Abstract
Nowadays is referred to as the era of big data where every individual or organization produces large amounts of data through various digital devices used. Higher education institutions continuously produce data and only strore it in various data formats and physical files, thus creating massive raw data. Collection of data created from a long time produces big data, so it is difficult to be treated manually or processed using conventional data processing applications. Higher education is an educational institution that always produces data from time to time continuously through various affairs in each of its parts. Multi campus institutions have physical locations that are far apart from one to another with more than one physical infrastructure. Each campus branch produces its own data, this requires a though about how to build a large data infrastructure, so that stakeholders can use various data from each branch of the campus for the analysis process of various needs of tertiary institutions. Multi campus big data infrastructure is the focus of this research, through the stages of big data sampling on multiple campuses using statistical and prototyping methods, so that data flow and data unity can be standardized in all branches of the campus by minimizing infrastructure constraints that are based on socioculture and spatial aspects.
Highlights
Higher education institutions continuously produce data and only strore it in various data formats and physical files, creating massive raw data
Collection of data created from a long time produces big data, so it is difficult to be treated manually or processed using conventional data processing applications
Multi campus big data infrastructure is the focus of this research, through the stages of big data sampling on multiple campuses using statistical and prototyping methods, so that data flow and data unity can be standardized in all branches of the campus by minimizing infrastructure constraints that are based on socioculture and spatial aspects
Summary
Higher education institutions continuously produce data and only strore it in various data formats and physical files, creating massive raw data. Adopsi big data pada perguruan tinggi multi kampus dapat dimanfaatkan melalui data analytics untuk berbagai keperluan yang berkaitan dengan pengambilan keputusan.
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