ali | Yazdani Shohreh | Khanmohammadi Mohammadhamed | Maleki Ali | Issue Writer Certificate

Keywords

Auditor's report type

J48 algorithm

Random forest

Abstract

Making economic decisions and allocating resources optimally without the presence of valid and reliable data is not possible. Capital flows towards superior economic activities when capitalist decisions rely on timely, relevant and reliable information. In this regard, auditing plays a vital role in determining the validity of information; in other words, given the accountability requiring the presence of valid and reliable data, it can be stated that auditing is one of the fundamental accountability processes. In the current research, an optimum prediction method for independent Auditor's report types is selected and two approaches of the J48 algorithm and Random forest are compared. This research has been conducted on 84 corporates during 2008-2017. In order to train, test and investigate the research variables, Weka software was used. The dependent variable is the Auditor's report type. Results indicated that the accuracy of the J48 algorithm has been 72.61% and 60.42% in training and test sections, respectively and the accuracy of the Random forest has been 94.57% and 63.09% in training and test sections, respectively; so, the Random forest model is more effective.

Multimedia

No record.

Cites

No record.

References

No record.

Cite

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans