Proceedings of the International Interdisciplinary Conference, Vienna

THE APPLICATION OF POWER BI IN PLANNING FOR NEW STUDENTS APPLICATION IN THE POST-GRADUATE PROGRAMS OF SUAN SUNANDHA RAJABHAT UNIVERSITY, THAILAND

SUWANNEE PUNSIRI, ASSISTANT PROFESSOR DR. CHUENAAROM CHANTIMACHAIAMORN

Abstract:

The primary objective of this research was to develop the decision support system for the Academic Section that helps with new student admission in the post-graduate programs of the Graduate School, Suan Sunandha Rajabhat University, Thailand. This decision support system is expected to help in the analysis of the possibility of the program application and it also provides clear guideline for related staff members to work. Moreover, it can help with the development and modification of the marketing strategies so that the university can compete with other universities more efficiently. In conducting this research, students’ information in each program from the registration section of the Graduate School as well as the Academic Service Department of the university between 2013-2017 was gathered. The decision system was developed by utilizing Microsoft SQL Server 2016 which was used to collect and stored the students’ information. Apart from that SQL Server Business Intelligence Development Studio in the part of Integration Service was used to retrieve, modify and enter the data in the ETL process. Then, the data were examined for their relationship via Analysis Service. The result of this research was a data cube in which multiple dimensions of information can be retrieved and the Business Intelligence Program, known as ‘Power BI’ which could present report in a form of a dashboard via internet. With these innovations, the university administrators could view the overall data. This study also evaluated satisfaction towards the use of this program from ten users and found that they were satisfied with its capability in supporting the decision, its accuracy and its function. The overall satisfaction was rated at a high level with a mean score of 4.07 and standard deviation of 0.64.

Keywords: Database, Business Intelligence

DOI: 10.20472/IAC.2018.001.014

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