Business intelligence tool analysis and exploration of Attendance Management System (AMS) using Auto Regression TREE (ART)

"Time is money." There is perhaps no more accurate analogy in business. Unfortunately, if there is one thing that we all have difficulty managing, it is time. That includes the ability to accurately measure and manage the attendance of staff. Sure, most organizations have been tracking tim...

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التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Badr Aldeen, Badr Abdallah
التنسيق:	أطروحة
اللغة:	English English
منشور في:	2016
الموضوعات:	H Social Sciences (General)
الوصول للمادة أونلاين:	http://eprints.utem.edu.my/id/eprint/18686/1/Business%20Intelligence%20Tool%20Analysis%20And%20Exploration%20Of%20Attendance%20Management%20System%20%28AMS%29%20Using%20Auto%20Regression%20Tree%20%28ART%29.pdf http://eprints.utem.edu.my/id/eprint/18686/2/Business%20Intelligence%20Tool%20Analysis%20And%20Exploration%20Of%20Attendance%20Management%20System%20%28AMS%29%20Using%20Auto%20Regression%20Tree%20%28ART%29004.pdf
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spelling	my-utem-ep.186862023-08-03T10:47:54Z Business intelligence tool analysis and exploration of Attendance Management System (AMS) using Auto Regression TREE (ART) 2016 Badr Aldeen, Badr Abdallah H Social Sciences (General) HD Industries. Land use. Labor "Time is money." There is perhaps no more accurate analogy in business. Unfortunately, if there is one thing that we all have difficulty managing, it is time. That includes the ability to accurately measure and manage the attendance of staff. Sure, most organizations have been tracking time worked for basic payroll functions for some time. But using staff attendance data for long-term labor forecasting, short-term staff scheduling, or overall labor cost reductions are functions that have eluded most but the top performing companies. A growing number of organizations are implementing attendance management system (AMS), and AMS now finds itself in the middle of this movement. The rising interest in automated AMS is driven by the difficulty in tracking what has become a rapidly moving target. Organizations must respond to constantly changing market and industry conditions, try to manage an increasingly diverse workforce, and increasingly disperse workers.The central goal of this study is to enhance a model for human resource (HR) assignments in skill-based environments. AMS are tools for efficient management of labour resources and accurate labour reporting. The AMS moduale implemented using Microsoft .NET environment is presented in the study. Analytical capabilities of data collected by the system by means of business intelligence platform of SQL Server 2005 are considered.Some charts and figures produced by data mining tools including OLAP, and Time Series are given. AMS deals with the maintenance of the staff attendance details. It is generating the attendance of the staff on basis of presence. It is maintained on the daily basis of their attendance. The staff attendance reports based on daily, weekly or monthly and consolidate will be generated. 2016 Thesis http://eprints.utem.edu.my/id/eprint/18686/ http://eprints.utem.edu.my/id/eprint/18686/1/Business%20Intelligence%20Tool%20Analysis%20And%20Exploration%20Of%20Attendance%20Management%20System%20%28AMS%29%20Using%20Auto%20Regression%20Tree%20%28ART%29.pdf text en public http://eprints.utem.edu.my/id/eprint/18686/2/Business%20Intelligence%20Tool%20Analysis%20And%20Exploration%20Of%20Attendance%20Management%20System%20%28AMS%29%20Using%20Auto%20Regression%20Tree%20%28ART%29004.pdf text en validuser http://library1.utem.edu.my:8000/elmu/index.jsp?module=webopac-d&action=graphicFullDisplayRetriever.jsp&szMaterialNo=0000101479 mphil masters Universiti Teknikal Malaysia Melaka Faculty of Information and Communication Technology
institution	Universiti Teknikal Malaysia Melaka
collection	UTeM Repository
language	English English
topic	H Social Sciences (General) H Social Sciences (General)
spellingShingle	H Social Sciences (General) H Social Sciences (General) Badr Aldeen, Badr Abdallah Business intelligence tool analysis and exploration of Attendance Management System (AMS) using Auto Regression TREE (ART)
description	"Time is money." There is perhaps no more accurate analogy in business. Unfortunately, if there is one thing that we all have difficulty managing, it is time. That includes the ability to accurately measure and manage the attendance of staff. Sure, most organizations have been tracking time worked for basic payroll functions for some time. But using staff attendance data for long-term labor forecasting, short-term staff scheduling, or overall labor cost reductions are functions that have eluded most but the top performing companies. A growing number of organizations are implementing attendance management system (AMS), and AMS now finds itself in the middle of this movement. The rising interest in automated AMS is driven by the difficulty in tracking what has become a rapidly moving target. Organizations must respond to constantly changing market and industry conditions, try to manage an increasingly diverse workforce, and increasingly disperse workers.The central goal of this study is to enhance a model for human resource (HR) assignments in skill-based environments. AMS are tools for efficient management of labour resources and accurate labour reporting. The AMS moduale implemented using Microsoft .NET environment is presented in the study. Analytical capabilities of data collected by the system by means of business intelligence platform of SQL Server 2005 are considered.Some charts and figures produced by data mining tools including OLAP, and Time Series are given. AMS deals with the maintenance of the staff attendance details. It is generating the attendance of the staff on basis of presence. It is maintained on the daily basis of their attendance. The staff attendance reports based on daily, weekly or monthly and consolidate will be generated.
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Badr Aldeen, Badr Abdallah
author_facet	Badr Aldeen, Badr Abdallah
author_sort	Badr Aldeen, Badr Abdallah
title	Business intelligence tool analysis and exploration of Attendance Management System (AMS) using Auto Regression TREE (ART)
title_short	Business intelligence tool analysis and exploration of Attendance Management System (AMS) using Auto Regression TREE (ART)
title_full	Business intelligence tool analysis and exploration of Attendance Management System (AMS) using Auto Regression TREE (ART)
title_fullStr	Business intelligence tool analysis and exploration of Attendance Management System (AMS) using Auto Regression TREE (ART)
title_full_unstemmed	Business intelligence tool analysis and exploration of Attendance Management System (AMS) using Auto Regression TREE (ART)
title_sort	business intelligence tool analysis and exploration of attendance management system (ams) using auto regression tree (art)
granting_institution	Universiti Teknikal Malaysia Melaka
granting_department	Faculty of Information and Communication Technology
publishDate	2016
url	http://eprints.utem.edu.my/id/eprint/18686/1/Business%20Intelligence%20Tool%20Analysis%20And%20Exploration%20Of%20Attendance%20Management%20System%20%28AMS%29%20Using%20Auto%20Regression%20Tree%20%28ART%29.pdf http://eprints.utem.edu.my/id/eprint/18686/2/Business%20Intelligence%20Tool%20Analysis%20And%20Exploration%20Of%20Attendance%20Management%20System%20%28AMS%29%20Using%20Auto%20Regression%20Tree%20%28ART%29004.pdf
_version_	1776103102135402496

Business intelligence tool analysis and exploration of Attendance Management System (AMS) using Auto Regression TREE (ART)

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