A Proposal for Outlier and Noise Detection in Public Official's Affidavits

Outlier and noise detection processes are highly useful in the quality assessment of any kind of database. Such processes may have novel civic and public applications in the detection of anomalies in public data. The purpose of this work is to explore the possibilities of experimentation with, validation and application of hybrid outlier and noise detection procedures in public officials' affidavit systems currently available in Argentina.Red de Universidades con Carreras en Informátic

A Proposal for Outlier and Noise Detection in Public Official's Affidavits

Outlier and noise detection processes are highly useful in the quality assessment of any kind of database. Such processes may have novel civic and public applications in the detection of anomalies in public data. The purpose of this work is to explore the possibilities of experimentation with, validation and application of hybrid outlier and noise detection procedures in public officials' affidavit systems currently available in Argentina.Red de Universidades con Carreras en Informátic

Comparing Outlier Detection Methods using Boxplot Generalized Extreme Studentized Deviate and Sequential Fences

Outliers identification is essential in data analysis since it can make wrong inferential statistics. This study aimed to compare the performance of Boxplot, Generalized Extreme Studentized Deviate (Generalized ESD), and Sequential Fences method in identifying outliers. A published dataset was used in the study. Based on preliminary outlier identification, the data did not contain outliers. Each outlier detection method's performance was evaluated by contaminating the original data with few outliers. The contaminations were conducted by replacing the two smallest and largest observations with outliers. The analysis was conducted using SAS version 9.2 for both original and contaminated data. We found that Sequential Fences have outstanding performance in identifying outliers compared to Boxplot and Generalized ESD

A Meta-Model for Real-Time Fraud Detection in ERP Systems

Fraud is a worldwide issue affecting almost every organization once in a time. Recent studies have shown that fraudulent behavior impacts up to 5 % of a companies annual revenue. Information systems (IS) have become an integral part of every modern organization. They contain the data foundation of the entire company and thereby supporting business processes and day-to-day transactions. Although an IS usually contains control mechanisms to prevent different kinds of fraud, these mechanisms look insufficient, considering the role of IS in many fraud cases. Since many cases from different companies have shown the need for an appropriate countermeasure, we want to develop an application that efficiently detects fraud and fraudulent behavior. Therefore, we conducted a structured literature review and a qualitative survey to apply the design science research (DSR) methodology and derive requirements for a fraud detection system (FDS). As a result, we present a meta-model for a FDS for enterprise resource planning (ERP) systems. We also provide application requirements, principles, and features that define areas for further research

Una propuesta para la detección de datos anómalos y ruido en declaraciones juradas públicas

Outlier and noise detection processes are highly useful in the quality assessment of any kind of database. Such processes may have novel civic and public applications in the detection of anomalies in public data. The purpose of this work is to explore the possibilities of experimentation with, validation and application of hybrid outlier and noise detection procedures in public officials' affidavit systems currently available in Argentina.Red de Universidades con Carreras en Informátic

Propuesta de detección de datos anómalos y ruido en declaraciones juradas públicas

Los procesos de detección de campos anómalos y con ruido son de suma utilidad para la evaluación de calidad de bases de datos de todo tipo. Estos procesos pueden tener una utilidad cívica y pública inédita si se encuentran dirigidos a la detección de valores anómalos en datos públicos. En este trabajo, se propone investigar la posibilidad de experimentación, validación y aplicación de procedimientos híbridos de detección de datos anómalos y ruido en sistemas de declaraciones juradas oficiales disponibles actualmente en Argentina.Outlier and noise detection processes are highly useful in the quality assessment of any kind of database. Such processes may have novel civic and public applications in the detection of anomalies in public data. The purpose of this work is to explore the possibilities of experimentation with, validation and application of hybrid outlier and noise detection procedures in public officials’ affidavit systems currently available in Argentina.XIII Workshop Base de Datos y Minería de DatosRed de Universidades con Carreras en Informática (RedUNCI

Propuesta de detección de datos anómalos y ruido en declaraciones juradas públicas

Los procesos de detección de campos anómalos y con ruido son de suma utilidad para la evaluación de calidad de bases de datos de todo tipo. Estos procesos pueden tener una utilidad cívica y pública inédita si se encuentran dirigidos a la detección de valores anómalos en datos públicos. En este trabajo, se propone investigar la posibilidad de experimentación, validación y aplicación de procedimientos híbridos de detección de datos anómalos y ruido en sistemas de declaraciones juradas oficiales disponibles actualmente en Argentina.Outlier and noise detection processes are highly useful in the quality assessment of any kind of database. Such processes may have novel civic and public applications in the detection of anomalies in public data. The purpose of this work is to explore the possibilities of experimentation with, validation and application of hybrid outlier and noise detection procedures in public officials’ affidavit systems currently available in Argentina.XIII Workshop Base de Datos y Minería de DatosRed de Universidades con Carreras en Informática (RedUNCI

Propuesta de detección de datos anómalos y ruido en declaraciones juradas públicas

Los procesos de detección de campos anómalos y con ruido son de suma utilidad para la evaluación de calidad de bases de datos de todo tipo. Estos procesos pueden tener una utilidad cívica y pública inédita si se encuentran dirigidos a la detección de valores anómalos en datos públicos. En este trabajo, se propone investigar la posibilidad de experimentación, validación y aplicación de procedimientos híbridos de detección de datos anómalos y ruido en sistemas de declaraciones juradas oficiales disponibles actualmente en Argentina.Outlier and noise detection processes are highly useful in the quality assessment of any kind of database. Such processes may have novel civic and public applications in the detection of anomalies in public data. The purpose of this work is to explore the possibilities of experimentation with, validation and application of hybrid outlier and noise detection procedures in public officials’ affidavit systems currently available in Argentina.XIII Workshop Base de Datos y Minería de DatosRed de Universidades con Carreras en Informática (RedUNCI