ahmed rohan (17 résultats)

Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Seminar paper from the year 2017 in the subject Computer Science - Commercial Information Technology, grade: 1.7, Heilbronn University, language: English, abstract: Today almost every software and websites has a mobile compatible version and everyone can check anything on his mobile or tablet. This wasn't the case 7-8 years ago. For SAP, Graphical User Interface as known as GUI was very powerful at the time when SAP launched its ERP software. With time, many other software exists with the fleet of HTML5 based powerful and more appealing modern UI-technology.For this, the old GUI was not able to stand with it. As everyone knows, today are smartphones and tablets more powerful than pc's. So, it was very important for SAP to find a solution and its was SAP Fiori - 'One UX for all SAP Products'. Fiori is based on a framework known as SAPUI5 which is built on top of HTML5 and is compatible with any device and any screen size. The first announcement from SAP about Fiori was in May 2013 with the first release of 25 transactional Fiori apps for the most common business functions, such as self-services tasks which known as ESS/MSS.Today, there are more than 1140 true Fiori apps available in Fiori library. The number of apps can partially supplement the previous GUI transactions. SAP offers three types of Fiori apps with different database requirements. A distinction is made between Transactional apps, Analytical apps and factsheets. Only Transactional apps can run on any database that supports SAP ERP. The other 2 types require SAP HANA as database. Since 2013, Fiori has made great progress and will continue in the coming years.

Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Seminar paper from the year 2016 in the subject Computer Science - General, grade: 1.7, Heilbronn University, language: English, abstract: In this seminar thesis you will get a view about the Data Mining techniques in financial fraud detection. Financial Fraud is taking a big issue in economical problem, which is still growing. So there is a big interest to detect fraud, but by large amounts of data, this is difficult. Therefore, many data mining techniques are repeatedly used to detect frauds in fraudulent activities. Majority of fraud area are Insurance, Banking, Health and Financial Statement Fraud. The most widely used data mining techniques are Support Vector Machines (SVM), Decision Trees (DT), Logistic Regression (LR), Naives Bayes, Bayesian Belief Network, Classification and Regression Tree (CART) etc. These techniques existed for many years and are used repeatedly to develop a fraud detection system or for analyze frauds.

Taschenbuch. Etat : Neu. Neuware -Seminar paper from the year 2017 in the subject Computer Science - Commercial Information Technology, grade: 1.7, Heilbronn University, language: English, abstract: Today almost every software and websites has a mobile compatible version and everyone can check anything on his mobile or tablet. This wasn¿t the case 7-8 years ago. For SAP, Graphical User Interface as known as GUI was very powerful at the time when SAP launched its ERP software. With time, many other software exists with the fleet of HTML5 based powerful and more appealing modern UI-technology.For this, the old GUI was not able to stand with it. As everyone knows, today are smartphones and tablets more powerful than pc¿s. So, it was very important for SAP to find a solution and its was SAP Fiori ¿ ¿One UX for all SAP Products¿. Fiori is based on a framework known as SAPUI5 which is built on top of HTML5 and is compatible with any device and any screen size. The first announcement from SAP about Fiori was in May 2013 with the first release of 25 transactional Fiori apps for the most common business functions, such as self-services tasks which known as ESS/MSS.Today, there are more than 1140 true Fiori apps available in Fiori library. The number of apps can partially supplement the previous GUI transactions. SAP offers three types of Fiori apps with different database requirements. A distinction is made between Transactional apps, Analytical apps and factsheets. Only Transactional apps can run on any database that supports SAP ERP. The other 2 types require SAP HANA as database. Since 2013, Fiori has made great progress and will continue in the coming years.BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt 24 pp. Englisch.

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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Bachelor Thesis from the year 2017 in the subject Computer Science - Commercial Information Technology, grade: 1.3, Heilbronn University, language: English, abstract: White-collar crime is and has always been an urgent issue for the society. In recent years, white-collar crime has increased dramatically by technological advances. The studies show that companies are affected annually by corruption, balance-sheet manipulation, embezzlement, criminal insolvency and other economic crimes. The companies are usually unable to identify the damage caused by fraudulent activities. To prevent fraud, companies have the opportunity to use intelligent IT approaches. The data analyst or the investigator can use the data which is stored digitally in today's world to detect fraud.In the age of Big Data, digital information is increasing enormously. Storage is cheap today and no longer a limited medium. The estimates assume that today up to 80 percent of all operational information is stored in the form of unstructured text documents. This bachelor thesis examines Data Mining and Text Mining as intelligent IT approaches for fraud detection in white-collar crime. Text Mining is related to Data Mining. For a differentiation, the source of the information and the structure is important. Text Mining is mainly concerned with weak- or unstructured data, while Data Mining often relies on structured sources.At the beginning of this bachelor thesis, an insight is first given on white-collar crime. For this purpose, the three essential tasks of a fraud management are discussed. Based on the fraud triangle of Cressey it is showed which conditions need to come together so that an offender commits a fraudulent act. Following, some well-known types of white-collar crime are considered in more detail.Text Mining approach was used to demonstrate how to extract potentially useful knowledge from unstructured text. For this purpose, two self-generated e-mails were converted into struc-tured format. Moreover, a case study will be conducted on fraud detection in credit card da-taset. The dataset contains legitimate and fraudulent transactions. Based on a literature research, Data Mining techniques are selected and then applied on the dataset by using various sampling techniques and hyperparameter optimization with the goal to identify correctly pre-dicted fraudulent transactions. The CRISP-DM reference model was used as a methodical procedure.

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Taschenbuch. Etat : Neu. Neuware -Bachelor Thesis from the year 2017 in the subject Computer Science - Commercial Information Technology, grade: 1.3, Heilbronn University, language: English, abstract: White-collar crime is and has always been an urgent issue for the society. In recent years, white-collar crime has increased dramatically by technological advances. The studies show that companies are affected annually by corruption, balance-sheet manipulation, embezzlement, criminal insolvency and other economic crimes. The companies are usually unable to identify the damage caused by fraudulent activities. To prevent fraud, companies have the opportunity to use intelligent IT approaches. The data analyst or the investigator can use the data which is stored digitally in today¿s world to detect fraud.In the age of Big Data, digital information is increasing enormously. Storage is cheap today and no longer a limited medium. The estimates assume that today up to 80 percent of all operational information is stored in the form of unstructured text documents. This bachelor thesis examines Data Mining and Text Mining as intelligent IT approaches for fraud detection in white-collar crime. Text Mining is related to Data Mining. For a differentiation, the source of the information and the structure is important. Text Mining is mainly concerned with weak- or unstructured data, while Data Mining often relies on structured sources.At the beginning of this bachelor thesis, an insight is first given on white-collar crime. For this purpose, the three essential tasks of a fraud management are discussed. Based on the fraud triangle of Cressey it is showed which conditions need to come together so that an offender commits a fraudulent act. Following, some well-known types of white-collar crime are considered in more detail.Text Mining approach was used to demonstrate how to extract potentially useful knowledge from unstructured text. For this purpose, two self-generated e-mails were converted into struc-tured format. Moreover, a case study will be conducted on fraud detection in credit card da-taset. The dataset contains legitimate and fraudulent transactions. Based on a literature research, Data Mining techniques are selected and then applied on the dataset by using various sampling techniques and hyperparameter optimization with the goal to identify correctly pre-dicted fraudulent transactions. The CRISP-DM reference model was used as a methodical procedure.Books on Demand GmbH, Überseering 33, 22297 Hamburg 100 pp. Englisch.

Taschenbuch. Etat : Neu. SAPUI5 and Fiori. Status and Future Perspective | Rohan Ahmed | Taschenbuch | 24 S. | Englisch | 2018 | GRIN Verlag | EAN 9783668714540 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

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Taschenbuch. Etat : Neu. Fraud Detection in White-Collar Crime | Rohan Ahmed | Taschenbuch | 100 S. | Englisch | 2018 | GRIN Verlag | EAN 9783668738355 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Seminar paper from the year 2017 in the subject Computer Science - Commercial Information Technology, grade: 1.7, Heilbronn University, language: English, abstract: Today almost every software and websites has a mobile compatible version and everyone can check anything on his mobile or tablet. This wasn't the case 7-8 years ago. For SAP, Graphical User Interface as known as GUI was very powerful at the time when SAP launched its ERP software. With time, many other software exists with the fleet of HTML5 based powerful and more appealing modern UI-technology.For this, the old GUI was not able to stand with it. As everyone knows, today are smartphones and tablets more powerful than pc's. So, it was very important for SAP to find a solution and its was SAP Fiori - 'One UX for all SAP Products'. Fiori is based on a framework known as SAPUI5 which is built on top of HTML5 and is compatible with any device and any screen size. The first announcement from SAP about Fiori was in May 2013 with the first release of 25 transactional Fiori apps for the most common business functions, such as self-services tasks which known as ESS/MSS.Today, there are more than 1140 true Fiori apps available in Fiori library. The number of apps can partially supplement the previous GUI transactions. SAP offers three types of Fiori apps with different database requirements. A distinction is made between Transactional apps, Analytical apps and factsheets. Only Transactional apps can run on any database that supports SAP ERP. The other 2 types require SAP HANA as database. Since 2013, Fiori has made great progress and will continue in the coming years. 24 pp. Englisch.

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Seminar paper from the year 2016 in the subject Computer Science - General, grade: 1.7, Heilbronn University, language: English, abstract: In this seminar thesis you will get a view about the Data Mining techniques in financial fraud detection. Financial Fraud is taking a big issue in economical problem, which is still growing. So there is a big interest to detect fraud, but by large amounts of data, this is difficult. Therefore, many data mining techniques are repeatedly used to detect frauds in fraudulent activities. Majority of fraud area are Insurance, Banking, Health and Financial Statement Fraud. The most widely used data mining techniques are Support Vector Machines (SVM), Decision Trees (DT), Logistic Regression (LR), Naives Bayes, Bayesian Belief Network, Classification and Regression Tree (CART) etc. These techniques existed for many years and are used repeatedly to develop a fraud detection system or for analyze frauds. 20 pp. Englisch.

Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Seminar paper from the year 2016 in the subject Computer Science - General, grade: 1.7, Heilbronn University, language: English, abstract: In this seminar thesis you will get a view about the Data Mining techniques in financial fraud detection. Financial Fraud is taking a big issue in economical problem, which is still growing. So there is a big interest to detect fraud, but by large amounts of data, this is difficult. Therefore, many data mining techniques are repeatedly used to detect frauds in fraudulent activities. Majority of fraud area are Insurance, Banking, Health and Financial Statement Fraud. The most widely used data mining techniques are Support Vector Machines (SVM), Decision Trees (DT), Logistic Regression (LR), Naives Bayes, Bayesian Belief Network, Classification and Regression Tree (CART) etc. These techniques existed for many years and are used repeatedly to develop a fraud detection system or for analyze frauds.Books on Demand GmbH, Überseering 33, 22297 Hamburg 20 pp. Englisch.

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Bachelor Thesis from the year 2017 in the subject Computer Science - Commercial Information Technology, grade: 1.3, Heilbronn University, language: English, abstract: White-collar crime is and has always been an urgent issue for the society. In recent years, white-collar crime has increased dramatically by technological advances. The studies show that companies are affected annually by corruption, balance-sheet manipulation, embezzlement, criminal insolvency and other economic crimes. The companies are usually unable to identify the damage caused by fraudulent activities. To prevent fraud, companies have the opportunity to use intelligent IT approaches. The data analyst or the investigator can use the data which is stored digitally in today's world to detect fraud.In the age of Big Data, digital information is increasing enormously. Storage is cheap today and no longer a limited medium. The estimates assume that today up to 80 percent of all operational information is stored in the form of unstructured text documents. This bachelor thesis examines Data Mining and Text Mining as intelligent IT approaches for fraud detection in white-collar crime. Text Mining is related to Data Mining. For a differentiation, the source of the information and the structure is important. Text Mining is mainly concerned with weak- or unstructured data, while Data Mining often relies on structured sources.At the beginning of this bachelor thesis, an insight is first given on white-collar crime. For this purpose, the three essential tasks of a fraud management are discussed. Based on the fraud triangle of Cressey it is showed which conditions need to come together so that an offender commits a fraudulent act. Following, some well-known types of white-collar crime are considered in more detail.Text Mining approach was used to demonstrate how to extract potentially useful knowledge from unstructured text. For this purpose, two self-generated e-mails were converted into struc-tured format. Moreover, a case study will be conducted on fraud detection in credit card da-taset. The dataset contains legitimate and fraudulent transactions. Based on a literature research, Data Mining techniques are selected and then applied on the dataset by using various sampling techniques and hyperparameter optimization with the goal to identify correctly pre-dicted fraudulent transactions. The CRISP-DM reference model was used as a methodical procedure. 100 pp. Englisch.

Taschenbuch. Etat : Neu. Data mining techniques in financial fraud detection | Rohan Ahmed | Taschenbuch | 20 S. | Englisch | 2018 | GRIN Verlag | EAN 9783668709287 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu Print on Demand.