scholarly journals Analytic Procedures: A Holdback-vetting Forecasting Model

2017 ◽  
Vol 3 (1) ◽  
pp. 65
Author(s):  
Edward J. Lusk
Keyword(s):  
Decision Support ◽  
Open Access ◽  
Best Practices ◽  
Decision Support System ◽  
Regression Model ◽  
Confidence Intervals ◽  
Random Effects ◽  
Support System ◽  
Forecasting Model ◽  
Ols Regression

Introduction: Forecasting is now a best practices requirement for PCAOB audits. This is clear from AS 5 where Analytic Procedures are now a part of the Planning and Substantive Phases of the certification audits. In this regard, we are encouraged by the “On the Go Stores” AP case offered by the AICPA, and have extended their case illustration of AP treatments.Study Précis: In our presentation, we initially consider the OLS Regression model utilized in the AICPA case and offer a vetting protocol to rationalize the use of this forecasting model in the AP phases. Then we move to a disposition analysis stage where the forecast information is posed in relief to the actual client value so as to ascertain if Extended Procedure investigations would be warranted.Results: We offer three Confidence Intervals drawn from the OLS modeling system that are formed from the Fixed Effect, Random Effects, and finally the Excel Platform for the 95% CI parameter set.Impact: The protocol set is programmed in an open-access VBA Decision Support System which is available free as a download with no restriction on its use.

scholarly journals A Robust Newcomb-Benford Account Screening Profiler: An Audit Decision Support System

2017 ◽  
Vol 8 (3) ◽  
pp. 27
Author(s):  
Frank Heilig ◽  
Edward J. Lusk
Keyword(s):  
Decision Support ◽  
Best Practices ◽  
Decision Support System ◽  
Decision Support Systems ◽  
Support System ◽  
Support Systems ◽  
Programming Tools ◽  
The Many ◽  
Exclusive Sets

The best practices execution of the audit is conditioned by the facility with which Decision Support Systems [DSS] can be created using simple Excel™ programming tools and functionalities. Such DSS can aid in the exclusive binary triage of the many of the client’s accounts each of which typically has tens of thousands of items into: {Accounts that may warrant Extended Procedures Testing [EPT]} or {Accounts that may not warrant EPT}. We use the Newcomb-Benford first-digit-profile as a triage platform to screen client accounts into the above mentioned exclusive sets. We call this DSS: The Newcomb-Benford Robust Screening:DSS [NBRS:DSS]. We report on the details of its development & vetting, and illustrate its functionalities using one of the historical Benford Datasets. The NBRS:DSS employs four account screening platforms each of which has been reported in the literature. The NBRS:DSS is available from the authors free as a download without restrictions to its use.

Decision Support System Development Based On Android Using Analytical Hierarchy Process (AHP) Method For Determining The Middle Small Business Development Priority In Sorong City

2019 ◽  
Vol 5 (2) ◽  
pp. 25-39
Author(s):  
Luluk Suryani ◽  
Raditya Faisal Waliulu ◽  
Ery Murniyasih
Keyword(s):  
Decision Support ◽  
Small Business ◽  
Decision Support System ◽  
Support System ◽  
Analytical Hierarchy Process ◽  
System Development ◽  
Business Development ◽  
Ahp Method ◽  
Small Business Development ◽  
Hierarchy Process

Usaha Kecil Menengah (UKM) adalah salah satu penggerak perekonomian suatu daerah, termasuk Kota Sorong. UKM di Kota Sorong belum berkembang secara optimal. Ada beberapa penyebab diantaranya adalah mengenai finansial, lokasi, bahan baku dan lain-lain. Untuk menyelesaikan permasalah tersebut peneliti terdorong untuk melakukan pengembangan Aplikasi yang dapat membantu menentukan prioritas UKM yang sesuai dengan kondisi pelaku usaha. Pada penelitian ini akan digunakan metode Analitycal Hierarchy Process (AHP), untuk pengambilan keputusannya. Metode AHP dipilih karena mampu menyeleksi dan menentukan alternatif terbaik dari sejumlah alternatif yang tersedia. Dalam hal ini alternatif yang dimaksudkan yaitu UKM terbaik yang dapat dipilih oleh pelaku usaha sesuai dengan kriteria yang telah ditentukan. Penelitian dilakukan dengan mencari nilai bobot untuk setiap atribut, kemudian dilakukan proses perankingan yang akan menentukan alternatif yang optimal, yaitu UKM. Aplikasi Sistem Pendukung Keputusan yang dikembangkan berbasis Android, dimana pengguna akan mudah menggunakannya sewaktu-waktu jika terjadi perubahan bobot pada kriteria atau intensitas.  Hasil akhir menunjukkan bahwa metode AHP berhasil diterapkan pada Aplikasi Penentuan Prioritas Pengembangan UKM.

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