Home Solutions CREATE AND EVOLVE NEW EMPLOYEE ATTENDANCE SYSTEM
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Data collection and analysis process is gathering as well as measuring information on the variables of interest in an established fashion of system. The components of data collection in research is common to all the fields of the study that includes physical and social sciences, humanities and business related issues. Present report deals with doing research on the importance of location based attendance. The aim of the project, objectives as well as problem statement is discussed in the present task. In addition, the adopted theories or framework related to the project is described in the report. Along with these, methodology and data collection/ analysis techniques are presented in the report. The paper also presents description of the proposed artefact and project completion plan.
The main of this project is to create a mobile application for effective location based attendance system by using GPS and integrate payroll system with the new system or the existing system.
Objectives of the project can be explained as followed.
In addition, there are some errors and misuses are found while using the manual system. Thus, there is a problem identified in the manual system and requires an automated system fulfilling the requirements.
However, installation of automated location based system has some issues that are included in the problem statement. Location based attendance may lead to have fake attendance. In addition, as the location based attendance is based on GPS system, it is required to have privacy for the staffs that can be hampered through application of the attendance of the staffs based on their location. It is also important to have internet connection for giving attendance in the office, which lacks sometimes among the staffs. It develops several issues among the staffs of the organization.
Adopted theories/ Framework:
PIECES framework- In order to identify the issues in the project problem, PIECES framework would be helpful in this aspect. In this framework, performance of the manual attendance system can be detected throughout and response time. Analysis of information is useful to find out the lack of any information that is essential to fulfil the objective as well as accuracy of the information in the study. Analysis of the inputs helps to analyze the data that are not captured. In addition, it is analyzed of illegal data in the manual format of attendance tracking of the staffs.
Analysis of the stored data is useful to find out the data that is not secured and not well organized. Data that is not flexible and difficult to encounter the needs can be analyzed with the help of the framework. Moreover, costs of the system that is untraceable and too high can be explained by using the framework. It is important to control the security of the system.
The analysis is useful to analyze the information that helps to find the loopholes in the manual attendance tracking system. It results to enable automated system for tracking attendance of the employees as the solution of previous issue. In the contrary, PIECES framework is helpful to analyze performance of the staffs and attendance while conducting investigation on the location based attendance tracker system. The PIECES framework has been selected in order to analyze the data present in the system. It enables to analyze inputs, outputs, stored data, and economics, control as well as efficiency along with the services related to the use of automated location based attendance system.
In below, we have compared some of the theories related to our location based attendance system because by using these frameworks/theories our team identified issues/problems. Technology acceptance model and code and fix model are not efficient.
EASE OF USE
CONTROL AND SECURITY
Technology Acceptance Model
Code and Fix Model
Table 1: Comparison of Theories
For fulfilling the outcome of the project, our team suggested that different method of collection and analyzing data. After lots of research it has been suggested that option of choosing both qualitative and quantitative methods of collecting and analyzing the data. Moreover, for getting outcome of the project different types of data had been collected from different sources like interviews, surveys, case studies, focus group and so on. We compared the analyzed data with the existing and already published data so, that quality of data could be analyzed for making our research more relevant. For identifying the quality of data our team had analyzed the data according to the desired result.
In brief, it could be identified that semi structured interviews; surveys were conducted as a part of the primary data collection methods and different tools were used to analyzing the result.
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