Development of Academic Data Warehouse (Case Study: Major-Minor Curriculum Bachelor Program of Computer Science Department at IPB).
Pembangunan Data Warehouse Akademik (Studi Kasus : Kurikulum Mayor-minor Program Sarjana Departemen Ilmu Komputer IPB)
Seminar, Kudang Boro
Adrianto, Hari Agung
MetadataShow full item record
University need in-depth knowledge to conduct evaluation, planning and decision making. Static reporting systems are considered not flexible in exploring information within an existing information system. Dynamic reporting tools are needed so that users can perform data analysis by looking at the available data from various dimensions. A solution proposed in this paper is to develop a data warehouse. Information for the data warehouse is extracted from the existing operational data stores. The research represented here elaborates the use of data warehouse for academic purpose at Bogor Agricultural University especially for Computer Science Department, starting from the planning stage to design and implementation stage. Online Analytical Processing (OLAP) integrated with data warehouse is developed to analyze academic data including student‟s grades, GPA, and cumulative GPA for every semester as well as every academic year. This research aims to develop a data warehouse and web-based OLAP using Mondrian 3.1.6 as OLAP server. The steps in this research are 1) data preprocessing including data cleaning, data integration, data transformation and 2) data warehouse using galaxy scheme and OLAP development. This research produces a data warehouse and web-based OLAP containing three data cubes: Subject_Grade, GPA, and Minor. Data warehouse consists of seven dimensions (Time, Generation, Sex, Subject, Grade, Status of study, and Minor) and three tables (Subject_Grade, GPA, and Minor). This application provides information as of bar chart, line chart, pie chart, report with Excel Spreadsheet, and file pdf. Users can explore this application to get academic related information in Computer Science Department by application OLAP operations including roll-up, drill-down, dice, slice, drill through, pivot, etc.
- UT - Computer Science