Teknik Prediksi Data Mining pada Perguruan Tinggi sebagai Kajian Literatur

Higher education is an interesting research object because there are complex research topics that can be used by students, lecturers or researchers. One of the research topics that uses university research objects is related to data mining. Data mining is a technique that can be used to extract data into knowledge and functions to find patterns from large data. There are currently 5 data mining roles used, namely Estimation, Prediction, Classification, Clustering and Association. One of the techniques used is Prediction. The aim of this research is to conduct systematic literature review research related to data mining prediction techniques with 3 aspects, namely Algorithms, Frameworks/Methods and Research Topics. The results of this research are the Algorithm Trends used in the research, namely the Support Vector Machines (SVM), Random Forest, Decision tree (DT), Artificial Neural Networks (ANN), Naive Bayes (NB), Neural Network (NN), and K- Nearest Neighbor (KNN) Framework used is Data Mining, Educational data mining and Machine Learning and the trending topic is related to Prediction, namely measuring Student performance.