Implementasi Analisis Big Data untuk Memprediksi Kelulusan Mahasiswa Fakultas Teknik Universitas Langlangbuana - Chintia Putri Demasari; Nova Ariyanti; Prayoga Galih Muharan; Benie Ilman (Jurnal Accounting Information System (AIMS), 2023)
The Faculty of Engineering at the University of Langlangbuana has a large number of students who do not graduate on time. Based on observations and data available at the Faculty of Engineering, Langlangbuana University, there are still many students who do not graduate on time which causes a decrease in the score in the accreditation assessment criteria. The timely graduation of students is one of the criteria for accreditation assessment at Langlangbuana University. To get good accreditation results, it is necessary to predict the graduation rate with a method Big Data Analytic so that it can anticipate delays in graduating students at the Faculty of Engineering, Langlangbuana University. The database owned by Langlangbuana University can be used as a reference as material for predicting student graduation at the Faculty of Engineering. With the digitization of data which has resulted in a very rapid data spike, Langlangbuana University requires Big Data Analytic. The results showed that using Big Data Analytics can improve decision making to improve student performance and success and also all related aspects, especially at the Faculty of Engineering, Langlangbuana University.