Interpretasi Model Machine Learning Terhadap Data Siswa Siswi di Sekolah Internasional

Abstract

This TA report is entitled "Machine Learning Interpretation of International Student Data". This report contains an interpretation effort that can be made by a machine learning on international student data. This report aims to find an insight from plots that have been created and interpreted using machine learning algorithms. The dataset in this report is a dataset related to scores of international students. To perform the interpretation, the algorithm used is a linear regression algorithm. The applications and IDEs used in carrying out the machine learning interpretation process are Jupyter Notebook and R Studio. Jupyter Notebook is used to try to find the most suitable algorithm in the case of international student data. R Studio is used to create plots which will later be used to interpret the data. In R Studio,  created plot  is an effect plot and also an ALE plot. Both will be interpreted and the results of the interpretation can be used as an insight to find the cause of the predicted result of the value to be predicted.