Discovering inactive students patterns and trends by applying data warehouse and visualisation on campus student record

Dyah Ayu Anggreini Tuasikal; Mohammad Shobri; Abba Suganda Girsang

doi:10.1117/12.2566981

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1 June 2020 Discovering inactive students patterns and trends by applying data warehouse and visualisation on campus student record

Dyah Ayu Anggreini Tuasikal, Mohammad Shobri, Abba Suganda Girsang

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Proceedings Volume 11515, International Workshop on Advanced Imaging Technology (IWAIT) 2020; 1151536 (2020) https://doi.org/10.1117/12.2566981
Event: International Workshop on Advanced Imaging Technologies 2020 (IWAIT 2020), 2020, Yogyakarta, Indonesia

Abstract

Inactive students is one of the problems that is often experienced by several campuses in Indonesia There are several factors that cause students to be inactive which can be categorized into two, namely not officially active and not official. Students are informal and inactivity can lead to other problems. Therefore, college students require active data processing to read and visualize trends that can be used as supporting data for policy making in order not conclude other problems. By using a data warehouse applications, where the ETL process is done as a backend process that can provide supporting data to record and process the data the students are not active. Visualization of inactive student trends is useful for the campus to help display data in an easily understood model. This aims to enable the campus to learn trends and help the campus determine strategic policies so as to reduce the number of levels of inactive students in lectures.

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Dyah Ayu Anggreini Tuasikal, Mohammad Shobri, and Abba Suganda Girsang "Discovering inactive students patterns and trends by applying data warehouse and visualisation on campus student record", Proc. SPIE 11515, International Workshop on Advanced Imaging Technology (IWAIT) 2020, 1151536 (1 June 2020); https://doi.org/10.1117/12.2566981

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